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Transcript of spatial dimensions of filariasis in kumbakonam control unit
SPATIAL DIMENSIONS OF FILARIASIS IN KUMBAKONAM CONTROL UNIT, TAMIL NADU, INDIA: A GIS APPROACH
Thesis submitted to the Bharathidasan University
for the award of degree of Doctor of Philosophy in Geography
Submitted by
S. Vadivel Assistant Professor and
Part – time Research Scholar,
Research Supervisor
Dr.P.H.Anand, M.Sc.,M.Phil.,Ph.D. Associate Professor and Head
Post Graduate and Research Department of Geography, Government Arts College (Autonomous),
Kumbakonam – 612 001, Tamil Nadu, India
May - 2012
DECLARATION
I do hereby declare that the thesis entitled “SPATIAL DIMENSIONS
OF FILARIASIS IN KUMBAKONAM CONTROL UNIT, TAMIL NADU, INDIA: A
GIS APPROACH”, which I am submitting for the award of Degree of
Doctor of Philosophy in Geography, to the Bharathidasan University, is
the original work carried out by me, in the Post Graduate and Research
Department of Geography, Government Arts College (Autonomous),
Kumbakonam 612 001, Tamil Nadu, India, under the guidance and
supervision of Dr. P.H. Anand, Associate Professor and Head, PG and
Research Department of Geography, Government Arts College
(Autonomous), Kumbakonam.
I further declare that this work has not been submitted earlier in
this or any other University and does not form the basis for the award
of any other degree or diploma.
Kumbakonam S. Vadivel
4th May 2012 Part-time Research Scholar
PG and Research Department of Geography (DST-FIST Recognized)
Government Arts College (Autonomous), (Accredited by NAAC // AICTE and Affiliated to Bharathidasan University)) Kumbakonam, 612 001, Tamil Nadu
Dr.P.H.Anand,M.Sc.,M.Phil.,Ph.D. 04-05-2012 Associate Professor and Head,
CERTIFICATE
This is to certify that the thesis entitled “SPATIAL DIMENSIONS OF
FILARIASIS IN KUMBAKONAM CONTROL UNIT, TAMIL NADU, INDIA: A GIS
APPROACH”, submitted by Mr. S. Vadivel, for the award of Doctor of
Philosophy in Geography, in the Bharathidasan University was carried
out at the Post Graduate and Research Department of Geography,
Government Arts College (Autonomous), Kumbakonam, 612001 under
my guidance and supervision after fulfilling the basic requirements
specified by the University.
(P.H. ANAND)
Research Advisor
ACKNOWLEDGEMENT
More than 1.3 billion people in 72 countries worldwide are threatened by
lymphatic filariasis, commonly known as elephantiasis. Over 120 million people are
currently infected, with about 40 million disfigured and incapacitated by the disease.
Lymphatic filariasis can result in an altered lymphatic system and the abnormal
enlargement of body parts, causing pain and severe disability. Acute episodes of local
inflammation involving the skin, lymph nodes and lymphatic vessels often accompany
chronic lymphoedema. To interrupt transmission WHO recommends an annual mass
drug administration of single doses of two medicines to all eligible people in endemic
areas.
Lymphatic filariasis, commonly known as elephantiasis, is a neglected tropical
disease. Infection occurs when filarial parasites are transmitted to humans through
mosquitoes. When a mosquito with infective stage larvae bites a person, the parasites are
deposited on the person's skin from where they enter the body. The larvae then migrate to
the lymphatic vessels where they develop into adult worms in the human lymphatic
system. Infection is usually acquired in childhood, but the painful and profoundly
disfiguring visible manifestations of the disease occur later in life. Whereas acute
episodes of the disease cause temporary disability, lymphatic filariasis leads to permanent
disability.
Currently, more than 1.3 billion people in 72 countries are at risk. Approximately
65 per cent of those infected live in the WHO South-East Asia Region, per cent in the
African Region, and the remainder in other tropical areas. Lymphatic filariasis afflicts
over 25 million men with genital disease and over 15 million people with lymphoedema.
Since the prevalence and intensity of infection are linked to poverty, its elimination can
contribute to achieving the United Nations Millennium Development Goals.
World Health Assembly Resolution 50.29 encourages Member States to eliminate
lymphatic filariasis as a public-health problem. In response, WHO launched its Global
Programme to Eliminate Lymphatic Filariasis (GPELF) in 2000. The goal of the GPELF
is to eliminate lymphatic filariasis as a public-health problem by 2020. The strategy is
based on two key components: interrupting transmission through annual large-scale
treatment programmes, known as mass drug administration, implemented to cover the
entire at-risk population; alleviating the suffering caused by lymphatic filariasis through
morbidity management and disability prevention.
The present research is focused upon taking all the parameters concerned are the
latest technological development to identify and analyze the problem by using GIS and
GPS technology. The research would help the administration to plan for the future and
the scientists to continue in the Filarial related research. For the successful completion of
the work several people have extended their assistance and help. I mention few of them
here and keep the rest in my mind. At the outset I thank our Principal i/c
Dr. J. Govindadoss, for extending moral and administrative support for the successful
completion of this work.
I remember the similar support, which was extended to me by the then Principals,
of this college. I thank all the staff members of the Filiarial Contol unit, which is under
the control of Director of Public Health and Preventive Medicine, Chennai and
Kumbakonam Filarial Control Unit.
I convey my sincere thanks to Prof. I.C. Kamaraj and Prof. V. Kumaraswamy,
former Heads of the Department of Geography, for consistent encouragement and critical
suggestions as and when I approach them.
I wish to express my deepest gratitude to Dr. P.H. Anand, Associate Professor
and Head, P.G and Research Department of Geography, Government Arts College
(Autonomous), Kumbakonam for his unencumbered, exemplary guidance, indefatigable
efforts to steer in the right direction, bountiful scholarly advice, undiminished zeal for
extracting fruitful information and for his painstaking efforts and deepest understanding
of my needs in this research.
I extend my sincere thanks to Dr. P. Thirumalai, Assistant Professor of
Geography, P.G and Research Department of Geography, government arts college
(Autonomous) Kumbakonam for giving a good shape to this project. I also convey my
deep sense of gratitude to my colleagues, Dr. P. Arul, Dr. B. Gobu, Dr. R. Maniyosai,
Thiru. K.K. Jayakumar, Thiru. A. Senthilvelan and Thiru. R. Thulasiraman.
I appreciate the students of M.Sc., Geography, of this college for the assistance during
research work.
The present work will be incomplete but for the perfect tolerance, sacrifice,
boundless love and ceaseless prayers of my parents, wife Mrs. Anbarasivadivel and
childrenV. Sivabalan, V. Sivakrishnan and relatives for providing calm atmosphere
during the research work. Last but not the least I am very much thankful to my colleague
Dr. J. Senthil Assistant Professor for his wholehearted support and assistance provided
during the GPS data collection.
S. Vadivel
CONTENTS
Chapter One
PROBLEM STATEMENT AND PROCEDURES
Page #
1.1 Filariasis: Definition and Meaning 1 1.2 History of Lymphatic Filariasis: 2000BC-500AD 3 1.2.1 Discovery of Symptoms: 1588-1592 3 1.2.2 Discovery of Microfilariae: 1863 and 1866 4 1.2.3 Discovery of the Adult Worm: 1876 4 1.2.4 Discovery of the Life Cycle: 1877 4 1.2.5 Discovery of Transmission: 1900 5 1.2.6 Current Discoveries 5 1.3 Identification Methods: Filariasis 5 1.3.1 Infections Agents 6 1.3.2 Mode of Transmission 6 1.3.3 Incubation period 7 1.3.4 Period of communicability 7 1.3.5 Vector Aspects 7 1.3.6 Aedes vectors 8 1.3.7 Mansonia vectors 8 1.3.8 Anopheles vectors 8 1.4 Types of filariasis 9 1.5 Worms that cause filariasis 9 1.6 Lymphatic filarial diseases 10 1.7 Geographical Distribution of Filariasis in Select Countries 11 1.8 Geographical variation in transmission 14 1.9 Filariasis in Asia 16 1.10 Filariasis in India 16 1.11 Filariasis in Tamil Nadu 17 1.12 National Control Strategies in select countries 19 1.13 Review of Literature 22 1.13.1 Socio cultural literature 25 1.14 Impact on infected individuals 27 1.14.1 Current knowledge about LF’s sociocultural burden 27 1.14.2 Impact upon lifestyle and economic opportunities 29 1.15 Impacts on the LF elimination programme 30 1.15.1 Paucity of LF-related sociocultural research 30 1.15.2 Beliefs about disease causality and transmission 31
1.15.3 Community ownership of treatment programmes 32 1.15.4 The value of increasing our sociocultural understanding 33 1.16 Problem Statement 36 1.17 Objectives 36 1.18 Methodology 37
Chapter Two
PROFILE OF THE STUDY AREA
2.1 Introduction 39 2.2 Etymology 40 2.3 History 40 2.4 Geography 42 2.4.1 Topography 44 2.4.2 Drainage 44 2.4.3 Soils 44 2.4.4 Climate 44 2.4.5 Temples 45 2.5 Municipal administration and politics 47 2.6 Economy 47 2.7 Transport and communication 48 2.8 Education 49 2.9 Filariasis: Night Clinic and Administrative Functions 50 2.10 Major Industries 52 2.11 Population Characteristics 52 2.12 Landuse
53
Chapter Three
CREATION OF GIS INFORMATION BASE FOR FILARIASIS PATIENTS
3.1 Introduction 54 3.2 Using GIS for Public Health 57 3.3 The Business of Health Care Geographic 58 3.4 A Wealth of Tools 59 3.5 Tomorrow's Health Care 61 3.6 GIS Information Base filariasis Patients in Kumbakonam: 1998-
2008
63 3.7 Conclusion 66
Chapter Four
DIMENSIONS OF FILARIASIS IN KUMBAKONAM: A FACTOR ANALYTIC METHOD
4.1 Introduction 67 4.2 Filariasis in Kumbakonam 73 4.3 Technique of Analysis 73 4.3.1 The Process of Factor Analysis: Data Matrix 75 4.4 Extracting the factors 77 4.5 Interpretation of the factors 78 4.6 Household level variation in vector infection and mf prevalence 80 4.6.1 Households with mf carriers 80 4.6.2 Households with infected mosquitoes 81 4.6.3 Transmission dynamics 81 4.6.4 No. of mf carriers 81 4.6.5 Antigenaemia prevalence 81 4.7 Filariasis in Kumbakonam: Spatial Dimensions 82 4.7.1 Dimension-I: Quality of Life 88 4.7.2 Dimension-II: Environmental Perception 89 4.7.3 Dimension-III: Stage of Filariasis and Medical Treatment 89 4.7.4 Dimension-IV: Health Care towards the Disease 90 4.7.5 Dimension-V: Psychological Attitudes and Awareness Measures 91 4.8 Conclusion 91
Chapter Five RECOMMENDATIONS AND CONCLUSION
92
References
Appendices
Publications
LIST OF TABLES
2.1 Growth of Population in Kumbakonam: 1901 - 2011 52
2.2 Different Types of Land use in Kumbakonam 53
3.1 Variable Description and Variable Code 83
3.2 Principle Component Matrix 85
3.3 Rotated Component Matrix 86
3.4 Spatial Dimensions of Filariasis in Kumabakonam: Rotated Factor
Structure
87
LIST OF MAPS After Page #
3.1 GIS Map showing Administrative Units 64
3.2 GIS for the Spatial Distribution of Filarial Cases: 1998 64
3.3 GIS for the Spatial Distribution of Filarial Cases: 1999 64
3.4 GIS for the Spatial Distribution of Filarial Cases: 2000 65
3.5 GIS for the Spatial Distribution of Filarial Cases: 2001 65
3.6 GIS for the Spatial Distribution of Filarial Cases: 2008 65
1 Chapter
Problem Statement and Procedures
1.1 Filariasis: Definition and Meaning
Filariasis is an abnormal enlargement of any part of the body due to obstruction of
the lymphatic channels in the area (lymphatic system), usually affecting the arms, legs, or
external genitals. In tropical countries the most common cause is filariasis, infestation
with certain filaria, small parasitic roundworms of the genera Wuchereria bancrofti or
Brugia malayi that are introduced into the body by many species of mosquitoes. The
adult worms live in the lymphatic system, causing local inflammation, fibrosis, and
obstruction, and resulting in the characteristic enlargement and thickening of the skin.
The initial damage done by the worms can be greatly worsened by secondary bacterial
and fungal infections.
Recovery from filariasis is possible and surgery sometimes helps, but any
elephantiasis that develops during the disease cannot be cured. Ivermectin, an antifilarial
drug, has been effective with a single dose. Diethylcarbamazine often kills the adult
worms or impairs their reproductive capabilities, and the antibiotic doxycycline, which
works by killing symbiotic bacteria that live inside the worms, also eliminates adult
worms. Albendazole, in combination with others drugs, is being used in a program of
mass drug administration undertaken under the auspices of the World Health
Organization in an attempt to eliminate filariasis. Begun in 1999 the program treats an
entire population in an attempt to eradicate the worm. Control of mosquitoes also is
instrumental in holding down the incidence of the disease. Careful hygiene and other
measures that prevent and control subsequent bacterial and fungal infections in limbs or
genitals in which the lymphatic system has been damaged can reduce disfigurement and
suffering. Blocking of the lymph channels and elephantiasis can also result from
lymphogranuloma venereum, a sexually transmitted disease.
Filariasis is a general term applied to a group of diseases caused by certain
nematode worms known as filaria, which take 3-15 months to mature according to
species. The adult live in either the connective tissues by lymphatic or mesentery, where
they produce live embryos known as microfilaria. The disease process of fever and
inflammation of the lymphatic system in chronic infections leads to debility,
disfigurement and disability (Imperato, 1974; Benenson, 1975). Filariasis is a most
commonly and widely used term in the world, and in India, for describing the disease
process produced by W.bancrofti and to a lesser extent Brugia Malayi. It is a thread like
adult worm that lives in the human host for decades. Infected persons are infective only
when they have at least 12 microfilaria per 200mm of blood, as only such persons are
considered capable of infecting the vectors. Infected humans with microfilaria in their
blood serve as the reservoir for the disease (Raghavan, 1969; Hyma, Ramesh and
Gunasekaran, 1989). The usual clinic incubation period from Infective mosquito bite to
microfilaria appearing in the peripheral blood is 7-10 months. The shortest period
reported is 4 weeks (WHO, 1984; Assessment committee of the NFCP, 1961, 1967,
1971; Imperato, 1974).
1.2 History of Lymphatic Filariasis: 2000BC-500AD
Due to the fact that there is no reliable written record of lymphatic filariasis
before the 16th century, ancient historical evidence of lymphatic filariasis cannot be
confirmed. Lymphatic filariasis has been known to occur in the Nile region, and ancient
artifacts suggest that the disease may have been present as early as 2000BC. A statue of
Pharaoh Mentuhotep II depicts swollen limbs, a characteristic of elephantiasis, which is a
symptom of heavy lymphatic filariasis infection. Artifacts from the Nok civilization in
West Africa may show scrotal swelling, another characteristic of elephantiasis. The Nok
artifacts date much later than the Egyptian artifacts, from about 500AD.
The first written account of lymphatic filariasis comes from the ancient Greek and
Roman civilizations. In these civilizations, writers were even able to differentiate
between the similar symptoms of leprosy and lymphatic filariasis, describing leprosy as
"elephantiasis graecorum" and lymphatic filariasis as "elephantiasis arabum."
1.2.1 Discovery of Symptoms: 1588-1592
The first reliable documentation of lymphatic filariasis symptoms did not occur
until an exploration of Goa between 1588 and 1592. During this trip, Jan Huygen
Linschoten wrote that inhabitants were "all born with one of their legs and one foot from
the knee downwards as thick as an elephants leg." Although this was the first account of
lymphatic filariasis symptoms, more documentation was made in parts of Africa and Asia
soon after. In 1849, William Prout became the first to document a condition common to
lymphatic filariasis called chyluria. This occurs with the passage of lymph in the urine so
it appears milky. Such a description was made in Prout's book entitled On the Nature and
Treatment of Stomach and Renal Diseases.
1.2.2 Discovery of Microfilariae: 1863 and 1866
In 1863, French surgeon Jean-Nicolas Demarquay became the first to record the
observation of microfilariae in fluid extracted from a hydrocoele (another common
symptom of lymphatic filariasis). Three years later, Otto Henry Wucherer discovered
microfilariae in urine in Brazil. However, the connection between these two discoveries
was not made until Timothy Lewis noted the occurrence of microfilariae in both blood
and urine. Lewis was also the first to make the association between these microfilariae
and elephantiasis.
1.2.3 Discovery of the Adult Worm: 1876
Soon after the discovery of microfilariae, the adult worm was documented by
Joseph Bancroft. The observed species was later named after Bancroft, and we now
recognize it as W. bancroft.
1.2.4 Discovery of the Life Cycle: 1877
Perhaps the most important discovery related to lymphatic filariasis was that
made by Patrick Manson in 1877. Manson was the first to look for an intermediate host
for lymphatic filariasis microfilariae. In 1877, he was finally able to pinpoint the
microfilariae in mosquitoes. This discovery was later applied to other tropical diseases
such as malaria, and was the first discovery of an arthropod as a vector. However,
Manson incorrectly hypothesized that the transmission occurred when the mosquito
deposited the filaria in water that then infected humans through ingestion of contaminated
water or direct skin penetration.
1.2.5 Discovery of Transmission: 1900
In 1900, George Carmichael Low discovered microfilariae in the proboscis of
mosquitoes, and finally pinpointed the true mechanism of transmission. Due to this
discovery, we now know that transmission is due to an infective bite from a mosquito
vector.
1.2.6 Current Discoveries
As research on lymphatic filariasis continues, more and more discoveries are
made in regards to prevalence, treatment options, prevention methods, transmission
cycles, and even new species. Clearly, current information on lymphatic filariasis is not
complete, and further research is needed.
1.3 Identification Methods: Filariasis
A Bancroftian filariasis is an infection with the nematode worm Wuchereria
bancrofti. Man is the only vertebrate host. Early acute manifestations include fever,
lymphadenitis, and lymphangities of the extremities, orchitis, epididynitis, funichlitus and
abscess. Prolonged and repeated infection with obstruction to lymph flow often leds to
hydrococle or to elephantiasis of the limbs; genitalia or breasts or Chyluria. Female
worms give rise to embryos, which in the absence of lymphatic obstruction, reach the
blood stream.
Life Cycle - The adult worms reside in the lymphatics of the human host. Female
W. bancrofti measure 80–100 × 0.25 mm and the male 40 × 0.1 mm. The adult Brugia
spp. has only half of this dimension. Microfilariae are produced from ova in the uterus of
the female worm. They are sheathed and measure on average 260 × 8 µm (Figures 84.3,
84.4). Microfilariae are ingested by the vector female mosquito during a blood meal.
They escheat in the mosquito stomach, becoming first-stage larvae which penetrate the
stomach wall of the mosquito and migrate to the thorax muscles. There they develop
through two moults to the infective third-stage larvae (1500 × 20 µm). The development
in the mosquito takes a minimum of 10–12 days. Mature infective larvae then migrate to
the mouthparts of the mosquito from where they enter the skin of the human host,
probably through the puncture site made by the proboscis of the vector when it takes its
blood meal. The larvae migrate to the lymphatics and develop to adult worms.
Microfilariae appear in the blood after a minimum of 8 months in W. bancrofti and 3
months in B. malayi. The adult worms may live and produce microfilariae for more than
20 years, but on average the lifespan is shorter. Microfilariae have a lifespan of
approximately 1 year. Microfilarial densities may reach 10000 per mL of blood or more,
but are usually lower.
1.3.1 Infections Agents
Wuchereria bancrofti and Brugia malayi, and nematode worms and the most
important. Man with microfilaria in the blood; in malaysis, occasionally, other mammals
are infected with Brugia malayi.
1.3.2 Mode of Transmission
When a mosquito harboring infective larvae bites, W.bancrofti is transmitted to
the host. In fact W.bancrofti is transmitted by many species, the most important being
culex pipiens, C.fatigans, C.quique fasciatus, Aedes Polynesians and several of
Anopheles, some also vectors of malaria. B.malayi is transmitted by various species of
Mansonia, Anopheles, and Aedes. Microfilaria, picked up by a mosquito while feeding
on an infected person, penetrate the stomach wall of the mosquito, lodge in thoracic
muscles, develop into infective larvae which migrate to the proboscis and penetrate the
new host as the mosquito bites (Beneson, 1975:115)
1.3.3 Incubation period
It is likely that allergic inflammatory manifestations appear as early as three
months after infection. But microfilaria does not occur until months later.
1.3.4 Period of communicability
Filariasis is not directly transmitted from human to human. Human may infect
mosquito ass long microfilaria are present in the blood. The mosquito is infective from
about 10 days after a blood meal until all infective are discharged.
1.3.5 Vector Aspects
Te culex pipiens compels includes C.Pipiens, C.Quinquefasciatus, C.molestud,
C.pallens, C.australiens and C.globocaxitus. Many of these co-exist. C.pipiens has an
extensive distribution in temperate latitudes (Holarctic region) and at high attitudes (East
and West Africa) and lower latitude (In South Africa, North America, northern Europe
and Argentina). It is distribution is increasing with urbanization, and construction
activities have created many new, artificial water sources which serve as focal points for
the breeding of this opportunistic mosquito (Minjas and Kihamia, 1991).
C.quinque fascitus has colonized tropical and Sub-tropical latitudes. It has been
recorded up to 1,800 meters, in four altitudinal Zones in India. Its distributions are also
increasing with urbanization and human activity. Many rural pockets which are
comparatively free from this mosquito are becoming colonized. Cules fatigans, Prevalent
widely in India, breeds usually in collections of dirty of polluted water. It is the most
common species that carries the filarial infection. It is the most common species that
carries the filarial infection. Common sources are; Latins; Servage; Sullage; Drains; Cess
pools and other water collections; Industrial wastes; Domestic wastes; and Artificial
containers, inside and outside houses ( Rao, 1981). Other important vectors are Aedes
polynesiensis and several Anopheline species.
1.3.6 Aedes vectors
These are found in countries such as the Philippines, Samoa and French Polynesia
where studies (Lu, Valencia, Llagas, Baltazar, and Cahanding, 1983; Carme, Utahia,
Turiara, and Teuru, 1979, for example) have been made on species such as polynesiensis,
A.Samoanus and A.paecilicus. A.polynesiensis is freeholds crabholes water storage
drums, discarded automobile tires, cams, bottles, and coconut shells. This species has
been found to have a flight range of 400 mm coconut plantations and coastal villages.
A.samoanus on the other hand breeds in leaf axils. A poecilius prefers of breeds in axils
of banana trees in the Philippines.
1.3.7 Mansonia vectors
The genus mansonia is divided into two subgenera: Ansonia and mansonioides. It
is the subgenus mansouioides that includes the important vectors of lymphatic filariasis
caused by B.malyi in the southern and southern Asia. In the past decade, studies on
mansonia vectors have been mainly from India, Indonesia, Malaysia and Thailand.
Studies in Sarawak have shown that mansonia mosquitoes are less exophagic than those
in peninsula, Malaysia, Sabah and the southern Thailand.
1.3.8 Anopheles vectors
The genus Anopheles is important in the transmission of the periodic W.bancrofti
in Africa, southern Asia and the island of New Guinea. It is also a significant vector
periodic B.malayi in southern Asia new transmission and distribution records include
A.Gambae from the island I Grande Comoro, and A flavirostris from Sabah. No mosquito
other than A.barbirosttis has been identified as a vector of B.Timori WHO. 1992).
C.pallens occurs in China, Japan and the United States of America. C.Molestus is mostly
distributed in temperate latitude.
1.4 Types of filariasis
Filarial disease has until recently been synonymous with ‘filarial fever’. Filariasis
comprises of several diseases. Most are caused by filarial worms and are transmitted by
blood sucking flies. For example, dracunculiasis is a closely related metazoan disease
transmitted by water fleas. An onchocerciasis or river blinder which is transmitted by
black flies of the genus simulium is probably the most serious of the filarial diseases. It
affects more than 40 million people, mainly in Tropical Africa, but also in central and
south America. The foci in the eastern Mediterranean Region extend to Yemen and the
Sudan.
The manifestations of on chocerciasis are mainly intense itching and, ultimately in
many cases, blindness. The blindness is due to the millions of onchocrca volvulus
microfilaria scatted throughout the body, especially in the skin and the eyes. The adult
worms lodge themselves in the nodules in the subcutaneous and even in deeper tissues in
various parts of the body.
1.5 Worms that cause filariasis
Lymphatic filariasis is the result of infection by parasite nematode worms, both
males and females, of the family Filariidae. The males are 15-30 mm long; the females
are 30-60 mm long. The female continuously sheds microfilaria about 0.2-0.3 mm long in
the lymphatic system which pass subsequently in its blood vessels. Three species are
particularly frequent according to Kin Paniker and Vijay Dhanda (1992).
a. Wuchereria bancrofti leads the most severe form of lymphatic
filariasis, affecting limbs, breasts and genitalia and it can induce tropical
pulmonary Eosnophilia.
b. Brugia malayi and brugia timori cause less severe problems and affect
mainly the lower limbs. WHO estimates that there 90 million cases of
lymphatic filariasis in the world, in 76 countries; 905 million people live
areas where they are of risk contacting the disease.
1.6 Lymphatic filarial diseases
Lymphatic filariasis is one of the major public health problems in many
developing countries. These diseases affect about 90 million people in Asia, Africa and
South America in addition to an estimated 905 million directly exposed to the rise of
infection. These are responsible for considerable disability and disfigurement due to acute
ademolymphamngitis and chronic lesions like elephantiasis and hydrocoele .The parasites
that cause human lymphatic Filarasis are Wucheraria bancrofti, Brugia malayi (Riji,
1983) and B.timori. Adult worms lodge in lymphatic vessels. The microfilaria circulates
in the blood often in a nocturnally periodic pattern, and is transmitted by various genera
of mosquitoes.
Lymphatic filariasis is a major health problem in many part of India. The disease
is commonly seen among the poorest of the poor and has a very low public health rating
in the priorities of most countries where it is prevalent. Unlike Onchoceriasis, lymphatic
filariasis can be relatively safely and effectively treated with DEC which ,although
mainly microfilariacidal, may in large enough doses be microfilariacidal.In lymphatic
filariasis, DEC is however not without side effects which are related to the rapid
destruction of large number of microfilaria in patients with high levels of parasilamia.
1.7 Geographical Distribution of Filariasis in Select Countries
Lymphatic filariasis is a major public health problem in tropical countries. Recent
estimates suggest that some 120 million persons are infected world-wide; 107 million
with Wuchereria bancrofti and 13 million with Brugia malayi. The number of people
with physical disabilities due either to lymphoedema and hydrocele or the newly
recognised sub-clinical abnormalities of lymphatic and renal function are currently
estimated at 43 million, with Bancroftian filariasis accounting for almost 40 million of
these cases (Michael 1996).
The International Task Force on disease eradication identified lymphatic
filariasis as one of six potentially eradicable diseases since there are now good enough
tools to combat the disease (CDC, 1993). The World Health Assembly at its meeting in
May 1997 passed a resolution on the elimination of the disease as a public health problem
through mass treatment of affected populations and appropriate management of clinical
cases.
In order to initiate any disease control programme based on mass drug
distribution, one needs to understand the geographical distribution of the disease in the
affected countries in order to know where to target mass treatment. Unfortunately, data
on the distribution of lymphatic filariasis are not widely available primarily because the
standard procedures for determining which communities are affected are cumbersome,
time-consuming, expensive and very intrusive. In areas where the parasite exhibits a
nocturnal periodicity, parasitological examinations need to be done at night. This
becomes logistically cumbersome to organize, and communities often refuse to co-
operate.
Recent epidemiological studies in Ghana suggested that clinical filarial disease is
a good proxy measure of the levels of endemicity of filariasis. (Gyapong et al, 1996).
This findings has since been validated in a WHO coordinated multi-country study (WHO
1998a). On the basis of the results, the study participants recommended the use of clinical
examinations of a sample of adults as a rapid method to assess the community burden of
the disease.
Even with these new rapid assessment methods, it would be very time-
consuming and expensive to do filariasis surveys in all potentially endemic communities
in order to determine the geographical distribution of lymphatic filariasis. However,
given the clustered distribution of filariasis in most parts of the world, it may be possible
to develop methods which allow the estimation of the distribution of filariasis on the
basis of surveys in a limited spatial sample of communities. Such a method has already
proven very valuable for onchocerciasis control in Africa (Ngoumou et al 1994, WHO
1998b).
Filarial Cripples an estimated 130 million people in the developing countries.
There are according to a recent WHO estimated, 119.1 million cases of lymphatic
filariasis in the world, in 76 countries and 905 million people live in areas. Where they
are at risk of contacting the disease, from the biting Mosquito which transmit the filarial
worms that cause serve disability and disfigurement. This amounts to106.2 million of
bancroftian filariasis and 12.9 million brugian filariasis (Micheal and Bundy, 1995) the
numbers over physical disabilities from their infections is approximately 43 million, with
bancraftian filariasis accounting for almost 40 million of these cause in the affected, the
limbs well the skin hardness and stretches, producing ulcers in a mild version of the
chronic stage of elephantiasis. The swelling is caused by the blockage of vessels in the
lymphatic system.
The 1992 report of the WHO expert Committee on filariasis indicates that
Brugian Infection is endemic in 8 Countries in South East Asian region (Bangladesh,
India, Indonesia, Maldives, Myanmar, Nepal, Srilanka and Thailand) While W. Bancroft
occurs in 7 countries in the American region (Brazil, Dominican republic Coasta Rica,
Guyana Haiti, Suriname, Trinidadad and Tobago) 4 in the Eastern – Mediterranean
region and 17 in the western pacific region (American Samoa, Brunei, Darussalam,
China, Cook Islands, Fiji, French, Polynesia, Malaysia, Nive, Papua, New Guinea,
Philippines, Republic of Korea, Samoa, Tonga and Vietnam), an additional 38 Countries
lie within the W.bancrofti endemic areas of sub Saharan Africa (Angola, Benin,
Burkinafaso, Burundi, Cameroon Capeverde, Central Equatorial Guinea, Ethiopia,
Gabon, Gambia, Ghana, Guinea, Guinea Bissau, Kenya, Liberia, Madagascar, Malawi,
Mali, Mauritius, Mozambique, Niger, Ramiro, Saotome and Principe, Senegal,
Seychelles, Sierra Leone, Togo, Uganda, United Republic of Tanzania, Zaire, Zambia
and Zimbabwe). India with 45.5 million cases and sub – Saharan with 40 million cases
have very similar burdens of W. bancrofti infections. Individually, the two account for 38
percent and 34 percent, respectively of the world burden. By Comparison, hower, There
are slightly higher infection and disease rates observed for the sub-Saharan than for India.
1.8 Geographical variation in transmission
The epidemiology of W. bancrofti and B. malayi infections varies in different
geographical areas, especially with respect to the prevalence and intensity of infection,
the transmission pattern and the clinical manifestations. Differences in vectorial capacity
and density are important factors influencing these epidemiological parameters in
different endemic areas. Even within the endemic community there can be considerable
variation in vector abundance and transmission between different sections and from one
household to the next. There are also inherent differences in the parasite; for example,
three strains of W. bancrofti and two strains of B. malayi have been recognized on the
basis of differences in periodicity of the micro- filariae. In most areas the microfilariae of
W. bancrofti are nocturnally periodic, being adapted to transmission by night-biting
Culex and Anopheles mosquitoes. A diurnal sub periodic form is found in the South
Pacific and in the Andaman and Nicobar Islands (India), whereas a nocturnally
subperiodic form is found in Thailand. B. malayi occurs both in a nocturnal periodic and
a nocturnal sub periodic form, whereas B. timori is nocturnally periodic. The sub periodic
forms are transmitted by vectors that bite mainly during the daytime. It is possible that
variation in worm habitat preferences within the host’s lymphatic system may con-
tribute to differences in clinical manifestations.
For details of the vector species and their bionomics, see Appendix IV.
Different geographical vector zones have been recognized on the basis of the
predominant vector species responsible for transmission in the areas.72 Culex
quinquefasciatus is the principal vector of W. bancrofti in urban and semiurban areas of
southern and South-east Asia, East Africa and America. Increased pollution of freshwater
bodies and the introduction of pit latrines, which favour breeding of this mosquito, have
led to increased transmission in many areas. C. quinquefasciatus is an endophilic night-
biter. There is no evidence that it is transmitting filariasis in West Africa. In rural areas of
Asia and Africa, Anopheles spp. are the main vectors, with the A. gambiae complex and
A. funestus being the most important vectors in Africa. The main vectors of the
Anopheles spp. bite indoors at night and breed in open, rather clean, water.
In the South Pacific islands the predominant vectors of W. bancrofti belong to
day-biting Aedes spp., especially A. polynesiensis. The majority of these mosquitoes bite
outdoors and breed in small temporary water collections: tree holes, empty cans and
bottles, coconut shells, plant axils and crab holes. In Papua New Guinea night-biting
Anopheles spp. are the principal vectors.
The nocturnally subperiodic form of B. malayi is transmitted by Mansonia
mosquitoes in dense swamp forest areas. This form is commonly found also in wild
monkeys. Nocturnally periodic B. malayi has been reported only from humans. It is
transmitted in open plains and agricultural areas, mainly by Mansonia spp. mosquitoes,
although in some areas species of Anopheles and Aedes also play a role. The larvae and
pupae of Mansonia mosquitoes obtain their oxygen directly from the cells of certain
species of aquatic plants present in clean water-bodies. Survival of the Mansonia spp. is
dependent on the association with the plants. Increased pollution has in some places led
to a decrease in breeding of Mansonia, with a subsequent drop in transmission of
B. malayi. Mansonia spp. prefers to feed outside and biting usually commences shortly
after dusk. A. barbirostris is the only mosquito to date to have been identified as a vector
of B. timori.
1.9 Filariasis in Asia
Asia excluding India and China is the region of third highest number of cases with
14.5 million and prevalence of 1.83 percent of bancroftian filariasis. The regional
estimates for brugian filariasis suggest that India accounts for 20 percent and china about
32 percent, making up half the global burden. The largest number of cases in both the
genera, W. bancroftio an B.malayi , occurs, in the 15-44 age group but the prevalence’s
of microfilaraemia and disease are the highest in the age group of 45 – 60 . There is also
a male bias for microfilaraemia, 10 percent more in bancroftian and 25 percent more in
brugian filariasis chronic disease due to bancroftian also appears to be more prevalent
among males than females, largely because of the large number of hydrocoele cases put
at 26.79 million. Two third of the known victims of the disease are in India, Indonesia
and China, India alone, more than 300 million people are exposed to the threat of
filariasis. The efforts at controlling the disease are undermined by the increasing
resistance of the parasites to drugs and the mosquito vectors to pesticides. Poor sanitation
and urban squalor provide for an ideal ground for filarial mosquitoes.
1.10 Filariasis in India
To give an idea of the extent of burden of bancroftian filariasis in India, the
country has 17 million cases of microfilareamia in male (with a prevalence rate of 3.87
percent), 12.46 million in females (Prevalence rate 3.04 percent). Lymphoedema cases
are 2.6 million in males (0.6 percent) and 3.98 million in females (0.97 percent).
Hydrocoele on the other afflicts 12.88 males (2.93 percent). These Cases amount to a
total of 29.43 million males (6.7 percent) and 16.1 million females (3.92 percent). The
extent of burden of being brugian filariasis in India, in the form of microfilaraemia, is
1.105 million cases in males (0.25 percent), and 0.692 million in females (0.17 percent).
Lymphoedema cases number 0.582 million in males (0.13 percent) and 0.282 million in
females (0.07 percent). These amount to a total of 1.635 million cases in males (0.37
percent) and 0.949 million in females (0.23 percent).
In India, the National Filaria control Programme (NFCP) is a division of the
National malaria Eradication Programme (NMEP) in the ministry of Health. The Primary
Control Strategies of the NFCP include larviciding and environmental control measures
for mosquito reduction in Urban areas, as well as screening urban Population by night
blood Surveys and treating with DEC (6 mg/kg/day X 12 days ) Those found either to be
microfilaraemic or to have Lymphoedema. Nearly 75 percent of the population is at risk
in rural areas all filariasis control efforts are confined urban areas. In India, the following
states and union have been identified as endemic to filarial. They are: Andhra Pradesh,
Assam, Bihar, Goa, Gujarat, Karnataka, Kerala, Madhya Pradesh, Maharastra, Orissa,
Tamil Nadu, Uttar Pradesh, West Bengal, Andaman and Nicobar Islands, Daman and
Diu, Lakshadeep and Pondicherry.
1.11 Filariasis in Tamil Nadu
In the State of Tamil Nadu Sample Surveys were conducted in the mid 1970s in
11 out of 15 districts. It was found that a total of 27 million people were exposed to risk
out of a total population of 41 million. One million suffered from filariasis and 1.83
million had microfilaria infections (Rao, 1981). Filarias due to W.bancrofti occurred
along the coastal zones of Tamil Nadu and in some inland areas. Relatively high
microfilaria rates (8.3 to 11.1 percent) were also observed in the early 1955- 59 surveys
under the NFCP (Sasa, 1976). The estimated figures for 1985 and 1986 for infection with
filaria were 16, 425 and 18, 729 respectively. Data for rural areas were not available for
the years 1985 and 1986. In the state, 13 Districts have been identified as endemic to
filaria. They are Chennai(Metropolis), Kancheepuram, Thiruvallur, Vellore,
Thiruvannamalai, Thiruchirapalli, Villupuram, Cuddalore, Nagapatinam, Thiruvarur,
Thanjavur, Pudukottai and Kanyakumari.
The First 12 districts are under the control of the Directorate of the Public Health
and preventive medicine while Chennai (until recently, Madras) under the Corporation of
the metropolis. The National Filaria Control Programme (NFCP) has been, and is being
implemented in Tamil Nadu, since 1957. Due to Limited financial resources, however,
the fileria Disease control is at present confined to 43 urban areas only. One Survey unit
is in operation at Madurai for delimiting the endemic areas in the un-surveyed district and
the scheme is funded by the Central Government on 50:50 share of the cost of material
and equipment.
Besides these, the state as a unique scheme for encouraging the local bodies to
implement anti– filarial and anti – mosquito schemes with grant in aid from the state
Government. Of the 728 local Bodies in Tamil Nadu, 174 are implementing Government
approved grant in aid schemes. The public health Department has taken up some special
trails for control of rural filariasis; the DEC enriched salt has been distributed in Kiliyur
of Villupuram District since 1989, this trail has been very successfully, in reducing
filariasis transmission as seen in the micro filarial rate of 15.12 reducing to 0.16 in 1992
and to no rate was reported in 1994.
A follow up of the successful project has been implemented in Kanniyakumari
district from October 1995. The Health salt is being distributed through public
distribution system (PDS) in endemic villages of this district for the control of the rural
filariasis. Now, A DEC monitoring cell has been established in the year 1996. There are
other programmes of control as well. A‘ single Day Mass Therapy; for example, has been
conducted in august 1996 in Cuddalore district under the NFCP and DEC tablets have
been distributed to 2.1 million people to avoid further spread of the disease in the area.
Tamil Nadu is the first state of the Indian Union to implement the new strategy of single
day mass therapy. A mass therapy has been implemented in Tanjavur and
Thiruvannamalai Districts during September 1997. In Tanjavur and Nagapatinam
Districts of the Cauvery Delta region in Tamil Nadu, 25 filaria and Malaria clinics have
now been established (In 1997) for the diagnosis, treatment and Control of filariasis and
malaria, directly under the taluk of the district headquarters Hospitals. There are in facts
two district programmes in Operation in the state, namely, the NFCP and the anti –
filarial scheme (AFS). The NFCP is being run in a way it takes care of mosquito
collection, Dissection of mosquitoes, larvicidal activities, Night Blood Surveys, Blood
smear, Examinations, and Treatment with DEC; the AFS on the other hand, is carried out
by the municipalities but with night surveys conducted by the NFCP.
1.12 National Control Strategies in select countries
In China, the first National Programme began in 1965 and the results have been
remarkable. From a Prevalence of 31 million cases in 196, diligent use of DEC –Fortified
salt and mass treatment programme with standard 2 week courses, China has brought the
number of filarial cases to an estimated 1.58 million. In all the once – endemic provinces
of China today, the prevalence is now less than 1 percent (WHO, 1994). Egypt presents a
different picture. There was early success in the control of the bancroftian filariasis
through DEC delivery and mosquito/ Environmental Control efforts. But the control
programme was relaxed in 1965 and the problem of bancroftian filariasis began to return.
The Peri Cairo rural and semi – urban area of the Nile delta have foci where the
prevalence of bancroftian filariasis is greater than 20 percent. The division of the ministry
of Health, responsible for the filariasis control oversees control which is based primarily
on identifying microfilariaemic individuals in night blood surveys and treating them with
standard courses of DEC. There is additionally limited mosquito efforts relying on
insecticides and insecticide impregnated bed nets (Harb, Fairs, Gad, Hafez, Rawzy and
Buck, 1993)
In the 1950’s Lymphatic filariasis was a public health priority in French
Polynesia, as 30 Percent of the population was microfilariaemic and 10 percent suffered
from hypoedema. Mass chemotherapy with various regimens of DEC was initiated which
ultimately became 6mg/kg delivered in single doses twice yearly to the entire population
The mass chemotherapy was therefore reinitiated in1993 by the ministry of Health, with
DEC at 3mg/kg being given every 6 months (Perolat, Guidi, Riviere and Roux 1986).
Indonesia is the only country with all the three species of filarial parasites, and
with transmission by five different mosquito genera and a plethora of individual species.
A National Filariasis Control Programme was established in the early 1970,s. There was
emphasis on spaced, low –dose DEC with appreciable Community participation and
involvement of the primary health care system in the country. The current Strategy is
based on mass distribution of low- dose DEC, at 100mg for an adult, 50 mg for a child
less than 10 years old , given weekly for 40 weeks by primary health care workers in
endemic communities, where microfilaraemia prevalence is more than 1 percent.
It was in the early 1960,s that a formal and systematic filariasis control
Programme was started in Malaysia. The current control activities are however in
corporated under the vector borne Diseases Control Programme of the Ministry of
Health. With an annual incidence of 3-5 cases microfilariaemia per100,000 population,
17 control teams are dispersed throughout the endemic areas to carry out geographical
reconnaissance, night blood surveys treatment of cases with DEC for 6 days, follow – up
evaluation and health education (Annual Report of the vector - borne Disease Control
Programme, 1993). A survey in 1960’s put 42 out of 56 surveyed provinces of the
Philippines as endemic to lymphatic Filariasis at present, both bancroftian and brugian
filariasis is widespread. The filariasis Control Programme is currently part of the
communicable Disease Control Service. Currently, there are 7.5 million People at risk of
W.bancrofti infection along the coastal areas of Srilanka. No new cases of brugian
filariasis have been reported after 1968. Until 1987, a million blood films a year were
examined for microfilaria; but now only two – thirds of this number is being examined.
The Prevalence of Microfilareamic persons in these areas was 0.36 percent during 1993.
All microfilareamic persons are given DEC at 150 mg twice daily for two weeks, with an
additional courses of treatment of one month later.
A filariasis Control Programme was instituted in 1961 in Thailand and it has how
been integrated into the basic health services Programme but Supervised by a District
filariasis division. Use of Impregnated bed nets and repellents is encouraged. The overall
Objective of the Programme is to the reduced micro filarial carrier rates to at least 0.6
percent in all endemic areas and then to interrupt both transmission and occurrence of
Lymphoedema or elephantiasis (Suvanndabba, 1993).
1.13 Review of Literature
Panicker, Pani Sabesan and Krishnamurthy (1990) have studied the relative utility
or door to door surveys, school surveys, community health camps, filariasis clinics and
microfilaria detection camps, in the detection of the filariasis in the endemic area for
brugian malayi: shertallai taluk in Kerala state, south India. In this study, 67,071 have
been examined for microfilaraiamia and 26,929 persons have been examined for the
manifestations of filariasis: 1,335 microfilaria carriers and 4,074 clinical cases of
filariasis have been detected.
Case detection and treatment following door to door surveys is the mainstay of
filariasis control in china and many Southeast Asian countries including India,
anonymous, 1984. It is interesting to note that in china 339 million people have been
screened for microfilaria and 4 million have been treated with DEC in a ten years period
(jinjiang; 1986). This has not been possible in the India. It has been found that after 30
years of launching the national filariasis control programme (NFCP) in India, door – to –
door surveys were yet to be carried out in 78 or the 290 endemic districts (Sharma,
Biswas, Das and Dwivedi, 1983) and the present programme protected only 5 out of 252
million people in rural areas exposed to the risk of infection (RAO and Sharma, 1986).
The vector control research centre (VCRC) in Pondicherry carried out a five year
study (1980 – 1985) in the coastal villages of the region objective was to establish on
intersectorial action plan for health by co–ordinating the activities of various
Governmental agencies operating in the village and concerned with local administration ,
health social welfare education, rural development and fisheries. To encourage the local
community, a variety of schemes were introducing by the VCRC.
Another early step taken by the programme was to control the most obvious
breeding sites of mosquitoes. The local bodies of the Panchayat have paid little attention
to water supply and waste water disposal. This resulted in conditions, ripe for the
breeding or mosquitoes over waste areas, especially near public taps and wells. The
VCRC is involved in this matter and gained a good name from the community.
The VCRC, with the encouragement of the child development service, gave
special training in vector control to anganwadi workers and asked them to pass on this
knowledge to women, for whom literacy classes are also provided. With the co –
operation of the Department of Education, the Children were taught the public hygiene
and simple vector control methods and they reclaimed a mosquito Breeding swap and
turned it into play ground They also created a kitchen garden making use of the domestic
effluent which normally accumulated in pits that breed mosquitoes.
The VCRC formed a health committee in one village to carry out mosquito larval
control into ponds. The ponds were first de weeded, manually. Finger lings of common
carp (Cyprinus Carpio) were provided by the VCRC and the members were taught to
culture the fast growing, edible fishes. These fishes are used as larvicides for mosquitoes.
In the study by A.F Singh al (19990) Merthiolate was used as a preservative with
recommended concentration. This marthiolate saline as control did not cause any skin
reaction, whereas the antigen infected simultaneously, on the other arm, elicited positive
reaction ratio due to antigen (15 minutes after injection) ranged from 3.0 to 11.31
(median 4.8) which was highly significant (P<0.001), whereas the increase in the whole
area due to this mentholated saline ranged from 1.0 to 1.5 (medium 1.0) which was not
significant. Hence, merthiolated is a begin preservation and can safely be added to the
antigen in the recommended proportion.
Individuals of either sex, aged between 10 and 70 years, where include in the
study. These were drawn from filarial (w.bancroftio) endemic (chandraelal, 1973) and
filaria non-endemic areas having other helminthes injections. The Registration of micro
and a microfilareamic was done on the basis of night blood examination and the antigen
was assessed in different groups. The resurgence of lymphatic filariasis in the Nile Delta
(Harb et al, 1993), a study of 325,000 residents of 314 villages in six Governorates of the
Nile Delta area of Egypt, has revealed that the lymphatic filariasis increased from less
than 1 percent in 1965 to greater than 20 percent in 1991. In Egypt, surveys of filariasis
using combined measurements of the microfilaria rate and of the frequency of clinical
manifestations were concluded in many non – randomly selected communities. The
results provided a sketch panorama of the distribution of the disease.
Since 1974 a number of small spot surveys have been conducted in several parts
of the Nile Delta for filariasis studies. The prevalence and the intensity of microfilaria
have increased (Desowitz et al, 1993). The benchmark ecological and entomological
analysis (brengues, 1975) indicates bancroftian filariasis found through West Africa from
the mangrove swamps of the guinea to the sahelian Borden lands at 16 degrees latitude
north. It is the savannah areas that harbor the most filariasis (Hughes and hunter, 1970).
But the disease is not uniformly distributed it is found scattered.
A Typical geographic pattern of spotty occurrence of bancroftial diseases was
revealed in the study by lamontellerie (1972). In this survey about 147 villages in a
known filarial zone of southwest Burkina Faso. In 12 percent of the villages, there was no
filariasis, in another 33 percent, it was below 5 percent prevalence (hypoendemic); 26
percent, 5.0 to 19.9 percent prevalence (meso – endemic); and the remaining 29 percent
of the villages suffered more than 20 percent of prevalence (hyperendemicity). Two
villages were found with peak infection rates (42 percent and 43 percent), conditions
favoured for mosquitoes populations. More recently, coastal lagoons of the wory wast
near sassandra was reported hyperendemic buncroftian filariasis (Remy, 1988) and three
locations in Barkina Faso.
1.13.1 Socio cultural literature
Lymphatic filariasis (LF), the second most common vector-borne parasitic disease
after malaria, is found in over 80 tropical and subtropical countries. WHO estimates that
120 million people are infected with the parasite, with one billion at risk. These figures
are certain to be revised upwards because global prevalence mapping has not yet been
completed. According to WHO, LF is the second most common cause of long-term
disability after mental illness. One-third of people infected with LF live in India, a third
live in Africa and the remainder lives in the Americas, the Pacific Islands, Papua New
Guinea and South-East Asia. While not explicitly mentioned in the Millennium
Development Goals, LF and other neglected tropical diseases are recognized in the report
on the Commission for Africa as contributing significantly to the overall African disease
burden. LF and other helminthic diseases leave infected individuals, particularly women
and children, more vulnerable to HIV/AIDS, tuberculosis and malaria.
LF causes a wide spectrum of clinical and subclinical disease. Approximately
two-thirds of infected individuals show no overt evidence of disease, but when tested
demonstrate some degree of parasite-associated immunosuppression, and many show
evidence of renal dysfunction. The remaining third suffer from the chronic manifestations
of LF – chronic lymphoedema, elephantiasis and hydrocele. Further, those infected with
LF suffer the debilitating effect of acute filarial attacks that last from five to seven days
and may occur two to three times each year. Chronic filarial disease has serious social
and economic effects. Those afflicted with elephantiasis and hydrocele are often socially
marginalized and poor. Acute attacks and chronic disability cut economic output and
increase poverty.
In 1997, a World Health Assembly resolution called for the elimination of LF.
Public health interventions thus far have focused on interrupting the transmission of the
parasite through the use of mass drug administration campaigns (MDAs). The MDA
programmes deliver community-wide doses of diethylcarbamazine and albendazole, or
albendazole and ivermectin, once annually for a period of four to six years. Although
substantial progress has been recorded wherever the strategy has been implemented,
initial gains have been accompanied by the realization that an intervention that assumes
compliance will not alone ensure a permanent solution in many settings. Even in areas
where LF prevalence has been reduced to less than 1per cent of the population,
elimination remains elusive and in some situations the disease has resurged. We argue
that these “upstream” interventions could deliver more effectively “downstream” at
community level if the programmes were more firmly grounded in sociocultural
awareness during the planning stages.
This paper explores the disparity between the way the disease is defined at the
elimination programme planning stages and the way it is defined and perceived in the
diverse communities where it is implemented. We describe the impacts of undiagnosed
and untreated LF on the lives of potentially active and productive men and women and
explore the impact that awareness of local health and sociocultural norms and values can
have on improving primary and secondary LF control efforts.
1.14 Impact on infected individuals
Filariasis is caused by nematodes (roundworms) that inhabit the lymphatics and
subcutaneous tissues. Three filarial species cause lymphatic filariasis: Wuchereria
bancrofti, Brugia malayi, and Brugia timori. Infections are transmitted by mosquito
vectors; humans are definitive hosts. Lymphatic filariasis is a major cause of
disfigurement and disability in endemic areas, leading to significant economic and
psychosocial impact. The epidemiology, pathogenesis, and clinical features of lymphatic
filariasis will be reviewed here. The diagnosis, treatment, and prevention of lymphatic
filariasis and other filarial infections, including onchocerciasis, loiasis, and
mansonellosis, are discussed separately.
1.14.1 Current knowledge about LF’s sociocultural burden
The chronic manifestations of filariasis can have significant, and often very
negative, social impacts. The chronic disabling manifestations of this disease, including
lymphoedema of the limbs, breasts and external genitalia, have a profoundly detrimental
effect on the quality of life of affected individuals. The degree of social disability varies
between cultural settings, but the degree of stigmatization appears to be directly
correlated with the severity of visible disease. In conservative contexts, affected
individuals avoid seeking treatment for fear of drawing attention to their condition.
Failure to treat the disease results in recurrent acute febrile attacks and progressive
damage to the lymphatic system. Without access to simple hygiene advice, sufferers are
unable to prevent further progression of the outwardly visible complications of LF.
Women bear a double burden in societies where much of their role and identity is
dependent upon marriage and the ability to give birth to children. Young unmarried
women with LF may be forced to lead a reclusive existence in an attempt to hide their
illness or because their limited marriage prospects make them a burden to their families.
In Thailand and in west Africa there is a general perception that children born to a
woman affected by LF will be similarly affected. Shame and anxiety related to
difficulties in conceiving children are common for LF patients around the world. Young
females with LF are considered poor marriage prospects because the disease’s recurrent
debilitating acute episodes limit their ability to perform paid and unpaid work. The costs
associated with long-term health care as the disease progresses result in perceptions of
these women as financial burdens.
Although women may have concerns about marrying men with the physical
stigmata of LF, their gender roles and prevailing power structures often leave them in a
relatively powerless position. In Haiti, Coreil et al. found that the risk of dysfunction and
unhappiness was greater in marriages where the wife had physical manifestations of
filariasis. This is supported by data from coastal Ghana.
Gyapong et al. suggest that the physical and psychological burden borne by men
has a negative impact on their marriage and employment prospects. The extent of male
sexual disability as a result of LF has not been extensively studied, but investigators
believe that there is a significant “silent burden”. Gyapong et al. found that hydrocele had
a significant impact on young men, particularly at a time when they were struggling to
establish their sexual identity and their capacity to be reliable economic providers.
Unwillingness to admit to sexual dysfunction may shroud the real extent of this issue.
South American researchers found a wide range of disease-related problems, including
marriages without sexual activity, reports of painful intercourse in women whose partners
had penile lymphoedema and suicidal thoughts of both male and female partners being
attributed to the disease.
1.14.2 Impact upon lifestyle and economic opportunities
Gyapong et al. speculate that the current estimate of 850 000 disability-adjusted
life years (DALYs) lost as a result of LF was a gross underestimate. The estimates are
based on an assessment of gross clinical manifestations and do not take account of the
“incidence, duration and severity of acute adenolymphangitis”. In particular, the estimate
fails to capture the impact of disease on young people who, while not displaying clinical
manifestations or physical abnormalities, may be suffering the effects of acute fever
attacks. Acute episodes of adenolymphadenitis may result in school absenteeism and poor
educational attainment. Chronic disease can also present in childhood and affect
children’s quality of life.
As the disease progresses, the individual’s capacity to labour, both productively
and reproductively, are increasingly hampered. Coreil et al. note that in the Haitian
context, while impairment of mobility impacts upon the ability to garden or sell produce
in the market, acute attacks are equally detrimental to individuals’ ability to support
themselves and their family.
This finding is echoed by the work of Gyapong et al. and Suma et al. As the
disease progresses, the affected individual becomes too severely disabled to contribute to
household labour and further burdens the household economy.
1.15 Impacts on the LF elimination programme
The elimination programme is based on a simple two drug, once-yearly treatment
of at-risk individuals using safe and effective medicines (albendazole plus either
Mectizan® or diethylcarbamazine [DEC]). The World Health Organization (WHO)
recommends a minimum of five rounds to reduce the level of disease below the threshold
for sustaining transmission; then mass drug administration (MDA) can be stopped. MDA
programmes are already underway in 48 of the 83 LF-endemic countries and a number of
other countries are in the process of organising such programmes. Since the programme
began, 66 million babies have been born into risk free areas, a number that is expected to
increase sharply as even more countries begin LF elimination programmes.
1.15.1 Paucity of LF-related sociocultural research
A comprehensive literature search was undertaken to identify all published
sociocultural information available from LF-endemic countries. It was conducted using
PubMed, Ovid and their associated databases. Keywords included: lymphatic filariasis,
filariasis, Wuchereria bancrofti, Brugia malayi, Brugia timori, and elephantiasis,
hydrocele, sociocultural and socioeconomic.
Published LF literature is dominated by laboratory research and quantitative field
measurement of the impact of LF, with a wealth of local prevalence studies of parasite-
infected humans and vectors. Several researchers have highlighted the dearth of
sociocultural information on local beliefs, perceptions and behaviours towards the
disease. The paucity of sociocultural data is a common feature of other neglected tropical
diseases. Even with malaria, the neglected parasitic disease with the greatest tradition of
socio behavioral research, Williams and Jones observed that this research, while key to
successful outcomes, has yet to realize its full potential in contributing to control. Krishna
Kumari et al. and Gyapong et al. have argued that the lack of understanding and
documentation of LF’s socioeconomic consequences have led to a gross underestimation
of its impact. As the global elimination programme expands, the absence of sociocultural
insights and understanding appears to be impeding progress.
The multidisciplinary nature of the social science approach to researching
infectious diseases is often poorly understood by disease control programme planners.
Fundamental differences in research paradigms, research strategies and even language
make qualitative research approaches and findings difficult to communicate. Williams
and Jones observed that changing the status quo can be difficult in a context dominated
by research and funding structures that are not geared towards sociocultural approaches.
The United Kingdom-based Institute for Development Studies notes that “Health research
[in the developing context] is often funded by specialised agencies and priorities
identified by health sector managers who mostly have medical training.” The very tightly
focused health research agenda often overlooks or rejects the development of local
sociocultural understanding strategies against LF and other infectious diseases.
1.15.2 Beliefs about disease causality and transmission
Little information has been formally collected about how communities
incorporate LF, its origins and impact, into local knowledge systems. The role of
mosquitoes in transmitting the parasitic agents of filariasis is poorly appreciated in many
endemic communities, and thus it is not surprising that there is little awareness in these
areas of the importance of minimizing mosquito contact for preventing infection. In a
Malaysian study, only nine of 108 respondents associated filariasis with mosquitoes,
while walking barefoot on dirty ground or consuming contaminated food or drink was
commonly implicated as the source of infection. In rural Thailand, while schoolchildren
indicated correctly that mosquitoes transmit filariasis and that the disease could be
prevented by personal protection against mosquito bites, adults maintained that the
disease was inherited or resulted from poor blood circulation, carrying heavy loads,
prolonged standing, bathing in or drinking swamp water, personal contact with infected
individuals or sorcery. Suma et al. found that many participants in the Indian survey
believed that the disease was inherited. In Papua New Guinea and the United Republic of
Tanzania, although most people indicated that mosquitoes spread malaria, few
understood that mosquitoes could also spread filariasis (Wynd et al., unpublished
observation). Ahorlu et al. found that many villagers in a coastal Ghanian community
rejected the mosquito’s role in transmission. In French Polynesia, despite an intensive
community education campaign, most people discounted the idea that mosquitoes played
any part in disease transmission and attributed LF to the act of immersing an injured
ankle in the sea or consuming contaminated food and drink.
In the Philippines correct knowledge of disease transmission was associated with
the highest level of formal educational attainment. A study in rural south India found that
only 9 per cent of apparently uninfected people and 20 per cent of patients with chronic
filarial pathology knew that filariasis was contracted through mosquito bites. Other
causes commonly cited were occupation, polluted drinking water and poor nutrition.
1.15.3 Community ownership of treatment programmes
Gyapong et al. found that community-directed MDA programmes achieved much
higher levels of coverage than those delivered exclusively through the formal health
sector and were especially effective in areas where health facilities were limited.
Rifkinhas argued that community involvement is more effective when viewed as
an ongoing process. The explanation for improved coverage in the Ghanaian context
appeared to be twofold. First, the community was more likely to “own” the process
because it was involved in directing it and, as a result, was more likely to participate and
encourage participation by all community members. It is possible that this sense of
ownership may override or soften resistance to outside intervention. Secondly, the
iterative approach to seeking permission, returning to train local treatment coordinators
and ultimately delivering medication resulted in a higher overall level of understanding of
the programme’s purpose. Gyapong et al. highlight the need to allow this pilot
intervention time to expand into a larger geographical area and to broaden its focus to
include other health areas before claiming that the approach has long-term sustainability.
1.15.4 The value of increasing our sociocultural understanding
A quarter of a century ago, Dunn observed that the interactions between
sociocultural factors and LF control had largely been ignored, and that few attempts to
bridge the gap between biomedical knowledge and indigenous perceptions of disease had
been attempted. While there has been some growth of the literature in this area, insights
and understandings remain limited. Of the 80 countries known to be endemic for LF,
sociocultural information is available for only 11 (Brazil, French Polynesia, Ghana, India,
Kenya, Malaysia, Nigeria, Papua New Guinea, the Philippines, Thailand and the United
Republic of Tanzania).
Disease control programmes in developing countries often fail to fully meet their
objectives because the strategies pursued are inappropriate for the community or
challenge local perceptions of aetiology, prevention and control. Identification of
appropriate and sustainable filariasis treatment and prevention strategies requires a broad
understanding of local disease perceptions, including causes, consequences and means of
prevention. Since disease perceptions vary geographically, in-depth studies of the social,
cultural and economic aspects of disease will need to be context-specific. The
involvement of the community should be extended beyond a cursory consultation at the
beginning of the process. Community involvement and awareness must underpin and
direct the ongoing evolution of filariasis elimination programmes.
Sociocultural research methodologies have been employed by researchers in
Africa, the Caribbean and India. The use of focus groups, key informants and participant
appraisal techniques yield quantitative and qualitative data that improve the
understanding of local ways of accounting for, explaining and treating the disease.
Equally, they can help to identify those in the community at risk of failing to comply with
the treatment regimes, including migrant workers. Social science research illuminates
political power structures and stakeholder groups within communities, enabling
programmes to include all social groups. It also allows delineation of health service, drug
and community factors that influence compliance.
The collection of robust sociocultural data should inform the planning and
management of an LF elimination programme. First, an understanding of local
descriptions and interpretations of the disease is essential for informing and guiding the
development of programmes’ education and communication components. Equally,
without the support of local leaders and their participation as proponents and advocates,
the achievement of sufficiently high levels of coverage with drug combinations to
interrupt disease transmission will be elusive. Secondly, as the long-term morbidity
associated with pre-existing disease will continue to persist after transmission is
interrupted, sensitive approaches developed in partnership with the community are
required to generate the necessary impetus for effectively tackling the burden of chronic
disability post-elimination.
Efforts to interrupt transmission and eliminate LF as a public health problem will
certainly depend on effective mass chemotherapy campaigns and other public health
strategies, including vector control where appropriate. However, to increase the success
of elimination strategies, the sociocultural understandings of affected community groups
are pivotal in achieving sustainability, local participation and ownership. Early evidence
suggests that long-term efforts to eliminate the disease may fall short of elimination in
areas where community acquiescence has been replaced by distrust, engendered by
misguided communication and vertical programme delivery, or a shift in local power
structures. Strategies responsive to community sociocultural understandings will have
key roles in reversing this trend and in addressing the disability burden that is currently
only superficially understood in affected communities. If disability is detected early and
correctly managed, the negative economic and psychosocial consequences may be
averted.
To sustain interruption of the LF transmission cycle and prevent this disease’s
negative impacts on future generations, sociocultural analysis must be brought into the
mainstream of LF elimination efforts. By ensuring that sociocultural perceptions are
critical in developing programme strategies and policies, we stand a much greater chance
of eliminating LF.
1.16 Problem Statement
The Present problem is the prevalence of filariasis in Kumbakonam temple town
which has a long history of its presence. Kumbakonam has a conducive atmosphere and
its adverse environmental and ecological conditions favor the growth of filarial worm
inside the town as well as its peripheral wards. Kumbakonam is one of the oldest cultural
heritage town located in the central parts of Tami Nadu. The town is surrounded by
many religious temples with temple tanks. `Mahamaham’ is the major festival which is
being held once in twelve years and it is going to be held in 2004. The town does not
have proper under ground drainage system and the water is drained in open soak pit and
thus allowing mosquitoes to breed. Due to the non-availability of drainage system the
drain water is let on nearby vacant sites by which making these sites to soil pollution
zones and wet lands. The Temple tanks carry stagnant water pools which also caters the
feed for vectors in this region. Kumbakonam is well located in the deltaic regions and
the mosquito’s takes shelter in these regions. The presence to Filarial disease is high in
this zone when compared to the other 12 Filarial Control Units in Tamil Nadu and it is
because of the fact that they infect mainly the occupational character of the people mainly
those who are working in the paddy fields and the weaving industry. With this
background the present problem has mainly focused to study the Spatial and Behavioral
aspects of those who are affected due to the Filarial disease and keep them in the
Geographical Information System (GIS) for further analysis.
1.17 Objectives
It is clear from the above, that Kumbakonam is facing several environmental
problems particularly the stagnant water, waste water pollution zones, mosquito breeding
sites, marshy environment and so on which is necessary for the mosquitoes can grow
continuously and infect the people to the dreaded disease like Filariasis. To study the
spatial and behavioural aspects of the affected persons in this region the following
objectives are formulated:
a. To study the general environmental conditions that is conducive for the vector growth in this part of rice bowl of Tamil Nadu,
b. To study the spatial, environmental and behavioural attitudes about the affected persons in Kumbakonam filarial control unit,
c. To create a Geographical Information Base to maintain the data for GIS analysis and for further research,
d. To find the most dominating factors that are responsible for the high incidence of Filariasis in this region,
e. To suggest few eradication/ minimization methods of filariasis in this control unit, in the near future.
1.18 Methodology
To study the spatial and behavioural aspects of Filariasis affected persons in
Kumbakonam the reported disease cases were obtained from the Kumbakonam Filarial
Control Unit (KFCU) from 1998 to 2008. The details include, name of the affected
person, age of the person, their contact address, disease particulars, year of presence, date
of treatment and so on. Kumbakonam base map has been obtained from the
Kumbakonam Municipal Town Planning Department and the map was then digitized.
Based on the addresses of the affected persons obtained from the KFCU were plotted on
the maps for all the 272 reported cases for time period 1998-2008. Using the point
symbol in the MapInfo software the digitized map was used to plot the reported cases
with individual attached data bases. The details of each and every affected person can be
obtained by moving the mouse pointer around the points, in the map. This would
indicate the spatial distribution pattern of the Filarial disease from the time period 1998-
2008 (five GIS maps). Among the 272 affected cases 100 cases were selected for
Primary survey. The schedule consisting of 68 related questions about the various
attitudes of the affected cases towards the Filariasis. Despite the basic information about
the respondent the other relevant questions are: perception about the disease and various
environmental factors, environmental implications, presence of wet/ waste lands nearby
for the growth of vectors, marshy environment, details about the stagnant water and
public lavatories, protection from mosquitoes, health personal attention, collection of
blood smears, stages of the disease, treatment and psychological attitudes about presence
of the disease. Among the 68 questions 32 highly relevant variables from the data matrix
were selected for further analysis. Factor analysis is a dimension reduction method was
used to group the variables into number of factors for analytical interpretation.
2 Chapter
Profile of the Study Area
2.1 Introduction
Kumbakonam also spelt as Coombaconum in the records of British India, is a
town and a special grade municipality in the Thanjavur District in the southeast Indian
state of Tamil Nadu. It is located 40 kilometres from Thanjavur and 273 kilometres from
Chennai and is the headquarters of the Kumbakonam Taluk of Thanjavur District. The
town is bounded by two rivers, the Kaveri River to the north and Arasalar River to the
south. According to the 2001 census, Kumbakonam has a population of 140,021 and has
a strong Hindu majority; but it also has sizeable Muslim and Christian populations.
Kumbakonam dates back to the Sangam period and was ruled by the Early
Cholas, Pallavas, Medieval Cholas, Later Cholas, Pandyas, the Vijayanagar Empire,
Madurai Nayaks, Thanjavur Nayaks and the Thanjavur Marathas. It rose to be a
prominent city between the 7th and 9th centuries AD, when it served as a capital of the
Medieval Cholas. The town reached the zenith of its prosperity during the British Raj
when it was a prominent centre of European education and Hindu culture and it acquired
the cultural name, the "Cambridge of South India". In 1866, Kumbakonam was officially
constituted as a municipality, which today comprises 45 wards, making it the second
largest municipality in Thanjavur District, koodathin konam (i.e,angle of the (POT)
origin city) Kumbakonam, Kodathin Vasal Kodavasal(I.E., Entrance Of The Pot),
between Kumbakonam and Kodavasal Center of the Pot (Madyaman) is "Thirucherai".
Kumbakonam is known as the "temple town" due to the prevalence of a number
of temples here and is noted for its Mahamaham festival which attracts people from all
over the globe. The main products produced are brass, bronze, copper and lead vessels,
silk and cotton cloths, pottery, sugar, indigo and rice.
2.2 Etymology
The name "Kumbakonam", roughly translated in English as the "POT"s angle", is
believed to be an allusion to the mythical pot, the Sanskrit kumbha of the Hindu god
Brahma, which according to Hindu legend, contained the seed of all living beings on
earth. The kumbha is believed to have been displaced by a pralaya or deluge and
ultimately came to rest at the spot where the town of Kumbakonam now stands. This
event is now commemorated in the Mahamaham festival held every 12 years.
Kumbakonam is also known as Baskarashetramand Kumbamfrom time immemorial and
as Kudanthai in ancient times. Kumbakonam is also spelt as Coombaconum in the
records of British India. Kumbakonam was also formerly known by the Tamil name of
Kudamukku. Kumbakonam is also identified with the Sangam age settlement of
Kudavayil. Winslow, in his 1862 Tamil-English dictionary, associates negative
connotations with Kumbakonam. However, Winslow later apologized for his erroneous
claim.
2.3 History
The region around Kumbakonam was inhabited as early as the Sangam Age (3rd
century BC to 3rd century AD). The present-day Kumbakonam is believed to be the site
of the ancient town of Kudavayil where the Early Chola king Karikala held his court.
Some scholars identify Kumbakonam as the site of the fabled prison of Kudavayir-kottam
where the Chera king Kanaikkal Irumporai was imprisoned by the Early Chola king
Kocengannan. Kumbakonam is identified with the town of Malaikūrram which had
served as the Chola capital as early as the 7th century and with the town of Solamaligai
which had also served as a Chola capital. According to the Sinnamanur plates,
Kumbakonam was the site of a battle between the Pallava king Sri Vallabha and the then
Pandya king in 859 and between the Pandya king Srimara Pandya and a confederacy of
the Cholas and Gangas.
Kumbakonam came into limelight during the rule of the Medieval Cholas who
ruled from the 9th century AD to the 12th century AD. The town of Pazhaiyaarai, 8
kilometres from Kumbakonam was the capital of the Chola Empire in the 9th century.
Following the decline of the Chola kingdom, Kumbakonam was conquered by the
Pandyas in 1290. Following the demise of the Pandya kingdom in the 14th century,
Kumbakonam was conquered by the Vijayanagar Empire. Krishnadevaraya, the emperor
of Vijayanagara visited the town in 1524 and is believed to have bathed in the famous
Mahamaham tank during the Mahamaham festival. Kumbakonam was ruled by the
Madurai Nayaks and the Thanjavur Nayaks from 1535 to 1673 when it fell to the
Marathas. Each of these foreign dynasties had a considerable impact on the demographics
and culture of the region. When the Vijayanagar Empire fell in 1565, there was a mass
influx of poets, musicians and cultural artists from the kingdom.
According to the chronicles of the Hindu monastic institution, the Kanchi matha,
the matha was temporarily transferred to Kumbakonam in the 1780s following an
invasion of Kanchipuram by Hyder Ali of Mysore. When Tipu Sultan invaded the east
coast of South India in 1784, Kumbakonam bore the brunt of his invasion. The produce
fell sharply and the economy collapsed. Kumbakonam did not recover from the calamity
till the beginning of the 19th century.
Kumbakonam was eventually ceded to the British East India Company in 1799 by
the Thanjavur Maratha ruler Serfoji II and reached the zenith of its prosperity in the late
19th and early 20th century when it emerged as an important center of Brahminism,
Hindu religion and European education in the Madras Presidency. The opening of the
Suez Canal in 1869 fostered trade contacts with the United Kingdom. In 1877, railway
lines were completed linking Kumbakonam with the ports of Madras, Tuticorin and
Nagapattinam. The Tanjore district court was established in Kumbakonam in 1806 and
functioned from 1806 to 1863.
Kumbakonam continued to grow even after India's independence though it fell
behind the nearby town of Thanjavur in terms of population and administrative
importance. The population growth rate began to fall sharply after 1981. This decline has
been attributed to limited land area and lack of industrial potential. On July 16, 2004, a
devastating fire in the Sri Krishna school killed more than 80 children.
2.4 Geography
Kumbakonam is located at 10.97°N 79.42°E. It is situated 273 km south of
Chennai, 96 km east of Tiruchirappalli, and about 40 km north-east of Thanjavur. It lies
in the region called the "Old delta" which comprises the north-western taluks of
Thanjavur District that have been naturally irrigated by the waters of the Cauvery and its
tributaries for centuries in contrast to the "New Delta" comprising the southern taluks that
were brought under irrigation by the construction of the Grand Anicut canal and the
Vadavar canal in 1934. It has an average elevation of 26 metres (85 ft). The town is
bounded by two rivers, the Kaveri River on the north and Arasalar River on the south.
Although the Cauvery delta is usually hot, the climate of Kumbakonam and other
surrounding towns is generally healthy and moderate. Kumbakonam is cooler than
Chennai, the capital of Tamil Nadu. The maximum temperature in summer is about 40
degrees Celsius while the minimum temperature is about 20 degrees Celsius.
Kumbakonam receives an annual rainfall of 114.78 centimetres every year. The region is
covered with mainly alluvial or black soil which is conducive for rice cultivation. Other
crops grown in Kumbakonam include mulberry, cereals and sugarcane.
The flora of the Cauvery Delta mostly comprises palm trees. The town of
Kumbakonam is surrounded by extensive paddy fields. Methods of irrigation were
considerably improved following the opening of the Mettur Dam in 1934. The fauna of
the Cauvery Delta is limited to cattle and goats. The town is situated at the western flank
of the Kumbakonam-Shiyali ridge which runs along the Kollidam riverbasin separating
the Ariyalur-Pondicherry depression from the Nagapattinam depression. This granular
ridge projects further eastwards penetrating the Pondicherry depression and forms a hard
layer of cretaceous rock underneath the sedimentary top soil.
Residential areas make up 32.09 percent of the town's total area while commercial
enterprises and industrial units make up 2.75 and 1.21 percent respectively. The non-
urban portion of the town constitutes about 44.72 percent of the total area. Kumbakonam
has a total of 45 slums with a population of 49,117. The town has around 141 kilometres
of roads, 544 municipal roads making up 122.29 kilometres. There are also around 18.71
kilometres of state highways running through Kumbakonam. Over 87 per cent of the
municipal roads are paved. The town gets its water supply mainly through the
Valayapettai headworks across the river Cauvery and the Kudithangi headworks across
the river Kollidam.
2.4.1 Topography
The Town from a continuous stretch of level land with a few ups and downs made
by the deposition of the rivers. The town is located at about 27 metres above mean sea
level. The flow of water in the rivers of cavery and its distributory Arassalar has been
highly Seasonal.
2.4.2 Drainage
In Kumbakonam town the drainage system is ‘open drainage system’ and hence
drainage water is drained into Cauvery River and Arasalar River with in the city. The
drainage cannals are illmaintained and out modded and this leads to the city
environmental pollution. The river cauvery passes through the northern town and is
flowing east and west. On the south the river Arasalar passes at the east to west Direction
of the town.
2.4.3 Soils
The soils of the Kumbakonam are mostly alluvial deposits. The soils are classified
into major soil groups according to the soil survey techniques namely entisiols (alluvial
soil). The Entisiols (alluvial soil) are recent deposit of Alliuval soil with moderate to
rapid permeability. The soils are suitable for rice and other irrigated dry crops.
2.4.4 Climate
The Kumbakonam town experiences a moderate climate throughout the year. The
mean annual temperature is 32.2o C. There is a steady rise in Temperature from January
to May. The highest temperature is 38.1o C observed in May and April. April, May and
June are the hottest months of the year. Although summer is hot. Occasional rainfall
results in water stagnation in the wet field from august the temperature gradually lower to
minimum of 28.20o C in January. Climate association with topography played on
important factor in the dust Pollution. The town receives most its rainfall during
northeast monsoon, the annual average of rainfall is 12,600 mm. The maximum rainfall
received by the town is from October to December.
2.4.5 Temples
Kumbakonam is known for its temples and mathas. There are around 188 Hindu
temples within the municipal limits of Kumbakonam. Apart from these, there are several
temples around the town thereby giving the town the sobriquets temple town and City of
temples. The most important temples present in Kumbakonam are the Sarangapani
temple, the Kumbeswara temple and the Ramaswamy temple.
The Sarangapani temple was constructed by Nayak Kings in the 15th century and
has twelve storeys high. The Ramaswamy temple, which has scenes from the Hindu epic
Ramayana depicted on its walls, was constructed by the Nayak ruler Raghunatha Nayak
in the 16th century. Its principal idol of Lord Rama is made from a single piece of
saligrama. The Kumbeswara temple is considered to be the oldest Saivite shrine in the
town. It was constructed by the Medieval Cholas in the 7th century AD.[citation needed]
This is the main temple of the town and as per the local mythology, is closely connected
with the Mahamaham tank where pilgrims from all parts of India bathe once every 12
years during the Mahamaham festival. The temple of Nagesvara has a separate shrine for
the Sun god Surya who is believed to have worshipped the Hindu God Shiva at this place.
Kumbakonam has one of the few temples dedicated to the Hindu god Brahma.
Kumbakonam also has a number of Hindu monastic institutions or mathas. The
Sri Sankara matha of Kanchipuram was moved to Kumbakonam during the reign of
Pratap Singh and remained in Kumbakonam until the 1960s. There are also two Vellalar
mathas in the nearby towns of Dharmapuram and Thiruppanandal and a Raghavendra
matha in Kumbakonam. There is also a branch of the Vaishnavite Ahobila mutt in
Kumbakonam.
The Thirupureswarar temple of Patteeswaram, the Oppliyappan Sannadhi, the
Swamimalai Murugan temple and the Airavateswarar temple at Darasuram are located in
the vicinity of Kumbakonam.
Kumbakonam has a strong Hindu majority; but it also has sizeable Muslim and
Christian populations. Among Hindus, Kallars, Thondaimandala Mudaliars, Brahminsand
Dalitsare the numerically dominant Tamil-speaking groups. Brahmins are more numerous
and affluent in Kumbakonam than in other parts of Tamil Nadu. There are also large
populations of Moopanars, Vanniyars, Konars and Nadars. Amongst Muslims, the Sunnis
are dominant. However, there is also a significant Shia minority. Most of the Muslims are
Marakkayars or Labbays. The majority of Muslims in Kumbakonam are involved in
commerce or maritime trade. Kumbakonam also has a large population of Protestant
Christians largely due to the efforts of the German missionary Christian Friedrich
Schwarz. The Catholics in Kumbakonam are mainly affiliated to the Roman Catholic
Diocese of Kumbakonam which was separated from the Archdiocese of Pondicherry in
1899. The population of Kumbakonam is predominantly Tamil-speaking. The commonly
used dialects is the Central Tamil dialect. There are significant minorities speaking
Thanjavur Marathi, Telugu, Kannada and Saurashtrian as their mother tongue.
2.5 Municipal administration and politics
The functions of the municipality are devolved into six departments: General,
Engineering, Revenue, Public Health, Town planning and the Computer Wing. All these
departments are under the control of a Municipal Commissioner who is the supreme
executive head. The legislative powers are vested in a body of 45 members, one each
from each of the 45 wards. The legislative body is headed by an elected Chairperson and
is assisted by a Deputy Chairperson.
2.6 Economy
The important products of Kumbakonam include brass, bronze, copper and lead
vessels, silk and cotton cloths, sugar, indigo and pottery. Kumbakonam is considered to
be the chief commercial centre for the Thanjavur region. As of 1991, around 30per cent
of the population was engaged in economic activity. Rice production is an important
activity in Kumbakonam. Of 194 industrial units in Kumbakonam, 57 are rice and flour
mills. Kumbakonam is also a leading producer of betel leaves and nuts; the betel leaves
produced in Kumbakonam are ranked amongst the best in the world in terms of quality.
The A. R. R. Agencies, a leading manufacturer has its factory in Kumbakonam. The main
administrative offices of T. S. R. & Co., a cosmetic company, are also based in
Kumbakonam. Kumbakonam is also famous for its metal works. The Tamil Nadu
Handicraft Development Corporation had been established in the nearby town of
Swamimalai in order to train bronze artisans. Kumbakonam is an important silk-weaving
centre and more than 5,000 families were employed either directly or indirectly in silk
weaving. Silk weaved in Kumbakonam is regarded as one of the finest in the
subcontinent. They are largely used in the manufacture of Thirubuvanam silk sarees.
Kumbakonam was also an important salt-manufacturing area during British rule. In
recent times, Kumbakonam has emerged as an important manufacturer of fertilizers.
Apart from its manufactures, tourism is also a major source of income for the
town. The Hindu temples and colonial-era buildings have been recognised for their
tourism potential. The 12th-century Airaveswarar temple in the town of Darasuram near
Kumbakonam is an UNESCO World Heritage Site. Kumbakonam is also frequented
visited by art collectors interested in handloom cloth and other curios.
2.7 Transport and communication
Kumbakonam is well-connected by road and rail with the rest of India. The
nearest international airport is at Tiruchirapalli, which is 94 km from Kumbakonam. The
nearest seaport is located at Nagapattinam whch is about 50 km away. There are regular
government and private bus services to Chennai, Thanjavur, Tiruchirapalli,
Chidambaram, Nagapattinam, Coimbatore, Madurai, Pondicherry, and Tirunelveli. The
Karnataka State Road Transport Corporation (KSRTC) operates daily services from
Bangalore to Kumbakonam. On March 1, 1972, the Cholan Roadways Corporation was
established by the Government of Tamil Nadu with its headquarters in Kumbakonam in
order to improve transportation facilities in the districts of central Tamil Nadu. The
organisation acquired the fleets of buses earlier owned by private operators - Sri
Ramavilas Service, Raman and Raman Limited and Sathi Vilas. On July 1, 1997, the
organization was renamed Tamil Nadu State Transport Corporation, Kumbakonam and
presently forms first division of the Tamil Nadu State Transport Corporation. The
corporation runs a reconditioning unit and a tyre re-threading unit in Kumbakonam.
Kumbakonam is connected by rail with most important towns and cities in South India.
The Mysore-Kumbakonam Express which was extended upto Mayiladuthurai connects
Kumbakonam with Mysore. The train also halts at Bangalore on its way to Mysore and
back. The Tiruchirapalli-Kumbakonam passenger train connects Kumbakonam with
Tiruchirapalli while the Chidambaram passenger train runs regular services between
Kumbakonam and Chidambaram.
The traditional modes of transportation are bullock carts. It is recorded that as late
as the 1950s, landlords and rich farmers travelled mostly by bullock carts with the
exception of rare long journeys, which they undertook by buses or motor vehicles.
Kumbakonam has an efficient local bus transportation system. The mofussil bus stand is
located in the south-east of Kumbakonam and is situated just opposite to the Arignar
Anna Bus Stand where the long-distance buses are stationed. There are occasional ferries
that transport people and goods across the Cauvery. Till the beginning of the 20th
century, students of the Government Arts College used to cross the Cauvery on coracle
ferries in order to attend college. Since the construction of a bridge in 1944, the practice
of transporting men and goods by coracles has greatly diminished.
2.8 Education
Kumbakonam emerged as an important centre of education in the late 19th
century and was known as the "Cambridge of South India". The Government Arts
College, established in Kumbakonam in 1854, is one of the oldest educational institutions
in the Madras Presidency. It began as a provincial school on October 19, 1854, before
being upgraded to a government college in 1867. It was affiliated to the Madras
University in 1877. One of the early principals of the college was William Archer Porter,
a Cambridge Wrangler, who, along with T. Gopala Rao, was instrumental in its elevation
to a government college. He is also credited with framing the college's acclaimed
educational policy. In 1881, it became a full-fledged college and high school courses.
Notable faculty members included U. V. Swaminatha Iyer while the Indian
mathematician Srinivasa Ramanujan who studied from 1904 until 1906 when he dropped
out, was one of its noted pupils. The Government Arts College for Women was started in
1963 and had a total strength of 2,597 pupils in February 2006. The college offers various
undergraduate courses and one post-graduate course and is affiliated to the Bharathidasan
University. Other colleges in Kumbakonam include Idhya Colleges of Arts and Sciences,
Annai College of Arts and Sciences,Government College Of Fine Arts and Arasu
Engineering College. The Shanmugha Arts, Science, Technology & Research Academy
has a satellite campus based in Kumbakonam where arts and sciences are taught.
The Native High School, founded in 1876, and the Town Higher Secondary
School, one of whose students was Srinivasa Ramanujan, were some of the oldest schools
in the Madras Presidency. At present, there are of 36 government and private schools in
Kumbakonam.
2.9 Filariasis: Night Clinic and Administrative Functions
There are two subunits and two night clinics in operation in the study area of
Kumbakonam Town, under the control unit are Kumbakonam which is in Thanjavur
District. In Kumbakonam control unit, there is 13 administrative staff (1 superindent, 2
Assistant, 1 Junior Assistant, 1 Typist, 2 Drivers, 5 Office Assistant, 1 Night Watchman).
In the technical using of the control unit, there is one endomoligical Assistant and for
Laboratory Assistant. The Laboratory Assistant is engaged in Blood semear
Examinations. Under the Control of the Filaria Officer at Kumbakonam Control Unit,
there are 10 sub units and 9 night clinic. The breading places in the study area are
category as follows: pucca drainage, katche drainage, pacca chspit, katche chspit, septic
tank, disused well, used well, overhead tank, cesspool and other water containers. These
breading centers are monitored by the NFCP personnel. The NFCP personnel spray
larvicides like M.L.OILS, Baytex, Temiphos and Pyroxene, whichever is available in the
market for the eradication of mosquitoes.
The night clinics that operate in the delta region of Kumbakonam (two codes; O
and P) have main functions are Blood Smear Collection (for lab Test) and Slides
Examination (positive microfilaria detection). Each night clinic carries out 1,500 blood
smear tests a months and treatment with statement with standard DEC. The Fileria and
Malaria clinics, attached to the Kumbakonam Government Hospitals provide
lymphoedema treatment. They are also implementing the programs of control units and
night clinics, their main functions are
a. Interferential therapy;
b. Heat Therapy;
c. Penumatic compression Therapy and
d. Supply of Lymphoedem tablets to avoid swelling;
The sub units operate between 6 to 11 am (collection of Mosquitoes, and
Ministrative works) and 2.30 pm to 5.30 pm (antilarvae spray). The night Clinics operate
in the day between 2 to 5pm (Blood smear Tests) and 9 to 1 pm (Blood smear
Collection).
2.10 Major Industries
Kumbakonam is also one of the leading market centers in Thanjavur district. It is
a prosperous center for metallurgic works. The town is noted for weaving, brass utensils
and handicrafts.
2.11 Population Characteristics
In 1901, the details of population of Kumbakonam are known authentically there
were only 59,673 persons in 1901. It had increased gradually to more then 100,000 in
sixty years. The population decreased from 64,647 in 1911 to 60,700 in 1921. This may
be due to extensive famine and war conditions that prevailed. In all other decades there
was an increasing trend in population growth. According to 2000 census, the total
population of Kumbakonam was 141,814 of which 70,544 are females and 71,270 are
males. The population distribution in ward wise is mostly even except some central parts
of the town.
Table: 2.1 Growth of Population in Kumbakonam: 1871 - 2011
Year Population ±per cent 1871 44,444 --- 1881 50,098 +12.7 1891 54,307 + 8.4 1901 59,673 + 9.9 1911 64,697 +8.3 1921 60,700 -6.1 1931 62,317 +2.7 1941 67,008 +7.5 1951 91,643 +36.8 1961 92,581 +1.0 1971 113,130 +22.2 1981 132,832 +17.4 1991 139,483 +5.0 2001 141,812 +0.4 2011 167,098 +58.2
Source: Municipal office records
The growth of population during various decennial periods, Population of the
town during 1961 was 92,581 among them 46,029 were male and 46,552 were females.
In 1961 to 1971 the growth is very high compared to the proceeding years and in 1961
the population was 92,581 and it had increased to 1, 13,130 in 1971 and also in 1981
which is nearly 20,000 for the two consecutive decades. But in the case from 1981 to
1991 the increase was only about 7,000 and during the period from 1991 to 2001 it was
very less. It is evident that during the earlier periods the growth was abnormal and it has
gradually decreased over the present decade. It may be due to the awareness among the
people about the population control measures and also due to the out migration.
2.12 Landuse
Land use refers to utilization of land under different categories. The land use of
Kumbakonam town can be divided into major groups and they are residential,
commercial, industrial, transportation, public and semi-public, education, recreational,
open spaces and cultural lands, among the different land use
Table: 2.2 Different Types of Land use in Kumbakonam
Area in Sq Km
Percentage to Total
Residential 7.98 63.5 Commercial 0.82 6.6 Industrial 0.37 2.9 Public and semi-public 0.57 4.5 Transportation 2.04 16.2 Education 0.55 4.4 Recreation 0.07 0.5 Agricultural 0.18 1.4 Total 12.58 100.0
Source: Municipal office records
3 Chapter
Creation of GIS Information Base
for Filariasis Patients
3.1 Introduction
Lymphatic filariasis (LF), the second most common vector-borne parasitic disease
after malaria, is found in 81 tropical and subtropical countries. World Health
Organisation (WHO) estimates that 120 million people are infected with this parasite and
1.3 billion (i.e. >20per cent of the global population) are living at risk of infection. It is
estimated that 40 million people are suffering from the long term complications of the
disease. One-third of people infected with LF live in India, one third live in Africa and
the remainder lives in the Americas, the Pacific Islands, Papua New Guinea and South-
East Asia. The Global Programme for Elimination of Lymphatic Filariasis (GPELF)
began its campaign to interrupt transmission of the parasite using a strategy of annual
mass drug administration (MDA) to those at risk and to control or prevent LF-related
disability through morbidity management programs in which 12 million people have been
treated since 2000. The latest WHO figures shows that around 381 million people
received filariasis treatment in 2005 alone in 42 countries. In India LF is endemic in 18
states and the Union Territories. Approximately 420 million people reside in endemic
areas and 48.11 million are infected. Mortality is uncommon, whereas morbidity
associated with this infection can be considerable and lifelong. Because of these factors,
LF escapes the attention of planners and governments. Rural and urban areas in India
suffer with lack of adequate antifilarial measures and it is estimated only 11per cent of
the endemic population is protected by the National Filaria Control Programme (NFCP),
Government of India.
LF causes a wide spectrum of clinical manifestations in the infected populace.
Most of the population suffers with symptoms of LF such as chronic lymphoedema,
elephantiasis and hydrocele. Those infected with LF further bear the debilitating effect of
acute filarial attacks that last from five to seven days and may occur two to three times
each year. Chronic filarial disease has serious social and economic effects. Those
afflicted with elephantiasis and hydrocele are often socially marginalized and poor. Acute
attacks and chronic disability cut economic output and increase poverty. This is evident
from the observation that 94per cent of the countries with the lowest human development
index (HDI) are endemic for LF. The chronic manifestations of filariasis can have
significant, and often very negative, social impact. LF has traditionally been considered
to be a disease associated with poverty, inadequate sanitation and underdevelopment.
Sociodemographic factors such as ethnic group, parent's education and occupation, use of
protective measures, and living standard of the family are suggested to be important risk
factors for epidemics of vector borne disease. From filarial endemic countries there is
little published evidence of an association between LF and country-level poverty. In
Philippines, there is an apparent association between LF endemicity and poverty at
provincial level. In the majority of control strategies, the target population of disease
transmission and control are overlooked. In filariasis, poor knowledge and indigenous,
traditional belief systems contribute to high-risk and inappropriate illness prevention and
treatment.
Lymphatic filariasis (LF), caused by Wuchereria bancrofti and transmitted by the
Southern house mosquito Culex quinquefasciatus, accounts for 95per cent of the total LF
cases in India. To asses the LF disease and its biased factors, a pilot scale study was
carried out in Karimnagar district of Andhra Pradesh. The villages of this district have
been recognised as endemic for filariasis and MDA programs are still going on. There are
no such reports available on impact of socio-economic factors on LF in Andhra Pradesh.
Hence, the aim of this study is to assess the relationship between socioeconomic status
and occurrence of LF in these villages of Karimnagar district of Andhra Pradesh.
The tremendous potential of GIS to benefit the health care industry is just now
beginning to be realized. Both public and private sectors are developing innovative ways
to harness the data integration and spatial visualization power of GIS. The types of
companies and organizations adopting GIS span the health care spectrum--from public
health departments and public health policy and research organizations to hospitals,
medical centers, and health insurance organizations.
Esri has over 5,000 health care clients worldwide who are using the resource
integration capabilities of GIS to create analytical and descriptive solutions. GIS plays a
critical role in determining where and when to intervene, improving the quality of care,
increasing accessibility of service, finding more cost-effective delivery modes, and
preserving patient confidentiality while satisfying the needs of the research community
for data accessibility.
3.2 Using GIS for Public Health
In 1854, an English physician, John Snow, provided the classic example of how
mapping can be used in epidemiological research. He identified the water source
responsible for an outbreak of cholera in London by mapping the locations of those
afflicted. GIS has continued to be used in public health for epidemiological studies. By
tracking the sources of diseases and the movements of contagions, agencies can respond
more effectively to outbreaks of disease by identifying at-risk populations and targeting
intervention.
Public health uses of GIS include tracking child immunizations, conducting health
policy research, and establishing service areas and districts. GIS provides a way to move
data from the project level so that it can be used by the entire organization. Clinical and
administrative information can be disseminated in a visual and geographic manner that is
readily understood using Esri Internet Map Server (IMS) technology. This health data can
be easily accessed using an Intranet or the Internet
Balancing individual privacy with data accessibility has become more challenging
for public health agencies. "Spatially Enabling Vital Health Care Data" features an article
that describes the South Carolina Department of Health and Environmental Control's
program for managing georeferenced health records. The department aggregated health
record data at the census tract level so that the privacy of individual patients was
preserved while allowing easy access to data through the use of an ArcView GIS query
tool.
Quick access to medical records is crucial to effective treatment. A new program
that will make electronic medical records available for all armed services members, their
dependents, and retirees has placed the Department of Defense at the forefront of GIS
application development for health care. The department will pursue a patient-centric GIS
approach that focuses on the development of information around the patient, in contrast
to the approach used by the computerized medical record industry that builds information
around each episode or encounter a patient has with the health care system.
3.3 The Business of Health Care Geographic
While health care professionals in the public health sector were early adopters of
GIS and continue to find new and innovative uses for this technology, the use of GIS in
the private health sector has grown substantially in the last decade. Private sector use now
encompasses applications in marketing and business management as well as those
concerned with patient care. These applications take into consideration the unique
constraints under which the health care industry must operate.
Health care providers can no longer afford to indulge in the "build it and they will
come" fallacy. Health care is a repeat business. Though many hospitals and medical
centers have operated under Reilly's law of retail gravity more square footage equals a
larger trade area to draw from they have begun to realize that to be competitive they need
to be located conveniently to their customer base.
Site analysis operates a little differently for hospitals and medical centers. Unlike
other types of businesses, hospital locations continue to be dictated by Certificate of Need
(CON) programs in many states. This eliminates relocation as a method for improving the
market from which hospitals draw patients and leaves health care providers with two
methods of encouraging growth. Both require effective site analysis.
Providers can find new markets by increasing the range of services they offer
based on an analysis of patient needs, both present and future, in their market area. This
allows growth without requiring relocation.
Another stationary strategy involves identifying and cultivating a hospital's most
profitable services. This strategy includes studying competitors to learn about the services
they offer and populations they serve and to gauge how profitable they are.
Using GIS for demographic analysis to estimate the demand for various types of
services can benefit individual physicians. Physician specialties are more effectively
marketed by locating offices near pools of potential patients. This type of analysis can be
extended for application by health care providers.
How consumers access the services of managed health care providers is
controlled by geographic location. Matching physician locations to where employees live
or work assures that primary care physicians are available throughout the network and
that the types of specialties required by specific populations are located reasonably close
to these populations. Employers favor providers with networks that minimize the distance
employees must travel to obtain care.
"Mapping Health Care Networks" tells how Esri business partner GeoHealth
Incorporated of Redlands, California, has developed an ArcView GIS application that
helps managed care providers balance the location, type, and patient workload of
physicians in their network.
3.4 A Wealth of Tools
Managing patient care environments within hospitals and medical centers has
become an increasingly complex task. Caregivers require critical information that is
readily available in a visually streamlined format. Loma Linda University Medical
Center, one of the world's premier medical research centers, uses a GIS-based system
called the Patient Location and Care Environment System (PLACES) to let caregivers see
the physical bed location of each patient and to retrieve demographic and clinical
information.
PLACE uses an ArcView GIS application to view computer-aided
design/computer-aided manufacturing (CAD/CAM) floor drawings that show room and
bed locations for each floor and are tied to daily census information. When the system is
complete, physicians will be able to log on to an Intranet to retrieve the location and other
relevant information on their patients. Patient admission will also be improved because
admitting personnel will be able to quickly identify available beds. The use of mapping
to improve health care services doesn't stop at the building level.
BodyViewer, an ArcView GIS extension developed by GeoHealth Incorporated,
allows users in the health care industry to analyze, visualize, and map more than 14,000
of the International Classification of Diseases, Ninth Revision (ICD-9) codes that are
used throughout the health care industry to index every known ailment, treatment, and
procedure. BodyViewer logically aggregates these ICD-9 codes and displays them
graphically as organs and organ systems. The user can build a map showing where these
aggregated ICD-9 codes occur geographically.
Business management and marketing practices for private sector health care
companies have been enhanced through the use of various GIS software packages from
Esri. ArcView Business Analyst provides the data and ease of use that make product line
planning more effective by geographically linking operational data to patient and
provider location data. Areas that are underserved can be pinpointed. Marketing
strategies and promotions can be more effectively targeted to the populations that would
benefit from them through the use of ArcView Business Analyst.
Health care organizations can use GIS to improve management practices. Many
health organizations employ sales personnel. BusinessMAP PRO provides a fast and easy
way to balance sales territories, track prospects, and perform limited market analysis.
Using ArcView GIS, medical supplies and equipment can be visually located and
inventoried. Linking the physical location and condition of equipment or supplies in a
large facility or distributed medical campus is a powerful new management tool.
GIS can enhance customer service for a health care provider. Using, dynamic
maps that show the location of services are readily available over the Web. ArcLogistics
Route improves how, health services are delivered at home by scheduling and optimizing
routes between patients.
3.5 Tomorrow's Health Care
GIS has helped the health care industry manage resources and personnel in of the
same ways it has helped other consumer service enterprises. Use of GIS for business
function--marketing, sales, and facility and materials management will continue to grow.
However, in the increasingly information-intensive environment of tomorrow's
health care, the role of GIS will have greater importance due to its abilities to integrate a
wide range of data sources, from legacy systems to image data, and to make complex
data more quickly and easily understood.
Application of remote sensing (RS) and geographical information systems (GIS)
for Epidemiology and control of lymphatic filariasis (EM 9902 AFR) was developed to
produce filariasis distribution maps for Tamil Nadu, Karnataka, Kerala and Pondicherry,
and to identify the environmental risk factors in relation to occurrence of disease and (iii)
to develop tools for decision making, for the control of filariasis, Karnatakaand
Pondicherry was created in the first year (2000) of the study.
All the possible risk factors that are likely to influence the occurrence of
lymphatic filariasis (either directly or indirectly) were listed under three major categories
viz., physiographic, climatic and demographic. Initially, correlation of such
environmental variables as altitude, water vapour, rainfall, relative humidity and
saturation deficit that are likely to have a direct bearing on the filarial endemicity was
examined. The other variable (‘dummy indicators’) like vegetation and land use / land
cover (soil types, built up structures etc.,) and demographic were dealt with subsequently.
Bivariate (‘Pearson’ correlation) analysis explained a positive association of
filariasis endemicity (point data available in Tamil Nadu) with temperature (r = 0.41, p <
0.05) and rainfall (r = 0.44, p < 0.05). Though there is no direct association between
filariasis endemicity and humidity, a significant association with saturation deficit (r =
0.53, p < 0.01) was observed. The filariasis endemicity was found to have a negative
correlation with altitude ( r = - 0.44, p < 0.05) Multivariate (Multiple linear regression -
stepwise) analysis revealed that among the seven possible risk variables (as stated above)
included in the analysis, only three (altitude, rainfall and saturation deficit) emerged as
significant variables contributing to 64 per cent of the variation in the endemicity rate.
The predictive value of the regression model is low, suggesting that the other variables
like vector breeding potential (land use / land cover etc.), socio-economic characteristics
etc. of the area may also be facilitating the situation conducive for the disease occurrence.
The RS image files have been calibrated to produce Normalized Differences Vegetation
Index (NDVI). The NDVI was also used to determine the land use / land cover pattern.
The cultivable (moisture) and low vegetation zone with composite NDVI values ranging
between 145 and 158 were the areas found to be associated with filariasis prevalence.
The appropriate classification (‘range finding’) for predicting the potential risk of
filariasis is being explored in relation to space and time. The areas are to be classified
ultimately into potentially endemic and non-endemic in terms of environmental
variables. This needs to be validated following a ground truth survey. The outcome of
this survey will form an important base in the map union function, which will facilitate
the creation of mapping tools for decision-making. To achieve this, a sample survey has
been planned in selected geo- coded points in the study area. Once the study area is
classified and the real time point data generated, prediction may be possible with the use
of environmental variables and demographic profiles.
3.6 GIS Information Base filariasis Patients in Kumbakonam: 1998-2008
To create different GIS data base files and also to study the spatial distribution of
filariasis in Kumbakonam the data has been gathered from the Kumbakonam Filarial
Control unit (KFCU) from 1998 to 2008. According to the KFCU there are 272 filarial
cases were reported for the above five years. The individual reported cases are as
follows: 1998 (30 cases), 1999 (3 cases), 2000 (164 cases), 2001 (57 cases) and 2008 (18
cases). The data shows that the reported filarial cases are not uniform. The collected
information has been plotted on to a base map of Kumbakonam and each and every point
has been traced from the address of the affected persons for the above five years. These
maps were first digitized and then the points were also transferred to the respective
location after properly identifying the addresses and street names. The details provided
by the KFCU about the patients were also attached with the sequential data base files and
this would indicate the details of the affected persons. The details include the patient ID,
name of the patient, address with door number and street name, sex category, age, disease
particulars, and how long the person is having the disease and date of treatment. The data
base can be updated with additional information if required. The data base is given in the
Appendix.
Map 3.1 shows the administrative units of Kumbakonam. According to the 2001
census the population of the town is 141,814, spread over in the 45 wards. Map 3.2 is
designed to show the GIS for the spatial distribution of Filarial cases reported in 1998
with attached data base file of the individual cases. There are 30 reported cases during
this period. The spatial distribution shows that the disease has widespread prevalence in
the peripheral wards except one case at the centre of the ward. The reason for low
reported cases are that the people were not willing to/ afraid of giving blood smear for
tests and identification whether the sample person is affected/ probability to be affected.
According to Map 3.3 there are only three cases reported and the locations are in
the western periphery of the town. The data base in the map, for example indicate that
the patient ID is 109; name of the patient is: Kamala; Address: 99, Mukkannar st; Sex: F;
Age: 33; Disease particular: Whether the disease is present either in the left or right leg;
Year: How long you are affected and reported; Date of treatment began: 8-10-1999.
Like wise each and every case data can be studied from the GIS base files. The low
reported cases in this year is due to the fact that the unwillingness of the people who are
living in Kumbakonam to give blood smear for sample analysis and hence the sample
selection was very low. The Health personal who takes the blood during night hours did
not get co-operation from the sample population and this could be the probable reason.
Map 3.4 shows the distribution cases for the year 2000. The number of reported
cases is 164 which is very high when compared to the previous years. The main reason
behind this is that there was no awareness about the filariasis disease among the people of
Kumbakonam and that could be several controlling factors. According to the Health
Department the staff strength has been increased considerably to visit each and every
sample population household and teach them about the disease. They have also taught
them about the surrounding they live and if the disease has grown and how this would
affect the external system and so on. The awareness that was created by the health
personal there has been a widespread response from the sample population and they
themselves voluntarily come forward to give blood samples and due to this co-operation
even in a single house they have identified two or more number of affected persons due
to filarial worm. Map 3.4 shows except few wards all others have reported cases and it is
particularly widespread prevalence in the southern parts of Kumbakonam.
Map 3.5 shows the distribution cases for the year 2001. According to the KFCU
the number of reported cases is: 57 cases. The spatial pattern of disease indicates that it
has widespread prevalence in the western parts of Kumbakonam. The disease has been
brought under control for this year when compared to the previous year.
Map 3.6 depicts the filarial distribution case for the year 2008 and the number of
reported cases is: 18. They are spatially distributed in the southern parts of
Kumbakonam. The considerable decrease in the number of cases when compared to the
two previous years are mainly due to the fact that the health department has actively
engaged in creating awareness among the sample population and involved in preventive
measures like distributing the medicines at their door steps. They keep on watching the
patients as well as their environment. Due to the environmental and disease ecological
awareness there has been a considerable as well as remarkable decrease in the town.
3.7 Conclusion
Filariasis is a dreaded disease, which affects the lymphatic system. The reaction
could be disfiguring of external organs particularly the legs and legs. The main cause of
the disease, which has widespread prevalence in the town could be improper
environmental conditions of the oldest heritage town. The disease could be prevented
only by way of creating awareness among the people and not merely providing medicines
and it is like prevention is better than cure.
4
Chapter
Dimensions of Filariasis in Kumbakonam: A Factor Analytic Method
4.1 Introduction
Filariasis has been identified as one of the six diseases, which are targeted for
elimination. The World Health Organization (WHO) has called for targeting lymphatic
filariasis (LF) elimination by the year 2020 (Ottesen, 2000). The main focus of
intervention to interrupt transmission is to adopt administering a mass annual single dose
(6 mg/kg of body weight) of diethylcarbamazine (DEC) with albendazole (400 mg).
Although substantial progress has been made wherever the strategy has been successfully
implemented to enhance compliance and to reduce infection levels in mosquitoes
(Richards et al. 2005), in certain areas where LF infection prevalence has been reduced to
less than 1per cent, either the elimination remains mysterious or the disease has resurged
(Esterre et al. 2001; Sunish et al. 2002). This may be due to the intervention failure at the
bottom level because of neglect of socio-cultural factors during the planning stages. In
view of this, developing a model to understand the role and impact of socio-economic
determinants, knowledge and practices on LF will be of potential value to identify the
probable causes and their effect on the occurrence of filarial disease. This information
will assist health planners and policy makers in devising appropriate and sustainable
control strategies to eliminate LF.
From a preliminary study with a small sample, it was observed that the proportion
of filarial cases in the lower income group was 0.43. Accordingly, in order to have an OR
of filarial disease of at least two in the lower income group as compared to the higher
income group, the sample size was found to be 264, i.e., 132 cases and 132 controls. An
inclusion criterion for the case was that an individual affected with either lymphoedema
or hydrocele and he/she should be in position to respond independently. For controls the
inclusion criteria were that he/she should be non- infected for LF and should be in a
position to respond independently. Accordingly, respondents covered were of three types,
viz., persons with lymphoedema; hydrocele, which are the major clinical manifestations
of LF (Surendran et al. 1996) in the study area and non-infected individuals. Thus, a
minimum sample size in each group of lymphoedema and hydrocele was fixed to be 135.
Considering the total sample size of lymphoedema and hydrocele cases, the sample size
of the non-infected individuals was fixed to be 270. The sample size was inflated by
40per cent to substitute for non- responsiveness and absenteeism during data collection.
For cases, the address details of patients diagnosed with major clinical manifestations
(lymphoedema or hydrocele), attending filariasis clinics from 1992 to 1997 at Vector
Control Research Centre, State Filaria Control Unit and Government General Hospital,
Pondicherry were listed and numbered serially and this cohort of patients formed the
study population of the affected individuals. From the sample blood survey data
(Manoharan et al. 1997) obtained in 1992, address details of ‘non-infected’ individuals
for W. bancrofti infection were also listed and numbered serially and formed the study
population for control. Respondents with minimum age of 15 years were included in the
study. The required number of individuals from the respective study population was
selected at random using EpiStatver 2000 software program. Each selected individual
was located in his/her house and the nature and purpose of the study were explained to
each respondent verbally. The respondent was assured that his/her identification as well
as information would be kept confidential and the information provided by him/her shall
be used for research purpose only. An attempt was made to determine the knowledge
level on disease transmission, diagnosis, treatment and prevention, mosquito breeding
and control and personal protection measures against mosquito bites.
In many countries, lack of funds and inadequate use of existing cost-effective
tools to fight infectious diseases are compounded by a failure to take account of the
health impact of other sectors.
All too often, the key determinants of health – as well as the solutions – lie
outside the direct control of the health sector. They are rooted in areas such as
sanitation and water supply, environmental and climate change, education, agriculture,
trade, tourism, transport, industrial development and housing. Yet many countries lack
the capacity to measure the impact of other sectors on health. Unless these issues are
addressed, it can be difficult to prevent or even control some infectious diseases.
The link between environmental quality and health, for example, is critical. Over
10per cent of all preventable ill-health today is due to poor environmental quality –
conditions such as bad housing, overcrowding, indoor air pollution, poor sanitation and
unsafe water. Bad housing and poor environmental conditions have the greatest
impact on acute respiratory infections and diarrhoeal diseases. And children are worst
affected – accounting for as much as two-thirds of all preventable ill-health due to
environmental conditions.
In developing countries, about 700 million people – mainly women and children
in poor rural areas – inhale harmful smoke from burning wood and other fuels. They
are increasingly at risk from acute respiratory infections, especially pneumonia. Over a
billion people lack access to safe drinking water – increasing their vulnerability to
diarrhoeal and parasitic diseases. In Africa, Asia and Latin America, at least 600 million
urban dwellers live in unhealthy homes or neighbourhoods. Almost 800 million people
worldwide lack access to health services.
Elsewhere, changes in land and water use can also have a major impact on the
incidence and pattern of disease. Deforestation, agricultural development, dams and
irrigation schemes can trigger outbreaks of parasitic or other infectious diseases through
favouring the spread of malarial mosquitos or freshwater snails that spread
schistosomiasis. Most at risk are the over half a billion poor people who live in
ecologically fragile regions. Other diseases affected by environmental change include
lymphatic filariasis, dengue fever, leishmaniasis, Chagas disease and bacterial meningitis.
Meanwhile, an increase in global warming could have a similar impact on the
spread of tropical diseases. A temperature rise of only 1-2o C over the next 50 years could
extend the range of malarial mosquitos further north – increasing the proportion of the
world's population at risk of malaria and other mosquito-borne diseases such as dengue
and lymphatic filariasis.
Poverty and malnutrition are other key factors that affect health. Malnutrition is
particularly lethal in combination with infectious diseases such as pneumonia, malaria,
measles and diarrhoeal diseases – the major killer diseases affecting children. It is an
underlying factor in over half of all child deaths. In 1997, an estimated 160 million
children were moderately or severely malnourished. More than one in four of the world's
population were estimated to be living in poverty – over a billion of them with incomes
of less than $1 a day. Even in industrialized countries, 100 million people live below the
poverty line.
The critical need for collaboration between health and other sectors has been
highlighted most recently by efforts to prevent HIV/AIDS. A few governments have
attempted to reduce individual vulnerability to HIV/AIDS through a cross-sectoral
approach. The aim is to influence infrastructure development plans, laws, education,
labour policies and the exercise of human rights, for example, in an effort to create an
environment that makes it easier for people to avoid HIV/AIDS. This can involve
providing incentives to enable girls to finish secondary education, boosting job and
educational opportunities for women to break the cycle of economic and sexual
dependency, and ending the criminalization of marginalized groups such as sex workers
and injecting drug users. It can also involve carrying out impact assessments for
development projects to foresee ways in which schemes could fuel the epidemic –
through accelerating the pace of urbanization, for example, or splitting up families
through creating the need for a migrant labour force.
In Thailand, where prostitution remains illegal, the government's pragmatic
approach to slowing down the epidemic has brought a significant decline in infections –
especially among the young. The multispectral approach included work with brothel
owners to urge 100per cent condom use in brothels, the launch of mass media campaigns
to encourage respect for women and discourage men from visiting sex workers, improved
educational and vocational opportunities for women to keep them out of the sex industry
and improved access to care, as well as economic and social support for people living
with HIV/AIDS.
In addition to the need for increased collaboration between the different public
sectors which impact on health, there is a need to build partnerships with the private
sector. The recent launch of the New Medicines for Malaria Venture – a joint initiative
by the public and private sectors to develop new antimalarial drugs – is an example of
efforts to harness greater public and private sector collaboration in developing new
products for use in developing countries. Another example is the donation of drugs by
industry free-of-charge to help eliminate infectious diseases with a high disease burden in
developing countries. These include donations of drugs by pharmaceutical manufacturers
SmithKline Beecham and Merck for the treatment of lymphatic filariasis and river
blindness, and Pfizer for trachoma. In addition vaccine manufacturers have occasionally
donated vaccines during outbreaks of disease, such as meningitis, for polio eradication,
and for vaccine trials in developing countries.
WHO's efforts to eradicate or eliminate diseases are a collaborative effort by
global partnerships. WHO has forged strategic alliances with governments, ministries of
health in developing countries, international development banks, foundations, the private
sector, civil society, non-governmental and international organizations and other UN
agencies.
Global efforts to eradicate polio, for example, have demonstrated what can be
achieved through private sector collaboration. Rotary International, a private sector
service organization, has raised $500 million to fund vast quantities of vaccine for mass
immunization campaigns and to help equip a refrigerated cold chain for vaccine
transport. Rotary has used its global network of over 28 000 clubs in 155 countries to
enlist volunteers to carry out social mobilization campaigns, provide organizational skills
for immunization campaigns, and administer polio vaccine drops to children.
4.2 Filariasis in Kumbakonam
Kumbakonam is one of the Special Grade Municipal towns in Tamil Nadu since
1988. It is the second largest town in Thanjavur District having a taluk head quarters
with a population of 139264 according to the 2010 census. Kumbakonam is also termed
as “Temple City” because of the presence of more temples when compared to other
towns in TamilNadu. ‘Maham’ is one of the major Hindu festivals which are being
celebrated once in twelve years held in the month of ‘Masi’ (February-March) which is
equivalent to the “Kumbamela” in the North India. There is however problems and we
should keep them in our mind as well. The most important of these is the half-hearted
participation of the community and the ‘resigned’ attitude of the individuals afflicted with
the disease. And there are other problems, too. No proper drainage system is in place, in
any of the territorial jurisdiction. All the waste waters stagnate on the main roads and
thoroughfares. Sometimes, the waste water is from the residential areas. The people
must be made to know that the environmental management is not solely dependent on the
personnel of the health department.
4.3 Technique of Analysis
Factor analysis is a generic term that we use to describe a number of methods
designed to analyze interrelationships within a set of variables or objects [resulting in] the
construction of a few hypothetical variables (or objects), called factors, that are supposed
to contain the essential information in a larger set of observed variables or objects that
reduces the overall complexity of the data by taking advantage of inherent
interdependencies [and so] a small number of factors will usually account for
approximately the same amount of information as do the much larger set of original
observations. Cureton and D'Agostino (1983) described factor analysis as "a collection of
procedures for analyzing the relations among a set of random variables observed or
counted or measured for each individual of a group". The purpose, they said, "is to
account for the intercorrelations among n variables, by postulating a set of common
factors, considerably fewer in number than the number, n, of these variables". Bryman
and Cramer (1990) broadly defined factor analysis as "a number of related statistical
techniques which help us to determine them [the characteristics which go together]”.
Gorsuch (1983) reminded the reader that "all scientists are united in a common
goal: they seek to summarize data so that the empirical relationships can be grasped by
the human mind”. The purpose of factor analysis, he said, "is to summarize the
interrelationships among the variables in a concise but accurate manner as an aid in
conceptualization". These definitions most likely make a great deal of sense to those
"left-brained" individuals who understand complex things fairly easily. Kerlinger (1979)
gave both a left-brained and a right-brained definition of factor analysis.
For the left-brainers: "Factor analysis is an analytic method for determining the
number and nature of the variables that underlie larger numbers of variables or
measures". And for the right-brainers he noted: "It [factor analysis] tells the researcher, in
effect, what tests or measures belong together--which ones virtually measure the same
thing, in other words, and how much they do so”. He further commented on factor
analysis in terms of curiosity and parsimony. He noted, "Scientists are curious. They
want to know what's there and why. They want to know what is behind things. And they
want to do this in as parsimonious a fashion as possible. They do not want an elaborate
explanation when it is not needed.” He sounds like a very right-brained individual! Each
definition of factor analysis has common elements. Each refers in some way to the
correlations among variables as reflected by the use of the words interrelationships,
intercorrelations and relations. Further, each definition makes clear the notion of reducing
the number of variables into a smaller set of factors. In short, factor analysis helps to
explain things by reducing large amounts of information into a manageable form and
size. Now that is an explanation that right-brained individuals (and of course, lefties, too),
can comprehend!
4.3.1 The Process of Factor Analysis: Data matrix
The first step in an exploratory factor analysis is to display the data in a data
matrix. A data matrix is "any array of numbers with one or more rows and one or more
columns" (Reymont & Joreskog, 1993). This appears to be quite straightforward (much
to the surprise and relief of the right-brained). Ah, but not so fast. In an effort to
complicate matters, there are issues of a vector (a matrix that has only one row) and a
scalar (which has both one row and one column), as well as a variety of matrices
identified by Gorsuch (1983) in developing factor analytic concepts. (The right-brained
among you are possibly noticing a constriction of air passages at the number of possible
options, but not to worry. This is merely an introductory paper on the topic of factor
analysis). Correlation Matrices. In order to determine the factors underlying the
variables, a "variable reduction scheme" (Gorsuch, 1983) is used which shows how the
variables cluster together; i.e., the variables are correlated with one another. These
correlations are represented in a matrix of association. A statistical measure of
association such as the Pearson r is used to indicate the magnitude of the correlations. A
correlation (or variance-covariance) matrix represents the relationships among the set of
variables in the study. In this correlation (or variance-covariance) matrix of variables, the
values located on the diagonal will be 1.0. This is because each of the variables will
correlate perfectly with itself. The off-diagonal elements are the co-variances between all
variable pairs. (Remember, right-brainers, this simply means the correlations between the
variables.) Because the number of correlations in the matrix reflects the number of
variables used in a study, it is possible that a single correlation matrix may have
thousands of entries. Factor analysis, explained Hetzel (1995), "attempts to simplify the
correlation matrix by accounting for a large number of relationships with a smaller
number of explanatory constructs [i.e., factors]". He further stated that these hypothetical
factors are determined by examining additional data matrices, specifically the factor
pattern matrix and the factor structure matrix.
In much of the literature on factor analysis, the term "factor loading" is used
instead of the more accurate terms, factor pattern coefficients and factor structure
coefficients, which are the elements comprising the factor pattern and factor structure
matrices. The exact nature of these coefficients and corresponding matrices is beyond the
scope of this paper. The important element is that factor pattern coefficients represent the
relationship of a specific variable to a specific factor without the influence of other
variables (Stevens, 1992). The factor structure coefficients can be thought of as being
identical to structure coefficients in other types of Correlation analyses. These
coefficients show the correlations of the variables with the factors (Hetzel, 1995). It is
with the results of these additional matrices, and through the careful interpretation of the
data, that the factors are extracted and interpretations made.
4.4 Extracting the factors
We are reminded by Cattell (1978) that "factor analysis is, in principle, nothing
more than asking what the common elements are when one knows the correlation". It is
at this point, when we have calculated the correlations between the variables and factors
that we can begin to determine the number of factors underlying the variables. The chief
concern, at this stage, according to Kim and Meuller (1978) is whether a smaller number
of factors can account for the co-variation among the original, larger set of variables.
Gorsuch (1983) indicated that there are numerous methods that can be used in deciding
how many factors to retain. Again, these methods are too detailed for the current paper,
but in general, regardless of the method used, he suggested that "one would want to
account for at least 70per cent of the total variance".
The critical point in deciding how many factors to retain is that this decision
requires the researcher to carefully consider the data and to use his or her judgment. As
with many other statistical concepts, a number of decision rules are available to help
guide the researcher with the decision as to the specific number of factors to retain. This
topic was summarized by Hetzel (1995): Regardless of the rules eventually used, when
considering the number of factors to retain, it is important for the researcher to remember
the advantages and limitations of the various decision rules and to make a subsequent
decision in a thoughtful and well-reasoned manner, based on the nature of the analysis.
4.5 Interpretation of the factors
Following the initial extraction of factors, an interpretation of these factors is
necessary. Kim and Meuller (1978) pointed out: It is important to emphasize that factor
analysis does not tell the researcher what substantive labels or meaning to attach to the
factors. This decision must be made by the researcher. Factor analysis is purely a
statistical technique indicating, which, and to what degree, variables relate to an
underlying and undefined factor. The substantive meaning given to a factor is typically
based on the researcher's careful examination of what the high loading variables measure.
Put another way, the researcher must ask what these variables have in common.)
It should be noted that the factors must be called something other than the name
of a particular observed variable. The reason for this is that factors are latent aggregates
of observed variables and the factor name should represent the aggregate and not be
confused with a specific measured variable. At this point in the analysis, the minimum
number of factors that can account for the observed correlations have been identified and
named. To obtain a more easily interpretable solution regarding the factors, the researcher
can engage in a process known as rotation. This is most easily done by computer and
again, is too complicated a matter for this paper. The results of rotation, however,
indicate "the simplest solution among a potentially infinite number of solutions that are
equally compatible with the observed correlations" (Kim & Mueller, 1978).
The process of exploratory factor analysis results in the smallest and most
compatible number of underlying factors from a larger set of initial variables on a test or
instrument. The process can be summarized as follows: (a) the researcher collects
observed scores (raw data) on an instrument without having a preconceived notion as to
the number of underlying factors, (b) presents this information in data matrices, (c)
correlates the variables, and (d) identifies the factors underlying the variables.
The impact of transmission heterogeneities to immune- epidemiology of
lymphatic filariasis: The objective of the study is to examine the variations in exposure
to mosquito biting at individual and household level and relate them to prevalence of
infection in human population. The study has been carried out in a village with a
population of 2083 in Villupuram district in Tamil Nadu, endemic for Wuchereria
bancrofti transmitted by Culex quinquefasciatus. The prevalence of chronic lymphatic
filariasis wass 15.2 per cent in the village.
A total of 139 randomly selected households have been included in the study.
These households have been monitored for a year to quantify the transmission intensity,
prevalence of microfilaraemia and antigenaemia and also incidence of acute disease.
Exposure to infection was assessed by fingerprinting the blood meal of vector mosquitoes
and parallel human blood samples in respective households, using a 9-locus radioactive
STR system based PCR for amplification. W. bancrofti infection in human subjects was
determined by membrane-filtration of microfilariae from blood. Humoral immune
response, in terms of filarial specific IgG1, IgG3, IgG4 and IgE antibody levels, and
circulating filarial antigen levels among members of the selected households, were
investigated on two time points. The results of the study are summarized below.
Out of 276 blood meal PCR fingerprints, 73 per cent of mosquitoes resting in a
house had fed on people within that household, whereas 27 per cent of them had fed on
people outside the house, which implies that a considerable number of mosquitoes move
between households. Additionally, 13 per cent of mosquitoes had multiple feeds on
different individuals in the household, with the rate of multiple feeding depending on the
density of humans in the household. Further, younger age classes (5-30 years) were bitten
by vectors more frequently than the older age classes.
4.6 Household level variation in vector infection and mf prevalence
134 households have matched data for entomology and parasitology. Out of 134
households, 31 (23 per cent) households were free from infected mosquitoes and mf
carriers. The remaining 103 (103/134=76.8per cent) households have either mf carriers
and/or infected mosquitoes. 37 households (37/134=27.6 per cent) have both mf carriers
and infected mosquitoes. 12 (12/134=8.95 per cent) households have only mf carriers,
with no infected mosquitoes. 54 out of 134 (40 per cent) households have only infected
mosquitoes, with no mf carriers. Only 16 out of 134 (=11.9 per cent) households were
found with infective mosquitoes, an evidence for active transmission.
4.6.1 Households with mf carriers
49 out of 134 (36.5 per cent) households have mf carriers. The number of mf
carriers per household ranged from 1 to 3 (Fig. 4.10). 37 of these 49 households (=75.5
per cent) have infected mosquitoes. 12 of these 49 households (12/49=24.5per cent) have
no infected mosquitoes. Out of 85 households with no mf carriers, 54 (63.5 per cent)
were with infected mosquitoes. Infective mosquitoes were found in only 8 of the 49
(=16.3 per cent) households with mf carriers. The average number of mf carriers per
household is 0.49 (range: 1-3). The over all mf rate is 13.8 per cent (66/479*100). When
considered only those households with a sample size of =>5 each were considered, a
maximum prevalence of 42.8 per cent (3/7) was observed in one household.
4.6.2 Households with infected mosquitoes
91 out of 134 (67.9 per cent) of the households are with infected mosquitoes. 37
of these 91 (=40.6 per cent) households were found with mf carriers. 43 out of 134
households (=32.1 per cent) are free from infected mosquitoes. However, 12 of these 43
households (27.9 per cent) are with mf carriers. Out of 16 households with infective
mosquitoes, only 8 (=50 per cent) households have mf carriers.
4.6.3 Transmission dynamics
The per-man hour resting density ranged from 0 in five households to 57. Only
one household has a density of 93, in which 2 out of 5 people sampled were found to be
positive for mf. The infection rate ranged from 0per cent to 42.9 per cent and infectivity
rate from 0per cent to 9.1 per cent
4.6.4 No. of mf carriers
(Only those households from where minimum of 20 mosquitoes were dissected
were considered). The transmission intensity index ranged from 0 to 19.5 in one house,
where also 2 out of 5 sampled persons were found positive for mf.
4.6.5 Antigenaemia prevalence
The prevalence of the circulating filarial antigenaemia (CFA) was 27.7per cent in
the study population (n=465). A one year follow up of 73 individuals with CFA showed
that 52 (71.2 per cent) remained positive for CFA and 21 (28.8 per cent) turned negative.
12.8per cent of the CFA negative individuals (n=188) turned positive during the one year
period. The antigenaemia prevalence and intensity was maximum in 21-30 year age class
and minimum in 41-50 year age class and it tended to increase in >50 year age classes.
4.7 Filariasis in Kumbakonam: Spatial Dimensions
To study the Spatial Dimensions of people in Kumbakonam town among the 272
cases 100 samples (nearly 40 per cent of the sample) have been considered to find the
various factors that are responsible for the prevalence of the disease. A questionnaire
schedule was prepared with 68 relevant questions to gather information about the
people’s perception about their environment and disease. The questions include apart
from the basic information about the respondent, age of the person, sex category and the
level of education the additional and major information such as: environmental
perception about the disease, stagnant water areas nearby, presence of marshy
environment, existing drainage facilities either drain or open pits, waste water stagnant
pools b\nearby, lavatory and intact septic tank facility, usage of mosquito bite prevention
methods, health personal attention towards the anti-mosquito spray, collection of blood
samples and co-operation with the health personal, stages of the disease and place of
occurrence, medical treatment after the disease presence, side effects during oral
medicine, presence of disease through whom, psychological attitudes about the
neighbours, relatives and friends with the filarial disease persons and how the patient
feels once the disease has affected. The questionnaire schedule is given in the Appendix.
The data for the above variables were gathered from the affected respondents
tracking with the addresses obtained from the KFCU. The survey was conducted for one
month and after the survey the schedule was converted into a geographical data matrix.
The data was studied carefully and among the 68 variables the most important and
justifiable variable of 32 (Table 3.1) have been selected for the 100 samples. Now the
data matrix is in the form of 32 * 100. The data was then fed into the computer and the
Factor analysis method was performed by using SPSS package version 10. The results of
the factor analysis are given in the tables 3.2 and 3.3. The results of the rotated factor
structure and the eigenvalues, percentage of contribution, cumulative contribution and the
communality are given in table 3.4.
Table 3.1 Variable Description and Variable Code
Variable Code Variable Description X1 AOR Age of the Responded X2 LOE Level of Education X3 PFD Perception about the Filarial disease X4 EID Environmental implication about the disease X5 PAD Perception about dirty X6 PWS Perception about Waste water stagnation X7 PMM Perception about Mosquito menace X8 PVC Perception about vegetation cover X9 PAD Perception about options of drainage X10 ADF Availability of drainage facility X11 ASP Availability of waste water in stagnant pools X12 ALF Availability of Lavatory facility X13 AST Availability of septic tank X14 UMC Usage of Mosquito Coils X15 UON Usage of Odomos during night X16 UGB Usage of good night and banish mates X17 HPA Health personal attention towards antimosquito spray X18 CBS Collection of blood semears at night X19 CFW Co-operation with of field workers during collection of blood semears X20 SOD The stage of the disease X21 COT Consumption of tablets regularly after disease presence X22 NDT Number of doses and time periods X23 SHE Side effects- Headache during the tablet conception X24 SEJ Side effects routine job per how many days X25 PEC Preventive efforts to curtail disease
X26 PDP Presence of disease through public health department X27 PSD Presence of disease surfaced while distributing tablets X28 TFM Treatment of your family members X29 TYN Treatment of your neighbors X30 TYR Treatment of your relatives X31 PAB Psychological attitude-Bitter X32 PAF Psychological attitude-Fate
Factor analysis is used to uncover the latent structure (dimensions) of a set of
variables. It reduces attribute space from a larger number of variables to a smaller
number of factors and as such is a "non-dependent" procedure (that is, it does not assume
a dependent variable is specified). Factor analysis could be used for any of the following
purposes: To reduce a large number of variables to a smaller number of factors for
modeling purposes, where the large number of variables precludes modeling all the
measures individually. As such, factor analysis is integrated in structural equation
modeling (SEM), helping create the latent variables modeled by SEM. However, factor
analysis can be and is often used on a stand-alone basis for similar purposes. To select a
subset of variables from a larger set, based on which original variables have the highest
correlations with the principal component factors. To create a set of factors to be
treated as uncorrelated variables as one approach to handling multicollinearity in such
procedures as multiple regression. To validate a scale or index by demonstrating that its
constituent items load on the same factor, and to drop proposed scale items which cross-
load on more than one factor.
Table: 3.2 Principle Component Matrix
Variable Code Component
1 2 3 4 5 6 7 8 9
X29 TYN .878 -.228 .190 -.212 0.050 0.066 .102 .179 -0.063
X30 TYR .876 -.221 .182 -.194 0.055 0.088 0.064 .139 -0.064
X28 TFM .808 -.151 .223 -.419 -.108 0.002 0.057 .109 -0.021
X20 SOD .506 0.006 -.432 0.037 0.099 .191 -.267 0.066 -0.027
X23 SHE -.401 -.130 .331 -0.050 .303 -.101 -0.015 -.155 0.077
X12 ALF .241 .860 -0.002 0.002 .149 -.239 0.035 0.063 -0.044
X13 AST .232 .857 0.010 -0.042 .126 -.264 -0.010 0.026 -.085
X7 PMM -0.026 .377 0.055 -0.074 0.055 .211 .231 .197 0.023
X21 COT -0.053 -.174 .699 .142 -.155 -.299 -.142 .205 -.164
X22 NDT -0.035 0.036 .601 0.084 .251 -.295 -0.020 .309 0.039
X24 SEJ -.209 -.126 .489 -0.035 .156 -.102 0.069 -.357 -.223
X32 PAF -.329 -.119 -.434 -0.078 -0.075 -.349 .427 .186 .258
X19 CFW -0.024 -.135 .398 .117 -.164 0.031 0.071 -0.065 .237
X27 PSD .257 -.198 -.182 .580 .421 .131 .314 .196 -0.059
X26 PDP .224 -.278 -0.038 .564 .478 0.046 .310 0.070 -.150
X25 PEC .105 -.116 0.038 .477 -.239 .368 0.0001 -0.065 0.077
X3 PFD .387 .262 .254 .472 -.353 -0.095 .186 -.164 .203
X18 CBS 0.006 -0.039 .238 -.375 .296 .118 .132 -.173 .364
X2 LOE 0.075 -0.069 -0.021 -.238 .517 -0.043 -.419 .-0.046 .226
X17 HPA .101 -0.087 .222 .125 -.395 .330 0.038 -.142 .224
X10 ADF -.298 0.075 .188 .227 -.163 .477 .108 .333 .250
X6 PWS -.159 -0.008 .263 .208 0.038 .419 0.037 -0.027 -.130
X14 UMC -.238 .198 0.086 -.196 .217 .379 -0.026 .353 -0.001
X8 PVC 0.013 0.014 0.0009 -.339 0.049 .240 .611 -.237 -0.012
X9 PAD -0.001 -.296 -.118 .242 .158 -0.015 -.429 .237 0.090
X11 ASP -0.061 -.350 -0.039 -.206 -0.075 -0.097 .136 -394 -0.032
X31 PAB -0.054 .201 .191 .172 .350 .371 -.253 -.380 -.146
X15 UON .273 0.088 .146 .134 .201 -.233 .188 -.333 -.144
X16 UGB .275 .184 .285 -.154 161 -0.072 .111 .307 .147
X5 PAD 0.046 .291 -0.037 -.100 .423 -266 .134 .134 .527
X4 EID .283 .402 0.094 .297 .160 .140 0.009 -.221 .482
X1 AOR -.370 0.032 0.076 -0.069 .119 -0.008 .279 .237 -.482
Source: Factor Analysis using SPSS package Table: 3.3
Rotated Component Matrix Variables Code Component
1 2 3 4 5 6 7 8 9
X29 TYN .958 0.006 -0.017 .161 0.062 -0.074 -0.001 0.046 0.035
X30 TYR .939 0.002 -0.040 .154 0.075 -0.090 0.046 0.052 0.019
X28 TFM .938 0.024 -.0009 -.127 0.068 -.101 -0.051 0.049 .108
X12 ALF 0.029 .937 -0.026 -0.046 0.011 -0.017 0.021 -0.012 0.059
X13 AST 0.026 .927 -0.012 -.112 -0.019 -0.061 0.048 -0.025 0.052
X11 ASP -0.019 -.371 0.014 -.112 -0.024 -.362 -0.031 0.062 .269
X21 COT .151 -0.074 .754 -0.088 .102 -0.026 0.045 -.211 -.264
X22 NDT .109 .194 .697 .103 -0.0007 .133 -0.028 .148 -.178
X20 SOD .353 0.059 -.589 0.038 0.028 -0.062 0.055 -0.086 -.275
X24 SEJ -.110 -.140 .517 -0.027 -0.052 -.230 .323 0.044 .233
X23 SHA -.298 -.152 .426 -0.013 -0.079 -0.044 .143 .321 0.086
X27 PSD 0.078 -0.008 -.104 -885 0.028 0.042 -0.029 -0.022 -0.079
X26 PDP 0.073 -0.066 0.067 .878 -0.008 -0.096 0.077 -0.004 -0.039
X3 PFD .123 .284 0.089 .126 .727 -.126 -0.004 -.278 0.030
X4 EID -0.019 .392 -.142 .167 .576 0.042 .185 .309 0.024
X17 HPA 0.098 -.243 0.039 -.119 .511 .164 .134 -.137 0.097
X1 AOR -.171 0.015 .279 .131 -.494 .183 -0.016 -.278 .220
X19 CFW 0.025 -.179 .303 -0.040 .186 0.076 0.019 -0.028 0.044
X25 PEC -0.082 -0.009 .150 .169 .372 -.310 -.194 -.240 -.263
X10 ADF -.208 -.124 -0.009 0.084 -.248 .680 0.004 -0.096 0.002
X14 UMC -0.046 0.089 0.012 -0.034 -.263 .580 .133 .143 0.053
X15 UON 0.041 .225 0.083 .268 0.011 -.473 0.046 0.004 .163
X7 PMM 0.073 .308 -0.022 0.035 -0.030 .366 0.012 -0.033 .241
X16 UGP -0.090 .114 .326 -.239 0.029 .363 -.227 -0.022 0.073
X32 PAF -.326 -0.083 -.102 0.084 -.109 -0.019 -.744 0.050 .169
X31 PAB -.168 0.096 -0.013 .100 0.021 -0.004 .725 .156 0.019
X6 PWS -.101 -.143 .120 .150 0.079 .291 .389 -.126 0.093
X2 LOE 0.084 0.035 -0.043 -0.057 .197 -0.083 .162 .640 -.266
X5 PAD -0.014 -.120 .135 .220 0.0007 -0.022 -.412 .630 0.093
X18 CBS 0.092 0.004 .109 -.116 0.075 0.033 0.066 .558 .339
X8 PVC 0.089 -0.077 -0.079 0.053 -0.038 0.044 -0.029 0.071 .757
X9 PAD -0.012 -.201 -0.054 .159 -0.062 0.043 0.009 .135 -.584
Source: Factor Analysis using SPSS package
Table 3.4 Spatial Dimensions of Filariasis in Kumabakonam: Rotated Factor Structure
Variables Code F1 F2 F3 F4 F5 Comm Dimension I: Environmental Quality of life
Open/No drainage facility X10 0.740 0.956 Water stagnant areas nearby X11 0.944 0.928 Septic tank intact/ availability X12 0.920 0.925 Marshy environment/ more vegetation cover
X8 0.886 0.883
Dimension II: Perception about the Environment Environmental perception about the disease
X4 0.963 0.885
Perception about mosquito menace
X7 0.837 0.801
Perception about open drainage pits
X9 0.625 0.704
Usage of mosquito bite protection methods
X16 0.581 0.701
Dimension III: Stages of Filariasis and Medical Treatment Types of disease and stages X20 0.682 0.809 Tablet consumption and doses X22 0.655 0.666 Types of side effects and number of days
X23 0.634 0.606
Satisfaction about the treatment by MO’s.
X24 0.619 0.618
Dimension IV: Health care Towards the Disease Towards anti-mosquito spray regularly
X17 0.518 0.728
Collection of blood smears regularly
X18 -0.452 0.599
Provision of Tablets regularly X21 0.692 0.566 Co-operation with the field worker
X19 0.425 0.529
Dimension V: Psychological Attitudes and Awareness Treatment by family members X28 0.745 0.567 Treatment by neighbors and relatives
X29 0.763 0.486
Personal Psychology X31 0.565 0.458 Preventive efforts to curtail the disease
X25 0.431 0.456
Eigen values 3.712 2.633 2.321 2.159 1.919 Percent of variance explained 11.601 8.229 7.253 6.746 5.996 Cumulative percentage of variance
11.601 19.830 27.083 33.829 39.826 40.000
Source: Factor Analysis using SPSS package
The dimensions, based on the variables loading on them and on the strength of the
loadings themselves, have been designated as follows:
Dimension-I Quality of Life
Dimension-II Environmental Perception
Dimension-III Stages of Filariasis and Medical
Treatment
Dimension-IV Health Care Towards the Disease
Dimension-V Psychological Attitude and Awareness
Measures
4.7.1 Dimension-I: Quality of Life
The four variables loading significantly on the factor are: open/ or no drainage
facility (loading 0.740), water stagnant areas nearby (0.944), septic tank intact/
availability (0.920), and marshy environment/ more vegetation cover (0.886). All the
variables are positively loaded and very significantly as well. The dimensions appear to
be implying that these four major variables play a significant role in creating a conducive
atmosphere for the vectors to grow either in the stagnant water areas or in the marshy
environment. The adverse environmental conditions are clearly co-ordinates with the
above variable, which transmits the filarial worm into the human body which ultimately
affect them in this region. The Eigen values of the main factor dimension are 3.712 and
the variance explained is 11.061 per cent. All the variables have high communality
unique variations as well.
4.7.2 Dimension-II: Environmental Perception
The second dimension is the perception about the environment of the people in
this region and all the variables are positively loaded. The main variables in this category
are environmental perception about the disease (0.963), perception about mosquito
menace (0.837), perception about open drainage pits (0.625) and usage of mosquito bite
protection methods (0.581). Environmental perception is a major factor in any urban
setting and several studies indicate that if the people’s perception about their surrounding
is good they lead a healthy environment. In the present context in the study area the
perception about the living environment contributes major underlying variable positively.
From the majority of the affected persons, they do not have any idea about the presence
of disease and some of them think that the bulging of leg or hand is due to some other
problem and not due to lymphatic filariasis. Similarly they patients do not agree with the
point that it is due to drainage water and stagnant water, which forms mosquito breeding
grounds. This dimension has an Eigen value of 2.633 and the variance explained is in the
order of 8.229 per cent.
4.7.3 Dimension-III: Stage of Filariasis and Medical Treatment
Stages of filariasis and Medical treatment forms the third dimension with the
major underlying variables are: types of disease and stage (0.682), tablet consumption
and doses (0.655), types of side effects and number of days (0.634) and satisfaction about
the treatment by medical officers (0.619). There are three stages of filariasis: early stage,
mature and old stage. Due to lack of awareness about the people they approach the
medical officers of the Filarial Control Unit only they attain either the mature stage or the
very late stage. Some time the recent co-operation by the people of this region for the
regular blood smear tests the disease is being identified at the early stages. They
immediately have given the prescribed medicines with number of doses. Some time the
medicines would react the patients and the alternate solutions are being given. This
dimension has an Eigne value of 2.321 with the percentage variance of 7.253.
4.7.4 Dimension-IV: Health Care towards the Disease
The fourth dimension is the Health care towards the disease. There are four
variables loaded in this factor and they are: Towards anti-mosquito spray regularly
(0.518), collection of blood smears regularly (-0.452), provision of tablets regularly
(0.692) and co-operation with the field worker (0.425). Recent years the peoples were
given proper knowledge about the filarial disease and its ecological factors that allows
the mosquito to grow and interaction with the people by the KFCU. People in this region
constantly watching the anti-mosquito liquids being sprayed with regular intervals. The
number of incidence has been increased during 2000 which was purely identified by the
health officers after properly testing the blood smears. This means in the previous years
the people were not co-operative and hence they were hiding the disease. The tables are
being distributed regularly for the positive cases of filariasis patients and even in single
house there are two or more number of afflicted persons were identified. The co-
operation with the field worker is highly positive and it is due to the increase in
awareness about the disease and to take all preventive measures individually. This fourth
dimension has an eigne value of 2.155 with a contribution of 6.746 percentages.
4.7.5 Dimension-V: Psychological Attitudes and Awareness Measures
The final factor is the Psychological attitudes and awareness measures that are
being taken/ under consideration. The variables loaded in this category are: treatment by
family members (0.745), treatment by neighbours and relatives (0.763), personal
psychology (0.565) and preventive efforts to curtail the disease (0.431). Psychological
attitudes about the affected persons with enlarged legs and hands are one of the major
underlying phenomenons that have to be considered seriously. The reason is that how
they feel once the disease is affected and how they move with the enlarged organs and
how the others who are nearby, friends and relatives and their attitudes about the affected
persons and so on. Naturally the people in the surrounding particularly in the affected
zone would take care of their environment to curtail this type of adverse disease. As per
this study the psychological attitudes of the people have been changing towards their
environment and taking all the control and preventive measures. This factor has an Eigen
value of 1.919 with a percentage contribution of 5.996.
4.8 Conclusion
The Results of Factor Analysis yielded five spatial dimensions, namely, Quality
of Life, Environmental Perception, Stages of Filariasis and Medical Treatment of the
patients/ afflicted, Health Care Towards the Disease and Psychological Attitudes and
Awareness Measures, from the samples gathered from the affected persons in the study
area.
5 Chapter
Recommendations and Conclusion
Elimination and eradication of human disease has been the subject of numerous
conferences, symposia, workshops, planning sessions, and public health initiatives for
more than a century. Although the malaria, yellow fever, and yaws eradication
programmes of earlier years were unsuccessful, they contributed greatly to a better
understanding of the biological, social, political, and economic complexities of achieving
the ultimate goal in disease control. Smallpox has now been eradicated and programmes
are currently under way to eradicate poliomyelitis and guinea-worm disease. In 1993, the
International Task Force for Disease Eradication evaluated over 80 potential infectious
disease candidates and concluded that six were eradicable. In 1997, the World Health
Assembly passed a resolution calling for the "elimination of lymphatic filariasis as a
public health problem".
The favorable attributes and potential benefits of eradication programmes are a
well-defined scope with a clear objective and endpoint, and the duration is limited.
Successful eradication programmes produce sustainable improvement in health and
provide a high benefit-cost ratio. Eradication programmes are attractive to potential
funding sources because they establish high standards of performance for surveillance,
logistics, and administrative support; develop well-trained and highly motivated health
staff; assist in the development of health services infrastructure including, for example,
mobilization of endemic communities; and provide equity in coverage for all affected
areas, including urban, rural, and even remote rural areas. They also offer opportunities
for other health benefits (e.g. for dracunculiasis eradication: health education and
improved water supply), improved coordination among partners and countries, and
dialogue across frontiers during war. Decisions on initiating a global disease eradication
campaign should also take into consideration the ideal sequencing of potentially
concurrent campaigns. Eradication programmes consume major human and financial
resources. Careful consideration must be given to whether two or more eradication
programmes are to be conducted simultaneously or sequentially, or if the target disease is
confined to a limited geographical area.
Disease elimination and eradication programmes can be distinguished from
ongoing health or disease control programmes by the urgency of the elimination and
eradication programmes and the requirement for targeted surveillance, rapid response
capability, high standards of performance, and a dedicated focal point at the national
level. Eradication and ongoing programmes constitute potentially complementary
approaches to public health. There are areas of potential overlap, conflict and synergy
that must be recognized and addressed. In many cases the problem is not that eradication
activities function too well but that primary health care activities do not function well
enough. Efforts are needed to identify and characterize those factors responsible for
improved functioning of eradication campaigns, and then apply them to primary health.
Evaluation of the effectiveness of advocacy measures for sustained
compliance with DEC mass treatment for the elimination of lymphatic filariasis in Tamil
Nadu, south India (EM 9901 AFR) the strategy recommended for elimination of LF
consists of (i) annual single dose mass treatment with anti-filarial drugs to interrupt
transmission and (ii) morbidity management to alleviate suffering in chronic patients. The
state government of Tamil Nadu launched annual DEC mass treatment programme in 12
districts in the year 1997-98. Evaluation of programme in some districts in Tamil Nadu
and information from other parts of the country suggest that the extent of distribution of
drug and peoples’ compliance with treatment is limited by certain operational problems
and lack of enthusiasm among people to participate in the programme. In the first few
rounds of MDA, drug distribution rates were in the range of 65per cent to 80per cent and
treatment compliance rate ranged from 50per cent to 65per cent. It is hypothesized that
the treatment compliance rate should be above 80per cent to facilitate elimination of LF.
Based on these results it was concluded that an advocacy campaign is necessary to
improve the drug distribution and treatment compliance rates. Therefore a study has been
undertaken to understand the factors that influence drug distribution and treatment
compliance, facilitate development of advocacy material by the state government,
monitor and evaluate the effectiveness of the advocacy campaign. The study was jointly
carried out by VCRC and the Department of Public Health and Preventive Medicine
(DPH), Government of Tamil Nadu.
The study consists of two phases – first phase envisages collection of baseline
information and development of advocacy strategy and second phase implementation and
evaluation of advocacy strategy. While VCRC played a major role in the base line
information collection and evaluation of the strategy, the DPH was primarily responsible
for the development and implementation of advocacy strategy. The annual mass
treatment programme was implemented in 12 districts in the year 2001. Until 2001, in all
the districts only DEC was distributed. The base-line (pre-advocacy) information has
been collected in Cuddalore and Villupuram districts in Tamil Nadu.
The phase I study focused on understanding the factors that influences drug
distribution and treatment compliance and the people’s knowledge of filariasis through
qualitative research methods and assessment of pre-advocacy drug distribution and
treatment compliance rates through quantitative questionnaire survey. 2.05 per cent
households in Cuddalore district and 2.52 per cent households in Villupuram district had
one or more of their members affected with elephantiasis. The respective figures for
hydrocele were 10.71per cent and 13.76 per cent. However, a majority of respondents
consider elephantiasis and hydrocele as different disease entities. While hydrocele was
recognized as a common health problem in all villages, respondents in 32 per cent of the
villages only said that their communities were affected by elephantiasis. About 34per
cent of the respondents believe that elephantiasis can be spread from one person to
another and the same proportion attributed elephantiasis to mosquito bite.
Other important perceived causes of elephantiasis were drinking water from
local ponds, accumulation of bad fluid in the legs and poor hygiene around the houses.
Only 9 per cent believe that hydrocele can be spread from person to another and injury
and heredity were the perceived causes of hydrocele. While 28 per cent believed that
elephantiasis can be cured, 72 per cent thought it can be prevented. The most important
way of prevention was said to be taking medicine. 86per cent of the respondents said that
hydrocele can be cured and 72 per cent suggested surgery is the best option for that.
About 45 per cent believe that the elephantiasis disease can be eradicated from their
communities. However, the private practitioners, health workers and PHC medical
officers felt that annual mass treatment alone may not be able to eliminate lymphatic
filariasis. They emphasized very much that improvement in sanitation and vector control
measures are also necessary to achieve elimination of LF. Community members also
believe that the government’s effort to control filariasis will be successful, as seen with
other diseases such as polio, and feel that people should extend support to these
programmes.
About 85 per cent of the people were aware of drug distribution in their
communities for elimination of elephantiasis and 73 per cent believed that the drug
protects them against the disease. The drug distribution rate was 72 per cent (range 49 per
cent to 89 per cent in different villages and urban wards) in Cuddalore district, it was 71
per cent (range 0 per cent to 94 per cent) in Villupuram district. However, many people
who received the drug failed to consume and therefore the final compliance rate with
treatment was much lower than the distribution rate. The treatment compliance rate was
34 per cent (range 16 per cent to 73 per cent) in Cuddalore district and 32 per cent (range
0per cent to 58 per cent) in Villupuram district. A number of respondents felt that many
people received tablets but did not bother to consume the tablets either because they were
not told about the importance of the programme or did not feel that consumption of the
drug is necessary. Some expressed that the programme should have been implemented in
a better way as it has been done in Polio and Guinea worm eradication programmes.
Some medical officers cited that the funds provided for the programme are not adequate.
While 55 per cent of the households possess radio, and 30 per cent of the rural
households and more than 80 per cent of the urban households were having television.
About 45 per cent of the respondents read news paper. Television and health workers
were the important source of health messages. The details on development,
implementation and evaluation of the effectiveness of advocacy campaign are being
studied.
Control
In communities endemic for lymphatic filariasis, the disfiguring and debilitating
clinical manifestations result in much suffering and have severe socioeconomic and
psychological consequences for those affected. The objective of control is to reduce
trans- mission and morbidity, thereby eliminating lymphatic filariasis as a public health
problem. Successful programmes for the control of lymphatic filariasis must be based on
a thorough understanding of the distribution and dynamics of the disease in the targeted
population. The diverse characteristics of communities in endemic foci, as well as
differences in vector, parasite and disease parameters, emphasize the importance of
having multiple measures and approaches for control.
The main method used in the control of lymphatic filariasis is mass
chemotherapy. It may be supplemented by mosquito control. Morbidity control through
patient management (hygiene, antimicrobial treatment, physiotherapy) and establishment
of self-help groups is recommended. To achieve success in a control programme it is
necessary for the community to be actively involved. Community leaders and motivated
persons should be identified and approached for the purpose of obtaining their
cooperation. Adequate health education should be given regarding the nature of the
disease and on the methods used for its control.
Before starting a control programme, knowledge of the geographical
delimitation of the disease is essential. Rapid assessment procedures are based on
examination of specific age-sex groups in selected populations to determine the
prevalence of easily recognizable signs such as hydrocele or circulating antigenaemia
Geographical information system (GIS) has been utilized for large- scale mapping of the
disease. All areas with indigenously acquired infections are considered to be endemic.
Criteria for distinguishing different levels of endemicity have so far not been established.
Mathematical models of lymphatic filariasis transmission, infection and disease
within the endemic community have been developed. It is envisaged that such models can
be used to predict the outcome of control based on different measures, and thus can
provide guidance towards the most cost effective control strategies in specific settings.
Elimination
Lymphatic filariasis (also called elephantiasis) is one of the diseases being
controlled through integrated programmes it is also treated with ivermectin but it has
already been successfully eliminated from China, Korea and ten African countries.
Elimination means stopping transmission in a particular territory.
Elimination of lymphatic filariasis in certain countries has been possible because
ivermectin is so effective, but there are other factors working in our favour, according to
Bockarie: “The drug is very good, tools for diagnosis are very good. There is no natural
reservoir for the parasite, so if you can eliminate it from humans, it is gone. If you reduce
the parasite load in the community to less than 1 in 1000, transmission is impossible.”
Like onchocerciasis, lymphatic filariasis is caused by thread like nematode
worms, although the worms that cause lymphatic filariasis are transmitted by mosquitoes
rather than blackflies. Infection leads to thickening of the skin and other tissues, and
massive swelling, particularly of the legs and male genitals. Of course, there are still
many people with lymphatic filariasis in the countries where transmission has been
successfully interrupted it will take many more years for the signs of the disease to
disappear.
Since OCP ended, strategies for onchocerciasis have also moved more towards
elimination in certain countries. These were prompted, says Bockarie, by the recent
upsurge in interest in NTDs generally. “We have the resources to monitor and evaluate
progress and there is a bigger workforce available which means we can put in place
protocols for effective monitoring.”
Although onchocerciasis and lymphatic filariasis are treated with the same drug, it
will not be simple to eliminate both diseases in all countries. “One of the biggest
challenges is co-infection,” says Bockarie. “We can control onchocerciasis and lymphatic
filariasis with existing tools but only in certain settings.”
One problem is another parasite called Loa loa, which is also sensitive to
ivermectin. Unfortunately, in patients with large numbers of Loa loa parasites in their
bodies, treatment with ivermectin can cause serious, potentially fatal, effects when dead
Loa loa worms enter the bloodstream. So ivermectin cannot be used to treat
onchocerciasis or lymphatic filariasis where Loa loa infections are also prevalent. This
does not mean, however, that we have to give up.
“Different strategies are being developed,” says Bockarie, “such as more refined,
higher resolution mapping.” Knowing precisely where the diseases are endemic is vital to
using resources in the most efficient and effective way. The standard approach for
onchocerciasis and lymphatic filariasis has been to go to a district and sample the people.
If more than 1 per cent is infected, the whole district is classed as endemic and is eligible
for treatment. This does not work in areas with Loa loa mapping has to be done at the
village level if the status of all three infections is to be accurately determined and the
right strategy implemented.
In areas with co-infection of Loa loa, the drug albendazole can be used first to
reduce the levels of Loa loa infection in order to dampen the adverse effects of treatment
with ivermectin that follows. Of course, as with the early days of OCP, control and
elimination efforts do not have to focus on drugs. Other approaches include using
antibiotics to kill Wolbachia, a bacterium that lives in lymphatic filariasis and
onchocerciasis parasites but not in Loa loa. The parasites are dependent on Wolbachia, so
killing the bacterium kills the parasites. However, there are other issues with using
antibiotics: treatment is over one or two weeks rather than in a single annual dose as with
the antiparasitic drugs, which makes it harder to ensure people get the full course of
treatment. Targeting the insects that transmit the parasites – the flies that carry Loa loa, or
the mosquitoes that transmit the worms that cause lymphatic filariasis is called vector
control, and it is an approach that Bockarie has been championing for years: “What
pushed me into public health and advocacy,” he explains, “was that vector control was
being ignored. The lymphatic filariasis control programme had two main objectives:
drugs to reduce infection in humans, and reduce or manage morbidity. Vector control was
missing. When the lymphatic filariasis programme was developing, there was no space to
talk about mosquitoes.”
Bockarie’s early training was in medical entomology the use of scientific
knowledge about insects to understand and address human disease. He began studying
malaria but mosquitoes that transmit malaria also transmit lymphatic filariasis and other
NTDs, although this sometimes seems to get overlooked: “In the last two to three years,
we’ve seen the impact of [insecticide treated] bed nets on malaria,” he says. “But we
know bed nets would impact on lymphatic filariasis as much as, if not more than, malaria
what’s happening in lymphatic filariasis?”
While the integrated efforts to control and eliminate various NTDs are growing, it
seems there is a need to integrate them further with efforts against the big three infectious
diseases – malaria, tuberculosis and HIV/AIDS – as well.
Eradication
Eradication can be simply defined as global elimination. It was achieved in the
20th century with smallpox and we may be close to eradicating a second disease in the
form of dracunculiasis, or Guinea worm disease. How? “Stop people drinking infected
water,” says Bockarie. “It’ll completely eradicate it, get rid of the parasite completely.” It
sounds simple, although as dracunculiasis is another neglected tropical disease, simple
doesn’t necessarily mean easy, but the WHO has set a firm target in its NTDs roadmap to
eradicate dracunculiasis by 2015.
Professor David Molyneux, acting chair of the UK Coalition against NTDs and
one of the scientists who introduced the term ‘neglected tropical diseases’, has
described progress on dracunculiasis so far as remarkable: “The total number of cases has
declined from well over three million in the late 1980s to only 1060 reported in 2011.
The end is in sight. What is remarkable is that this has been done without a drug
or a vaccine. Applying basic public health principles health education, case containment,
surveillance, water filtration and enhanced access to safe water has been critical.
“Success is in sight but as always, the cost remains as we travel down the final
mile and need to identify the last infected villages and isolate final cases.”
The Carter Center has been a particularly strong advocate for action against
dracunculiasis over the past 25 years and will play a role along with a number of funders
including the UK Department for International Development and the Gates
Foundation in achieving the 2015 eradication target. Another NTD called yaws is set for
eradication by 2020 but for the other NTDs, control and national or regional elimination
strategies remain crucial.
In the present study an attempt has been made to create a Geographical
Information Base (GIB) for the filariasis disease cases from 1998 – 2008 with the
attached data bases. The maps designed for five years clearly indicate the presence of
filarial disease and also we can infer that how the awareness among the people of
Kumbakonam has been increased towards the disease by which in a single family more
than two cases were identified.
The locational data base can be updated after gathering the relevant other
information and with the GIB, Geographical analysis can be performed. The existing
pattern of the disease clearly shows that from 1998 to the present the infected cases were
surfaced and being treated. According to the health personal, the Government has
planned to eradicate the disease before 2020. From the factor analysis for the 32
variables were grouped into five major factors namely: Environmental quality of life,
Perception about the Environment, Stages of Filariasis and Medical Treatment, Health
care Towards the Disease, and Psychological Attitudes and Awareness contributed nearly
40 per cent. According to the primary survey analysis, to eliminate the disease the above
five areas have to be concentrated spatially.
References
1. A Krishna Kumari, KT Harichandrakumar, KL Das, K Krishnamoorthy. Physical and psychosocial burden due to lymphatic fialriasis as perceived by patients and medical experts. Trop Med Int Health 2005; 10: 567-73.
2. Ahorlu CK, Dunyo SK, Simonsen PE. Scarification as a risk factor for rapid progression of filarial elephantiasis. In: Lymphatic filariasis research and control in Africa. Report on a workshop held in Tanga, Tanzania. Tanzania: Danish Bilharziasis Laboratory, Denmark & National Institute for Medical Research; 1997.
3. Amat-Roze JM: Geographic inequalities in HIV infection and AIDS in sub-Saharan Africa. Soc Sci Med 1993, 36:1247-56.
4. Amazigo UO, Obikeze DS. Social consequences of onchocercal skin lesions on adolescent girls in rural Nigeria. WHO/TDR Discussion Paper. Geneva: WHO;1992.
5. Anderson J, Maclean M, Davies C: Malaria research. An audit of international activity. London: Wellcome Trust Publishing 1st edition. 1996.
6. Annual Report, Vector Control Research Centre, Pondicherry. p18, 1998.
7. Annual Report, Vector Control Research Centre, Pondicherry. p23, 2000.
8. Appavoo, N.C., Pani S.P. and Das, P.K. The Science and Art of Lymphatic Filariasis Elimination in India: Hope for the Next Millennium. Department of Public Health and Preventive Medicine, Government of Tamil Nadu and Vector Control Research Centre, Pondicherry, p.1, 1999.
9. B Carme, A Utahia, E Tuira, T Teuru. Filarial elephantiasis in French Polynesia: a study concerning the beliefs of 127 patients about the origins of their disease. Trans R Soc Trop Med Hyg 1979; 73: 424-6.
10. B Haliza, R Mohd. Comparison of knowledge on filariasis and epidemiological factors between infected and uninfected respondents in a Malay community. Southeast Asian J Trop Med Public Health 1986; 17: 457-64.
11. B Nanda, K Krishnamoorthy. Treatment seeking behaviour and costs due to acute and chronic forms of lymphatic filariasis in urban areas in south India. Trop Med Int Health 2003; 8: 56-9.
12. Babu BU, Kar SK (2004) Coverage, compliance and some operational issues of mass drug administration during the programme to eliminate lymphatic filariasis in Orissa, India. Trop Med Int Health 9:702–709.
13. Bagayoko M, Clarke GP, Craig M, Le Sueur D: A spatial statistical approach to malaria mapping. Int J Epidemiol 2000, 29:355-61.
14. Balakrishnan, N., Ramaiah, et. al., Efficacy of biannual administration of DEC in the control of bancroftian filariasis. J Commun Dis 24: 87, 1992.
15. Baruah K, Rai RN (2000), The impact of housing structures on filarial infection. Jpn J Infect Dis 53: 107–110.
16. Beyers N, Gie RP, et al.: The use of a geographical information system (GIS) to evaluate the distribution of tuberculosis in a high-incidence community. S Afr Med J 1996, 86:40-1.
17. Booman M, et al. Using a geographical information system to plan a malaria control programme in South Africa. Bull World Health Organ 2000, 78:1438-44.
18. Braga C, Ximenes RA, Albuquerque M, Souza WV, et al. (2001) Evaluation of a social and environmental indicator used in the identification of lymphatic filariasis transmission in urban centers. Cad Saúde Pública 17: 1211–1218.
19. Briggs DJ, Elliott P: The use of geographical information systems in studies on environment and health. World Health Stat Q 1995, 48:85-94.
20. Building partnerships for lymphatic filariasis strategic plan. Geneva: WHO; 1999.
21. BV Babu, K Satyanarayana. Factors responsible for coverage and compliance in mass drug administration during the programme to eliminate lymphatic filariasis in the East Godavari District, South India. Trop Doct 2003; 33: 79-82.
22. C Witt, EA Ottesen. Lymphatic filariasis: an infection of childhood. Trop Med Int Health 2001; 6: 582-606.
23. Carme B (1979) Filarial elephantiasis in French Polynesia: A study concerning the beliefs of 127 patients about the origin of their disease. Trans R Soc Trop Med Hyg 73: 424–426.
24. Chadee DD, Williams SA, Ottesen EA (2002) Xenomonitoring of Culex quinquefasciatus mosquitoes as a guide for detecting the presence or absence of lymphatic filariasis: a preliminary protocol for mosquito sampling. Ann Trop Med Parasitol 96: 47–53.
25. Chan, M.S., Srividya, et al.: A Dyanamic model of infection and diseases in lymphatic filariasis. Am J Trop Med Hyg 59: 606, 1998.
26. Charlwood JD, Bryan JH: A mark-recapture experiment with the filariasis vector Anopheles punctulatus in Papua New Guinea. Ann Trop Med Parasitol 1987, 81:429-36.
27. Clarke KC, McLafferty SL, Tempalski BJ, On epidemiology and geographic information systems: a review and discussion of future directions. Emerg Infect Dis 1996, 2:85-92.
28. Coetzee M, Craig M, le Sueur D: Distribution of African malaria mosquitoes belonging to the Anopheles gambiae complex. Parasitol Today 2000, 16:74-7.
29. Cox FEG (2000) Elimination of lymphatic filariasis as a public health problem. Parasitol Today 16(4):135.
30. Craig MH, Snow RW, le Sueur D: A climate-based distribution model of malaria transmission in sub- Saharan Africa. Parasitol Today 1999, 15:105-11.
31. Das PK, Manoharan A, Subramanian et al. (1992) Bancroftian filariasis in Pondicherry, South India: epidemiological impact of recovery of vector population. Epidemiol Infect 108:483–493.
32. Das, P. K., Manoharan, et al. filariasis in Pondicherry, south India Epidemiological impact of recovery of the vector population. Epidemiol Infect 108: 483, 1992.
33. Das, P.K, Ramaiah, K.D., Vanamail, P., Pani, S.P., Yuvaraj, J., Balaraman, K. and Bundy, D.A.P. Placebo controlled community trial of four cycles of single dose diethyl carbamazine or ivermectin against Wuchereria bancrofti infection and transmission in India. Trans R Soc Trop Med Hyg 95: 336, 2001.
34. Das, P.K. and Pani, S.P. Filariasis in India; Epidemiology and control In: Helminthology in India Ed. M.L.Sood. International Book Distributors, Dehra Dun, 2002.
35. Das, P.K. and Pani, S.P. Towards elimination of lymphatic filariasis in India: Problems, challenges, opportunities and new initiatives. J Int Med Sci Acad 13: 18, 2000.
36. Das, P.K., Manoharan, et al. V. Cost-analysis of blood-surveys for the detection of microfilaria carriers in rural areas. Nat Med J India 8: 143, 1995.
37. Das,P.K,Sivagnaname,N.andAmalraj,D.Acomparativestudy of a new insecticide impregnated fabric trap for monitoring adult mosquito populations resting indoors. Bull Entomol Res 87: 397, 1997.
38. DB Evans, H Gelband, C Vlassoff. Social and economic factors and the control of lymphatic filariasis: a review. Acta Trop 1993; 53: 1-26.
39. De Albuquerque Mde F (1993) Urbanization, slums, and endemics: the production of filariasis in Recife, Brazil. Cad Saúde Pública 9: 487–497.
40. De Albuquerque Mde F, et al. (1995) Bancroftian filariasis in two urban areas of Recife, Brasil: the role of individual risk factors. Rev Inst Med trop S Paulo 37: 224–233.
41. DeichmannU: Africa population database http://grid2.cr.usgs.gov/globalpop/africa National Centre for Geographic Information and Analysis and United Nations Environment Programme, World Resources Institute 1996.
42. DH Molyneux, PJ Hotez, A Fenwick. “Rapid-impact interventions”: how a policy of integrated control for Africa’s neglected tropical diseases could benefit the poor. PLoS Med 2005; 2: e336.
43. DoiMoore DA, Carpenter TE: Spatial analytical methods and geographic information systems: use in health research and epidemiology. Epidemiol Rev 1999, 21:143-61.
44. Dunn C, Atkins P, Townsend J: GIS for development: a contradiction in terms? Area 1997, 29:151-159.
45. Durrheim DN, Wynd S, Liese B, Gyapong JO (2004) Lymphatic filariasis endemicity - an indicator of poverty?. Trop Med Int Health 9: 843–845.
46. EA Ottesen, BOL Duke, M Karam, K Behbehani. Strategies and tools for the control/elimination of lymphatic filariasis. Bull World Health Organ 1997; 75: 491-503.
47. EA Ottesen. The global programme to eliminate lymphatic filariasis. Trop Med Int Health 2000; 5: 591-4.
48. Elango, A., Paily, K.P., Pani, S.P., Yuvaraj, J. and Anand Paul Kumar, M.P.Histopathologyandimmunopathologyofskinofdifferentgrades of lymphoedema (W. bancrofti) in south India. Prog lymphol 17: 162, 2000.29.
49. El-Setouhy MA, Rio F (2003) Stigma reduction and improved knowledge and attitudes towards filariasis using a comic book for children. J Egypt Soc Parasitol 33:55–65.
50. Erlanger TE, Keiser J, Caldas De Castro M, Bos R, Singer BH, et al. (2005) Effect of water resource development and management on lymphatic filariasis, and estimates of populations at risk. Am J Trop Med Hyg 73: 523–533.
51. Esterre P, Plichart C, Sechan Y, Nguyen NL (2001) The impact of 34 years of massive DEC chemotherapy on Wuchereria ban- crofti infection and transmission: the Maupiti cohort. Trop Med Int Health 6:190–195.
52. FL Dunn. Behavioural aspects of the control of parasitic diseases. Bull World Health Organ 1979; 57: 499-506.
53. G Dreyer, J Noroes, D Addiss. The silent burden of sexual disability associated with lymphatic filariasis. Acta Trop 1997; 63: 57-60.
54. G Dreyer, Z Medeiros, MJ Netto, NC Leal, L Gonzaga de Castro, WF Piessens. Acute attacks in the extremities of persons living in an area endemic for Bancroftian filariasis: differentiation of two syndromes. Trans R Soc Trop Med Hyg 1999; 93: 413-7.
55. Galvez Tan JZ (2003) The elimination of lymphatic filariasis: a strategy for poverty alleviation and sustainable development-perspectives from the Philippines. Filaria Journal 2: 12.
56. Gbakima AA, Appawu MA, Dadzie S, Karikari C, Sackey SO, et al. (2005) Lymphatic filariasis in Ghana: establishing the potential for an urban cycle of transmission. Trop Med Int Health 10: 387–392.
57. Gesler W: The uses of spatial analysis in medical geography: a review. Soc Sci Med 1986, 23:963-73.
58. Golub A, Gorr WL, gould PR: Spatial diffusion of the HIV/AIDS epidemic: modelling implications and case study of the AIDS incidence in Ohio. Geogr Anal 1993, 25:85-100.
59. Goodchild M: Geographical information science. Int J GIS 1992, 6:31-45.
60. Gould P: The slow plague: a geography of the AIDS pandemic. Cambridge, Massachusetts: Blackwe 1993.
61. Gunasekaran, K., Padmanaban, V. and Balaraman, K. Development of Wuchereria bancrofti in Culex quinquefasciatus that survived the exposure of sub-lethal dose of Bacillus sphaericus as larvae. Acta Trop 74: 43, 2000.
62. GW Schultz. A study of Bancroftian filariasis on the islands of Bataan and Rapu, Philippines. Southeast Asian J Trop Med Public Health 1988; 19: 207-14.
63. Gyapong, J.O., Omane-Badu, K. and Webber, R.H. Evaluation of the filter paper blood collection method for detecting Og4C3 circulating antigen in bancroftian filariasis. Trans R Soc Trop Med Hyg 92: 407, 1998.
64. H Williams, C Jones, M Alilio, et al. The contribution of social science research to malaria prevention and control. Bull World Health Organ 2002; 80: 251-2.
65. HA Williams, COH Jones. A critical review of behavioural issues related to malaria control in sub-Saharan Africa: what contributions have social scientists made? Soc Sci Med 2004; 59: 501-23.
66. Hastings D, Clarke D: GIS in Africa: problems, challenges and opportunities for co-operation. IJ GIS 1991, 5:29-39.
67. Hay SI, Cox J, Rogers DJ, Randolph SE, Stern DI, Shanks GD, Myers MF, Snow RW: Climate change and the resurgence of malaria in the East African highlands. Nature 2002, 415:905-9.
68. Hay SI, Randolph SE, Rogers DJ: Remote sensing and geographical information systems in epidemiology. London: Academic Press 2000.
69. Hay SI, Snow RW, Rogers DJ: Predicting malaria seasons in Kenya using multitemporal meteorological satellite sensor data. Trans R Soc Trop Med Hyg 1998, 92:12-20.
70. Hightower AW, Ombok M, Otieno R, Odhiambo R, Oloo AJ, Lal AA, Nahlen BL, Hawley WA: A geographic information system applied to a malaria field study in western Kenya. Am J Trop Med Hyg 1998, 58:266-72.
71. Hill ND: Creating social borders from the WASAP data sets. Calverton, Maryland: Macro International 1998.
72. Holland P, Reichardt ME, Nebert D, Blake S, Robertson D: The global spatial data infrastructure initiative and its relationship to the vision of a digital earth. In: International Symposium on Digital Earth; Beijing, China 1999.
73. Hoti, S. L., Vasuki, V., Patra, K.P., Hariths, V.R., Ravi, G. and Sushma, S. Laboratory evaluation of Ssp I PCR assay for the detection of Wuchereria bancrofti infection in Culex quinquefasciatus. Indian J Med Res 114: 59, 2001.
74. Hoti, S. L., Vasuki, V.,Lizotte, M.W., et al., Detection of Brugia malayi in laboratory and wild-caught Mansonoides mosquitoes (Diptera: Culicidae) using Hha I PCR assay. Bull Entomol Res 91: 87, 2001.
75. Hoyle RH, Smith GT (1994) Formulating clinical research hypotheses as structural equation models: a conceptual overview. J Consult Clin Psychol 62:429–440.
76. Hutchinson CF, Todedano J: Guidelines for demonstrating geographical information systems based on participatory development. IJGIS 1993, 7:453-461.
77. Hutchinson MF, Nix HA, McMahan JP, Ord KD: Africa – A topographic and climatic database, CD-ROM (1): Centre for Resource and Environmental Studies, Australian National University 1995.
78. ICMR (2001) Impact of environmental changes on vector population in an urban situation. ICMR bulletin 31. http://www.icmr.nic.in/buoct01.pdf. Accessed on 18 February 2011.
79. INDEPTH: Population, Health and Survival at INDEPTH Sites. In: Population and Health in Developing Countries, vol. 1. Ottawa Canada: IDRC 2002, 356pp.
80. Institute for Development Studies. Mobilising social science research to improve health. Policy Briefing 2005:Issue 25.
81. IP Sunish, R Rajendran, TR Mani, A Munirathinam, SC Tewari, J Hiriyan, et al. Resurgence in filarial transmission after withdrawal of mass drug administration and the relationship between antigenaemia and microfilaraemia - a longitudinal study. Trop Med Int Health 2002; 7: 59-69.
82. J Coreil, G Mayard, J Louis-Charles, D Addiss. Filarial elephantiasis among Haitian women: social context and behavioural factors in treatment. Trop Med Int Health 1998; 3: 467-73.
83. JF Kessel. Disabling effects and control of filariasis. Am J Trop Med Hyg 1957; 6: 402-14.
84. JHF Remme, P Raadt, T Godal. The burden of tropical disease. Med J Aust 1993; 158: 465.
85. JM Hunter. Elephantiasis: a disease of development in north-east Ghana. Soc Sci Med 1992; 35: 627-49.
86. Joreskog KG (1973) A general method of estimating a linear equation system. In: Goldberger AS, Duncan OD (eds) Structural equation models in the social sciences. Seminar Press, New York, pp 85– 112.
87. Joreskog KG, Sorbom D (1978) LISREL IV: analysis of linear structural relations by the method of maximum likelihood. National Educational Resources, Chicago.
88. Joreskog KG, Sorbom D (1984) LISREL VI: analysis of linear structural relationships by maximum likelihood, instrumental variables, and least square methods, 3rd edn. Scientific Software, Mooresville. ISBN 0-8949-8024-6.
89. JW Mak. Problems in filariasis control and the need for human behaviour and socio-economic research. Southeast Asian J Trop Med Public Health 1986; 17: 479-85.
90. Kahn HA, Sempos CT (1989) Sample size calculation using odds ratio. Statistical methods in epidemiology. Oxford University Press, New York, pp 64–71.
91. Kalipeni E: Health and disease in southern Africa: a comparative and vulnerability perspective. Soc Sci Med 2000, 50:965-83.
92. KD Ramaiah, KN Vijay Kumar, K Ramu. Knowledge and beliefs about transmission, prevention and control of lymphatic filariasis in rural areas of South India. Trop Med Int Health 1996; 1: 433-8.
93. Kearns RA: AIDS and medical geography: embracing the other? Progr hum geogr 1996, 20:123-131.
94. Killewo J, Dahlgren L, Sandstrom A: Socio-geographical patterns of HIV-1 transmission in Kagera Region, Tanzania. Soc Sci Med 1994, 38:129-34.
95. Kloos H, Zein ZA: The ecology of health and disease in Ethiopia. Boulder, Colarado: Westveiw Press 1993.
96. Korte G: Weighing GIS benefits with financial analysis. Government Finance Review 1996, 12:48-52.
97. Kreuels B, Kobbe R, Adjei S, Kreuzberg C, Von Reden C, et al. (2008) Spatial variation of Malaria incidences in young children from a geographically homogeneous area with high endemicity. J Infect Dis 197: 85–93.
98. Krishna S: Science, medicine, and the future. Malaria. Bmj 1997, 315:730-2.
99. Kurmaraswami, V., Ottesen, et al. Ivermectin for the treatment of Wuchereria bancrofti filariasis: Efficacy and side reactions. J Am Med Assoc 259: 3150, 1988.
100. L Bandyopadhyay. Lymphatic filariasis and the women of India. Soc Sci Med
1996; 42: 1401-10.
101. Lakshmi, A. A statistical approach to monitor ongoing intervention for control of lymphatic filariasis. J Commun Dis 32: 10, 2000.
102. Lee SYD, Arozullah Ahsan M, Young ChoIk (2004) Health literacy, social support, and health: a research agenda. Social Science & Medicine 58: 1309–1321.
103. Lenhart A, Rakers L, et al. (2005) Significant decrease in the prevalence of Wuchereria bancrofti infection in anopheline mosquitoes following the addition of albendazole to annual, ivermectin-based, mass treatments in Nigeria. Ann Trop Med Parasitol 99(2):155–164.
104. Lindsay SW, Martens WJ: Malaria in the African highlands: past, present and future. Bull World Health Organ 1998, 76:33-45.
105. LL Belgrave, D Zablotsky, MA Guadagmo. How do we talk to each other? Writing qualitative research for quantitative health researchers. Qual Health Res 2002; 2: 1427-39.
106. Loslier L: Geographical information systems (GIS) from a health perspective. In GIS for health and the environment. Edited by De Savigny D, Wijeyaratne P. Ottawa: IDRC; 1994:13-20.
107. Low-Beer D, Stoneburner RL, Mukulu A: Empirical evidence for the severe but localized impact of AIDS on population structure. Nat Med 1997, 3:553-7.
108. Loyotonnen M: The spatial diffusion of the human immunodeficiency virus type 1 in Finland, 1982–1987. Ann Assoc Am Geogr 1991, 81:127-51.
109. Lu AG, Valencia LB, Llagas L (1988) Filariasis: A study of knowledge, attitudes and practices of the people of Sorsgon. Social and Economic Research Project Reports No. I, TDR/SER/PRS/1 WHO, Geneva.
110. Lu AG, Valencia LB, Llagas L, Aballa L, Postrado L. Filariasis: a study of knowledge, attitudes and practices of the people of Sorsogon. Social and Economic Research Project Reports No.1. Geneva: WHO; 1998.
111. Lymphatic filariasis: infection and disease. Control strategies. Report of a consultative meeting held at the University Sains Malaysia, Penang. Geneva: WHO; 1994.
112. Lymphatic filariasis: the disease and its control. Fifth report of the WHO expert committee on filariasis. Geneva: WHO; 2002.
113. M Gyapong, J Gyapong, M Weiss, M Tanner. The burden of hydrocele on men in Northern Ghana. Acta Trop 2000; 77: 287-94.
114. M Gyapong, JO Gyapong, G Owusu-Banalene. Community-directed treatment:
the way forward to eliminating lymphatic filariasis as a public health problem in Ghana. Ann Trop Med Parasitol 2001; 95: 77-86.
115. M Gyapong, JO Gyapong, S Adjei, C Vlassoff, M Weiss. Filariasis in Northern Ghana: some cultural beliefs and practices and their implication for disease control. Soc Sci Med 1996; 43: 235-42.
116. Manoharan A, Das PK, Keerthiseelan VB, Ramaiah KD (1997) Trend in Wuchereria bancrofti infection in Pondicherry urban agglom- eration after withdrawal of a five-year vector control programme. J Commun Dis 29:255–261.
117. MARA: Towards an Atlas of malaria risk in Africa: First technical report of the MARA/ARMA collaboration. Durban 1998.
118. Marsh K, Snow RW: Malaria transmission and morbidity. Parassitologia 1999, 41:241-6.
119. Marshal R: A review of methods for the statistical analysis of spatial patterns of disease. J R Statist Soc A 1991, 154:421-441.
120. Martin C, Curtis B, Fraser C, Sharp B: The use of a GIS-based malaria information system for malaria research and control in South Africa. Health Place 2002, 8:227-36.
121. Mathieu E, Lammie PJ, Radday J, Beach MJ, Streit T, Wendt J, Addiss DG (2004) Factors associated with participation in a campaign of mass treatment against lymphatic filariasis, in Leogane, Haiti. Ann Trop Med Parasitol 98:703–714.
122. Mayer JD: The role of spatial analysis and geographic data in the detection of disease causation. Soc Sci Med 1983, 17:1213-21.
123. Michael E, Bundy DA, Grenfell BT (1996) Reassessing the global prevalence and distribution of lymphatic filariasis. Parasitology 112: 409–428.
124. Minakawa N, Mutero CM, Githure JI, Beier JC, Yan G: Spatial distribution and habitat characterization of anopheline mosquito larvae in Western Kenya. Am J Trop Med Hyg 1999, 61:1010-6.
125. Molyneux DH (2003) Lymphatic filariasis (elephantiasis) elimination: a public health success and development opportunity. Filaria Journal 2: 13.
126. Molyneux DH, Hotez PJ, Fenwick A (2005) “Rapid-impact interventions”: how a policy of integrated control for Africa's neglected tropical diseases could benefit the poor. PLoS Med 2: e336.
127. Muhondwa EPY (1983) Community participation in filariasis control: The Tanzania experiment. TDR/SER/SWG (4)/WP/83.13, WHO, Geneva.
128. Mujinja PGM, Gasarasi DB, Premji ZG, Nguma J. Social and economic impact of lymphatic filariasis in Rufiji district, Southeast Tanzania. In: Lymphatic filariasis research and control in Africa. Report on a workshop held in Tanga, Tanzania.
Tanzania: Danish Bilharziasis Laboratory, Denmark & National Institute for Medical Research; 1997.
129. Murray CJ, Lopez AD: Mortality by cause for eight regions of the world: Global Burden of Disease Study. Lancet 1997, 349:1269-76.
130. Murty US, Praveen B, Kumar DV, Sriram K, Rao KM, et al. (2004) A Baseline Study on rural Bancroftian Filariasis in Southern India. Southeast Asian J Trop Med Public Health 35: 583–586.
131. Murty US, Rao MS, Sriram K, Rao KM (2010) Assessment of microfilaria prevalence in Karimnagar and Chittoor Districts of Andhra Pradesh, India. Asian Pacific Journal of Tropical Medicine 3: 647–650.
132. Mwobobia IK, Mitsui Y (1999) Demographic and socio-economic factors with implications for the control of lymphatic filariasis in Kwale District, Kenya. East Afr Med J 76: 495–498.
133. Nchinda TC: Malaria: a reemerging disease in Africa. Emerg Infect Dis 1998, 4:398-403.
134. Neglected tropical diseases: hidden successes, emerging opportunities. Geneva: WHO; 2006.
135. Nijkamp P, De Jong W: Training needs in information systems for local and regional development. Regional Development Dialogue 1987, 8:72-119.
136. Norman, R.A., Chan, M.S., Srividya, A., Pani, S.P., Ramaiah, K.D.,Vanamail, P., Michael, E., Das, P.K. and Bundy, D.A.P. EPIFIL: The development of an age-structured model for describing the transmission and control of lymphatic filariasis. Epidemiol Infect 124: 529, 2000.
137. Rauyajin, B Kamthornwachara, P Yablo. Socio-cultural and behavioural aspects of mosquito-borne lymphatic filariasis in Thailand: a qualitative analysis. Soc Sci Med 1995; 41: 1705-13.
138. Omumbo J, Ouma J, Rapuoda B, Craig MH, le Sueur D, Snow RW: Mapping malaria transmission intensity using geographical information systems (GIS): an example from Kenya. Ann Trop Med Parasitol 1998, 92:7-21.
139. Ottesen EA (2000) The global programme to eliminate lymphatic filariasis. Trop Med Int Health 5:591–594
140. Ottesen EA (2006) Lymphatic filariasis: Treatment, control and elimination. Adv Parasitol 61: 395–441.
141. Ottesen EA, Duke BO, Karam M, Behbehani K (1997) Strategies and tools for the control/elimination of lymphatic filariasis. Bull World Health Organ 75: 491–503.
142. P Esterre, C Plichart, Y Sechan, NL Nguyen. The impact of 34 years of massive DEC chemotherapy on Wuchereria bancrofti infection and transmission: the Maupiti cohort. Trop Med Int Health 2001; 6: 190-5.
143. P. Vanamail, S. Gunasekaran, Joreskog KG (1977) Structural equation models in the social sciences. Specification, estimation, and testing. In: Krishnaiah PR (ed) Application of statistics. North-Holland, Amsterdam, pp 265– 287
144. Pani, S. P., Balakrishnan, N., Srividya, A., Bundy, D.A.P. and Grenfell, B.T. Clinical epidemiology of bancroftian filariasis: Effect of age and gender. Trans R Soc Trop Med Hyg 85: 260, 1991.
145. Pani, S. P., Hoti, S.L., Elango, A.,Yuvaraj, J., Lall, R. and Ramaiah K.D. Evaluation of the ICT whole blood antigen card test to detect infection due to nocturnally periodic Wuchereria bancrofti in south India. Trop Med Int Health 5: 359, 2000.
146. Pani, S.P. and Lall, R. Clinical features, pathogenesis and management of lymphatic filariasis. ICMR Bull 28: 41, 1998.
147. Pani, S.P. and Srividya , A. Clinical manifestations of bancroftian filariasis, with special reference to lymphoedema grading: Indian J Med Res 102: 114, 1995.
148. Pani, S.P., et al. Episodic adenolymphangitis and lymphoedema in patients with bancroftian filariasis. Trans R Soc Trop Med Hyg 89: 72,1995.
149. Panicker, K.N., Krishnamoorthy, K., Sabesan, S., Prathiba, J. and Abidha. Comparison of effects of mass annual and semiannual single dose therapy with DEC for the control of Malayan filariasis. Southeast Asian J Trop Med Public Health 22: 402, 1991.
150. Perera M, Whitehead M, Molyneux D, Weerasooriya M, Gunatilleke G (2007) Neglected Patients with a Neglected Disease? A Qualitative Study of Lymphatic Filariasis. PLoS Negl Trop Dis 1: e128.
151. Perry B, Gesler W: Physical access to primary health care in Andean Bolivia. Soc Sci Med 2000, 50:1177-88.
152. Plaisier, A.P., Subramanian, S., Das, P.K., Souza, W., Lapa, T., Furtado, A.F.F., Vander Ploeg, C.P.B.,Habbema, J.D.E. and Van Oortmarssen, G.J. The LYMFASIM stimulation programme for modeling lymphatic filariasis and its control. Methods Inf Med 37: 97, 1998.
153. Rajagopalan PK, Das PK, Subramanian S, Vanamail P, Ramaiah KD (1989) Bancroftian filariasis in Pondicherry, south India. 1. Pre- control epidemiological observations. Epidemiol Infect 103: 685–692.
154. Rajagopalan, P. K. and Das, P.K. What ails mosquito control programmes in India. Bull Sci 4: 14, 1988.May-June 2002 ICMR Bulletin.
155. Rajagopalan, P. K., Das, C.M.R.,Reddy C.B.S. and Somachary, N. et al.
Evaluation of integrated vector control measures on filariasis transmission in Pondicherry. Indian J Med Res 87: 434, 1988.
156. Ramaiah KD (2009) Lymphatic filariasis elimination programme in India: progress and challenges. Trends Parasitol 25: 7–8.
157. Ramaiah KD, Das PK, Michael E, Guyatt H (2000) The Economic Burden of Lymphatic Filariasis in India. Parasitol Today 16: 251–253.
158. Ramaiah KD, Ramu K, Guyatt H, Kumar KN, Pani SP (1998) Direct and indirect costs of the acute form of lymphatic filariasis to households in rural areas of Tamil Nadu, South India. Trop Med Int Health 3: 108–115.
159. Ramaiah KD, Vijay Kumar KN, Ravi R, Das PK (2005) Situation analysis in a large urban area of India, prior to launching a programme of mass drug administration to eliminate lymphatic filariasis. Ann Trop Med Parasitol 99:243–252.
160. Ramaiah, K.D. and Vijaya Kumar, K.N. Effect of lymphatic filariasis on school children. Acta Trop 76: 197, 2000.
161. Ramaiah, K.D., Das, P.K., Appavoo, N.C., Ramu, K., Augustin, D.J., Vijayakumar, K.N. and Chandrakala, A.V. A programme to eliminate lymphatic filariasis in Tamil Nadu, India: Compliance with annual single dose DEC mass treatment and some related operational aspects. Trop Med Int Health 5: 842, 2000.
162. Ramaiah, K.D., Guyatt, H., Ramu, K., Vanamail, P., Pani, S.P. and Das, P.K. Treatment costs and loss of work time to individuals with chronic lymphatic filariasis in rural communities in south India. Trop Med Int Health 4: 19, 1999.
163. Ramaiah, K.D., Ramu, K., Guyatt, H., Vijaya Kumar, K.N. and Pani, S.P.Directandindirectcostsoftheacuteformoflymphaticfilariasis to households in rural areas of Tamil Nadu, south India. Trop Med Int Health 3: 108, 1998.
164. Ramaiah, K.D., Ramu, K., Vijaya Kumar, K.N. and Guyatt, H. Epidemiology of acute filarial episodes caused by Wuchereria bancrofti infection in two rural villages in Tamil Nadu, south India. Trans R Soc Trop Med Hyg 90: 639, 1996.
165. Ramaiah, K.D., Vanamail, P., Pani, S.P. and Das, P.K. The effect of six rounds of single dose mass treatment with DEC and ivermectin on Wuchereria bancrofti infection and its implications for lymphatic filariasis elimination. Trop Med Int Health, 7:767, 2002.
166. Ramaiah, K.D., Vijaya Kumar, K.N., Ramu, K., Pani, S.P. and Das, P.K. Functional impairment caused by lymphatic filariasis in rural areas of South India. Trop Med Int Health 2: 832, 1997.
167. Ramaiah,K.D.,Das,P.K.,Michael,E.andGuyatt,H.TheEconomic burden of lymphatic filariasis in India. Parasitol Today 16: 251, 2000.
168. Ramu, K., Ramaiah, K.D., Guyatt, H. and Evans, D. Impact of lymphatic filariasis on the productivity of male weavers in a south Indian village. Trans R Soc Trop
Med Hyg 90: 669, 1996.
169. Rauyajin O, Kamthornwachara B, Yablo P (1995) Socio-cultural and behavioural aspects of mosquito-borne lymphatic filariasis in Thailand: a qualitative analysis. Soc Sci Med 41: 1705–1713.
170. Raviglione MC, Dye C, Schmidt S: Assessment of worldwide tuberculosis control. WHO Global Surveillance and Monitoring Project. Lancet 1997, 350:624-9.
171. Reddy, G.S., Venkatesvarlou, N., Das, P.K., Vanamail, P., Vijayan S. K. and Pani, S.P. Tolerability and efficacy of single dose diethylcarbamazine (DEC) or ivermectin in the clearance of Wuchereria bancrofti microfilaraemia at Pondicherry, south India. Trop Med Int Health 5: 779, 2000.
172. Remy G: Epidemiologic distribution of HIV2 human immunodeficiency virus infection in sub-Saharan Africa. Med Trop (Mars) 1993, 53:511-6.
173. Remy G: Geographic distribution of HIV-1 infection in Central Africa: remarkable discontinuities. Ann Soc Belg Med Trop 1993, 73:127-42.
174. Ribeiro JM, Seulu F, Abose T, Kidane G, Teklehaimanot A: Temporal and spatial distribution of anopheline mosquitos in an Ethiopian village: implications for malaria control strategies. Bull World Health Organ 1996, 74:299-305.
175. Richards FO Jr, Pam DD, Kal A, Gerlong GY, Onyeka J, Sambo Y, brahim B, Terranella A, Kumbak D, Dakul A,Riji HM (1986) Comparison of knowledge on filariasis and epidemiologic factors between infected and uninfected respondents in a malay community. Southeast Asian J Trop Med Public Health 17: 457–463.
176. Rogers DJ, Randolph SE, Snow RW, Hay SI: Satellite imagery in the study and forecast of malaria. Nature 2002, 415:710-5.
177. S Rifkin. Paradigms lost: toward a new understanding of community participation in health programmes. Acta Trop 1996; 61: 79-92.
178. Sabesan S, Raju HK, Srividya A, Das PK (2006) Delimitation of lymphatic filariasis transmission risk areas: a geo-environmental approach. Filaria Journal 5: 12.
179. Sabesan, S., Palaniyandi, M. and Das, P.K. Mapping of lymphatic filariasis. Ann Trop Med Parasitol 94: 591, 2000.
180. Sabesan, S., Pradeep Kumar, N., Krishnamoorthy, K. and Panicker, K.N. Seasonal abundance and biting behaviour of Mansonia annulifera, Mansonia uniformis and Mansonia indiana and their relative role in the transmission of Malayan filariasis in Shertallai (Kerala State). Indian J Med Res 93: 253, 1992.
181. Sasa, M. Human Filariasis: A Global Survey of Epidemiology and Control, University of Tokyo Press, Tokyo, p336, 1976.
182. Schellenberg JA, Newell JN, Snow RW, Mung'ala V, Marsh K, Smith PG, Hayes RJ: An analysis of the geographical distribution of severe malaria in children in
Kilifi District, Kenya. Int J Epidemiol 1998, 27:323-9.
183. Scholten HJ, de Lepper MJ: The benefits of the application of geographical information systems in public and environmental health. World Health Stat Q 1991, 44:160-70.
184. Seim AR, Dreyer G, Addiss DG (1999) Controlling morbidity and interrupting transmission: twin pillars of lymphatic filariasis elimination. Rev Soc Bras Med Trop 32: 325–328.
185. Shenoy, R.K., Sandhya, K., Suma, T.K. and Kumarasami, V. A preliminary study of filariasis related acute adenolymphangitis with special reference to precipitation factor and treatment modalities. Southeast Asian J Trop Med Public Health 26: 301, 1995.
186. Smith T, Charlwood JD, Takken W, Tanner M, Spiegelhalter DJ: Mapping the densities of malaria vectors within a single village. Acta Trop 1995, 59:1-18.
187. Snehalatha KS, Ramaiah KD, Vijay Kumar KN, Das PK (2003) The mosquito problem and type and costs of personal protection measures used in rural and urban communities in Pondicherry region, South India. Acta Tropica 88: 3–9.
188. Snow RW, Craig M, Deichmann U, Marsh K: Estimating mortality, morbidity and disability due to malaria among Africa's non-pregnant population. Bull World Health Organ 1999, 77:624-40.
189. Snow RW, Craig MH, Deichman U, Le Sueur D: A continental risk map for malaria mortality among African children. Parasitol Today 1999, 15:99-104.
190. Snow RW, Gouws E, Omumbo J, Rapuoda B, Craig MH, Tanser FC, le Sueur D, Ouma J: Models to predict the intensity of Plasmodium falciparum transmission: applications to the burden of disease in Kenya. Trans R Soc Trop Med Hyg 1998, 92:601-6.
191. Sokal DC, Buzingo T, Nitunga N, Kadende P, Standaert B: Geographic and temporal stability of HIV seroprevalence among pregnant women in Bujumbura, Burundi. Aids 1993, 7:1481-4.
192. Srividya, A., Lall, R., Ramaiah, K.D., Ramu, K., Hoti, S.L., Pani, S.P. and Das, P.K. Development of rapid assessment procedures for the delimitation of lymphatic filariasis endemic areas. Trop Med Int Health 5:64, 2000.
193. Srividya, A., Palaniyandi, M., Michael, E., Pani S.P. and Das, P.K. A geostatistical analysis of the geographical distribution of lymphatic filariasis prevalence in southern India. Am J Trop Med Hyg, 2002.
194. Stock R: Africa South of the Sahara: a geographic interpretation. New York: Guilford Press 1995.
195. Stolk WA, Ramaiah KD, Van Oortmarssen GJ, Das PK, Habbema JD, et al. (2004) Meta-analysis of age-prevalence patterns in lymphatic filariasis: no decline
in microfilaraemia prevalence in older age groups as predicted by models with acquired immunity. Parasitology 129: 605–612.
196. Streit T, Lafontant JG (2008) Eliminating lymphatic filariasis: a view from the field. Annals of the New York Academy of Sciences 1136: 53–63.
197. Subramanian S, Pani SP, Das PK, Rajagopalan PK (1989) Bancroftian filariasis in Pondicherry, South India: 2. Epidemiological evaluation of the effect of vector control. Epidemiol Infect 103:693–702
198. Subramanian, S., Pani, S.P., Das, P.K. and Rajagopalan, P.K. Bancroftian filariasis in Pondicherry, south India: II. Epidemiological evaluation of the effect of vector control. Epidemiol Infect 103: 693, 1989.
199. Subramaniyam, R. G. and Venkatesvarlou, N. Mass administration of DEC medicated salt for filariasis control in the endemic population of Karaikal, south India: Implementation and impact assessment. Bull World Health Organ 74: 85, 1996.
200. Subramaniyam, R. G., Pani, S.P. and Das, P.K. Ivermectin: A new wonder drug for lymphatic filariasis, Clin Pharmacol Therapeut 18: 29, 1997.
201. Suma TK, Shenoy RK, Kumaraswami V (2003) A qualitative study of the perceptions, practices and socio-psychological suffering related to chronic brugian filariasis in Kerala, southern India. Ann Trop Med Parasitol 97:839–845.
202. Sunish IP, Rajendran R, Mani TR, Munirathinam A, Tewari SC, Hiriyan J, Gajanana A, Satyanarayana K (2002) Resurgence in filarial transmission after withdrawal of mass drug administra- tion and the relationship between antigenaemia and microfilaraemia—a longitudinal study. Trop Med Int Health 7:59–69.
203. Surendran K, Pani SP, Soudarssanane MB, Srinivasa DK, Bordolai PC, Subramanian S (1996) Natural history, trend of prevalence and spectrum of manifestations of Bancroftian filarial disease in Pondicherry (South India). Acta Trop 61:9–18.
204. Suresh, S., Kumaraswami, V., Suresh, I., Rajesh, K., Suguna, G., Vijayasekaran, V., Ruckmani, A. and Rajamanickam, M.G. Ultrasonographic diagnosis of subclinical filariasis. J Ultrasound Med 16: 45, 1997.
205. Tanser F, Hosegood V, Benzler J, Solarsh G: New approaches to spatially analyse primary health care usage patterns in rural South Africa. Trop Med Int Health 2001, 6:826-38.
206. Tanser FC, Le Sueur D, Solarsh G, Wilkinson D: HIV heterogeneity and proximity of homestead to roads in rural South Africa: an exploration using a geographical information system. Trop Med Int Health 2000, 5:40-46.
207. Tanser FC, Sharp B, le Sueur D: Malaria seasonality and the potential impact of climate change in Africa. Submitted for publication 2002.
208. Tanser FC, Wilkinson D: Spatial implications of the tuberculosis DOTS strategy in rural South Africa: a novel application of geographical information system and global positioning system technologies. Trop Med Int Health 1999, 4:634-8.
209. Tanser FC: The application of GIS technology to equitably distribute fieldworker workload in a large, rural South African health survey. Trop Med Int Health 2002, 7:80-90.
210. Taylor DRF: GIS and developing nations. In Geographical information systems. Volume 2. Edited by London: Longman. Maguire D, Goodchild M, Rhind D; 1991:71-84.
211. Testi A, Ivaldi W (2009) Material versus social deprivation and health: a case study of an urban area. Eur J Health Econ 10: 323–328.
212. Tewari, S.C., Hiriyan, J. and Reuben, R. Epidemiology of subperiodic Wuchereria bancrofti infection in Nicobar islands, India. Trans R Soc Trop Med Hyg 89: 163, 1995.
213. Thomas CJ, Lindsay SW: Local-scale variation in malaria infection amongst rural Gambian children estimated by satellite remote sensing. Trans R Soc Trop Med Hyg 2000, 94:159-63.
214. Thomson MC, Connor SJ, et al., Predicting malaria infection in Gambian children from satellite data and bed net use surveys: the importance of spatial correlation in the interpretation of results. Am J Trop Med Hyg 1999, 61:2-8.
215. Thomson MC, Connor SJ, Milligan PJ, Flasse SP: The ecology of malaria – as seen from Earth-observation satellites. Ann Trop Med Parasitol 1996, 90:243-64.
216. TK Suma, RK Shenoy, V Kumaraswami. A qualitative study of the perceptions, practices and socio-pyschological suffering related to chronic brugian filariasis in Kerala, southern India. Ann Trop Med Parasitol 2003; 97: 839-45.
217. Trape JF, Pison G, Preziosi MP, Enel C, Desgrees du Lou A, Delaunay V, Samb B, Lagarde E, Molez JF, Simondon F: Impact of chloroquine resistance on malaria mortality. C R Acad Sci III 1998, 321:689-97.
218. Twigg L: Health based geographical information systems: their potential examined in the light of existing data sources. Soc Sci Med 1990, 30:143-55.
219. UNAIDS: AIDS epidemic update: December 1998. Geneva: UNAIDS 1998.
220. Uttah EC (2011) Prevalence of endemic Bancroftian filariasis in the high altitude region of south-eastern Nigeria. Journal of Vector Borne Diseases 48: 78–84.
221. van Rie A, Beyers N, Gie RP, Kunneke M, Zietsman L, Donald PR: Childhood tuberculosis in an urban population in South Africa: burden and risk factor. Arch Dis Child 1999, 80:433-7.
222. Vanamail P, Gunasekaran S (2006) A study on risk factors of Wuchereria bancroftian filarial disease in Pondicherry. Demogr India 35:159–171.
223. Vanamail P, Gunasekaran S (2008) A quantitative analysis of the socio-economic determinants of health seeking behaviour related to bancroftian filariasis and its impact on elimination: a case– control study in Pondicherry, India. J Public Health 16:339–346.
224. Vanamail, P., Subramanian, S., Das, P.K., Pani, S.P. and Rajagopalan, P.K.EstimationoffecundiclifespanofWuchereriabancroftifrom a longitudinal study of human infection in an endemic area of Pondicherry (south India). Indian J Med Res 91: 293, 1990.
225. Vasuki, V., Patra, K.P. and Hoti, S.L. A rapid and simplified method of DNA extraction for the detection of Brugia malayi infection in mosquitoes by PCR assay. Acta Trop 79: 245, 2001.
226. Vijay Kumar KN, Ramaiah KD (2008) Usage of personal-protection measures against mosquito and the low prevalences of Wuchereria bancrofti microfilaraemia in the Indian city of Chennai. Ann Trop Med Parasitol 102: 391–397.
227. Vijayalakshmi, N., Sambasivarao, R., Anand Paul Kumar, M.P., Yuvaraj, J. and Pani, S.P. Role of aerobic bacteria in the aetiopathogenesis of acute adenolymphangitis (ADL) in filarial lymphoedema. Prog Lymphol 17: 163, 2000.
228. Vine M: Geographic information systems: their use in environmental epidemiological research. J Environ Health 1998, 61:7-10.
229. Vyas S, Kumaranayake L (2006) Constructing socio-economic status indices: how to use principal components analysis. Health Policy and Planning 21: 459–468.
230. Walter SD: Visual and statistical assessment of spatial clustering in mapped data. Stat Med 1993, 12:1275-91.
231. Weil, G.J., Lammie, P.J. and Weiss, N. The ICT filariasis test: A rapid-format antigen test for diagnosis of bancroftian filariasis. Parasitol Today 13: 401, 1997.
232. WHO: Global tuberculosis control. Geneva: World Health Organisation 1997.
233. WHO: TB – a global emergency. WHO report on the TB epidemic. Geneva: World Health Organisation 1994.
234. WHO: The world health report 1996: fighting disease fostering development. Geneva: World Health Organisation 1996.
235. WHO: The World Health Report 2000. Health Systems: Improving performance. Geneva: World Health Organisation 2000.
236. Wijesinghe RS, Ekanayake S, Perera MS, Wickremasinghe AR (2007) Knowledge
and perceptions of filariasis in Colombo, Sri Lanka, among patients with chronic filarial lymphoedema. Ann Trop Med Parasitol 101:215–223.
237. Wilkinson D, Pillay M, Crump J, Lombard C, Davies GR, Sturm AW: Molecular epidemiology and transmission dynamics of Mycobacterium tuberculosis in rural Africa. Trop Med Int Health 1997, 2:747-53.
238. Wilkinson D, Tanser FC: GIS/GPS to document increased access to community-based treatment for tuberculosis in Africa. Lancet 1999, 354:394-5.
239. World Bank: Overview of the World Bank's work in sub-Saharan Africa. Washington D.C.: World Bank 2000.
240. World Bank: World development report, 1993. Washington D.C.: World Bank 1993.
241. World Bank: World development report, 2000. Washington D.C.: World Bank 2000.
242. World Health Assembly (1997) Elimination of lymphatic filariasis as a public health problem. A 50.29.
243. World Health Assembly. Elimination of lymphatic filariasis as a public health problem. A 50.29, 1997.
244. World Health Organization (1992) Lymphatic filariasis: the disease and its control. Fifth report of the WHO expert committee on filariasis. World Health Organ Tech Rep Ser 821: 1–71.
245. World Health Organization (1999) Building partnerships for lymphatic filariasis - strategic plan. WHO, Geneva.
246. World Health Organization (2000) Eliminate Filariasis: Attack Poverty. Proceedings of the First Meeting of the Global Alliance to Eliminate Lymphatic Filariasis. WHO, Geneva.
247. World Health Organization (2006) Global Programme to Eliminate Lymphatic Filariasis. Wkly Epidemiol Rec 22: 221–232.
248. World Health Organization. Collaborative global programme to eliminate lymphatic filariasis. Programme background and overview towards initiating a national programme to eliminate lymphatic filariasis. WHO/CEE/FIL, p.1, 1999.
249. World Health Organization. Lymphatic filariasis: Reasons for hope. WHO/CTD/FIL/97.4 ,p.1, 1997.
250. World Health Organization. Lymphatic filariasis: The disease and its control. Fifth Report of the WHO Expert Committee on Filariasis. WHO Tech Rep Ser 821: 1, 1992.
251. WRI: Africa Data Sampler. CD-ROM edition 1. Washington D.C.: World
Resources Institute 1995.
252. Yapa L: Is GIS appropriate technology? IJGIS 1991, 5:41-58.
253. Years of Research. Silver Jubilee Publication, Vector Control Research Centre, Pondicherry. p. 95, 2000.
254. Zwarenstein M, Krige D, Wolff B: The use of a geographical information system for hospital catchment area research in Natal/KwaZulu. S Afr Med J 1991, 80:497-500.
APPENDIX - I
FILARIASIS IN KUMBAKONAM: CREATION OF GEOGRAPHICAL INFORMATION BASE (GIB) AND SPATIAL DIMENTIONS
A. personal Details on the Respondent: 1 Name (Optional) 2 Age In years : 3 Sex Male/Female 4 Education In completed years 5 Occupation Agriculture:
Weaving : Government Job: Private institution: Public institution: Own businesses:
6 Address Door no: Street name: Place name:
7 Family size Male adults: Female adults: Male children: Female children:
8 Control units Kumbakonam 9 Name of the sub units 10 Name of the night Clinic B. Details on Epidemiology and Diseases: 11 How long have you been suffering
from the disease (Filariasis)? In years:
12 How did you to know about this disease
On his/her own
13 Do you known the reason behind the disease
Yes/no
14 Do you know that your environment is the reason for it?
Yes/no
15 Do you know that it is caused by the mosquitoes?
Yes/no
16. Your perceptions about your own environment: a Dirty b Waste water is stagnant c Mosquito menace d Much vegetation/plants e No storm drains/drainage f People defecate/Urinate on road sides 17. Facilities/Amenities at home: a Drainage available b Waste water is stagnant pools c Lavatory d Septic tank e Well f Washing plat form around wall g Separate wash place for clothes and vessels h Big vessels/utensils for storing drinking water 18. There mosquito menace in the night: yes/no 19. The man to prevent mosquito menace at night: a Bed nets b Smoking c Mosquito coils d Odomos e Good night/banish mates 20. Does it affect/has it affected any other of your family members? : Yes/no C. Control and prevention Filariasis: 21. does the health personal spray anti-mosquito larval sprays around your house: Yes/no 22. What do the health workers do?
a Give information about disease b Take blood smears at nights c Distribute tablets regularly d Capture mosquitoes for laboratory analysis e Announce results of laboratory analysis 23. Did you corporate with field workers for collecting blood smears: yes/no 24. Is your disease in early stages? : Yes/no 25. Or is it in later, mature stages? : Yes/no 26. Do you take tablets regularly? : Yes/no 27. If yes, how many tablets? : In numbers 28. If no, give reasons 29. If you have taken tablets, what are the side effects? a Headache b Fever c Nausea d Vomiting 30. Do the side effects affect your daily job routine: yes/no? 31. How many days: in number 32. To prevent disease and avoid side effects of treatment? a Surgical operation b Any other preventive efforts 33. Do you know about the national Filariasis Control Programme (NFCP)? : Yes/no 34. If yes, how did you come to know? a Through public health department b Through advertisement
c While census was being taken d While health workers distributing tablets 35. Because you have / are afflicted by disease (answer: compassionately / insultingly or bitterly) a How do your family members treat you? b How do your friends treat you? c How do your neighbors treat you? d How do your relatives treat you? 36. How do you fell about it, psychologically? a Bitter / Hateful b It is fate. c Can be avoided 37. The efforts you take to prevent it from spreading/ infecting others (List one by one) 1. 2. 3. 4.
APPENDIX - II
Spatial Distribution of Filarial Cases: 1998
ID Name Address Sex Age Place of occurrence
Year **
Date_ Treat
40 Balamurugan S/o Palanivel
3x Karuppur road M 40 LL & RL
15 5/1/1998
39 Ramesakumar S/o Narayanan
Karuppur road M 18 RL 4 5/1/1998
50 Vinoth S/o Arokiyaraj
24, Chennai road M 10 LL 8 5/8/1998
20
Manjula W/o Shanmugam
16-c, Suruttai pattai Melakottiyur
F
27 RL 7 30/9/1998
14 Mariyamal W/o Chandrakasan
4-5, Mudukku street F 50 RL & LL
8 8/6/1998
13 S. Kannan S/o Srinivasan
10, Krishnan koil West street.
M 55 RL 3 8/6/1998
12 Rajeshknna C/o Rajendran
4, South street . Melakottiyur
M 18 LL 8 8/6/1998
7 Selambarasan C/oAmbalavanan
41, Swamimalai Main road
M 9 LL 8 18/6/1998
8 Swaminathan S/o Rathinam
13-A, Swamimalai Main road
M 65 RL 5 18/6/1998
6 Venkatraman S/o Lakshmanan
44, Swaminalai Main road
M 20 LL 10 18/6/1998
4 Selvam S/o Karumpairam
Moopa koil west street M 39 RL 5 11/6/1998
1 Jagaghalaprathaban 26 Moopakoil west street M 35 RL 4 11/6/1998 96 Balakrishnan
C/o Srinivasan 29,A, Sudamani Colony M 22 RL 4 5/10/1998
88 Malika W/o Durairaj
22, Pettaiyadavar Street F 23 LL 5 5/7/1998
89 Ganesan S/oVennyappan
22, Pettai north M 41 RL 7 8/10/1998
107 Jayalaxmi W/o Subramanian
2, Mukkannar Street F 24 LL 5 29/4/1998
108 Jaybal S/o Saminathan
99, Mukkannr Street M 35 RL 7 27/10/1998
225 Parvathy W/o Raj
Kattunayakkan Street F 30 RL 6 5/10/1998
260 Umma W/o Gurusamy
19, Mariyaman Koil Street
F 16 LL 8 15/12/1998
261 Mohan S/o Moorthy
28, Mari Amman koil Street
F 30 RH 6 28/7/1998
259 Hayarnesabeevi D/oAbdulhamid
13-9, Thaikal Street F 42 RL & LL
10 21/9/1998
37 Kamala W/o Rathinavel
1/A, Brameshpuram Valinadapu
F 28 LL 4 23/7/1998
67 Kannan S/o Kaliyamoorthi
7, Srinivasa Nandavanam
M 23 RL 8 28/1/1998
44 Sellammal W/o Vellayutham
M.M.R Nagar Perumandi Main Road
F 45 RL 5 29/7/1998
43 Keerteega D/o Murugan
16, Perumandi Main Road, North Street.
F 8 RL 6 28/7/1998
45 Kalyamoorthy S/o Marimuthu
11-F Perumandi Main Road
M 52 LL 8 29/7/1998
42 Balu S/o Kumbalingam
1, Perumandi Main Road, Sudukkadu Steet.
M 34 LL 28 28/7/1998
41 Gopal S/o Vaithilingam
12, Perumandi Main Road, First Street
M 52 RL 4 28/7/1998
155 R. Banchamoorthy S/o Raman
WECP Kumbakonam M 35 RH 4 27/10/1998
153 Alamelu W/o Subaiyan
Kamakodinagar Santhu F 35 LL 7 29/7/1998
** Presence of disease for the period specified Source: Filarial Control Unit, Kumbakonam
Spatial Distribution of Filarial Cases: 1999
ID Name Address Sex Age Place of
occurrence Year **
Date _treat
99 Kanimozhi D/o V. Perumal
Mallukachetti St F 13 LL 5 6/10/99
97 Sokkalingam S/o Sambasivam
5. Nellukadai St M 37 RH 7 28/10/99
109 Kamala W/o Jayabal
99, Mukkannar St F 33 LL 6 8/10/99
** Presence of disease for the period specified Source: Filarial Control Unit, Kumbakonam
Spatial Distribution of Filarial Cases: 2000
ID Name Address Sex Age Place of
occurrence Year **
Date Treat
100 Subramanian 64, Malluka chetti M 38 RH & LL 10 10/2/2000
s/o Ayyadurai street 111 Radhakrishnan 1, chetti new street M 59 RL 15 9/2/2000 112 Gowri
w/o Rengachari 28,Chetti new street F 45 RL 15 9/2/2000
114 Geetha w/oLakshmanan
41, Chetti new street F 45 LL & RL 8 11/2/2000
115 Giyaudeen A.r.r. road, 130, chetti new street
M 50 LL 15 12/2/2000
113 Rajamannar s/o Balakrishnan
39, Chetti new street M 75 LL 10 11/2/2000
116 Laxmiammal c/o thulasiraman
A.r.r road chetti new street
F 65 LL 20 15/2/2000
118 Annapurani c/o Loganathan
Chetti new street F 56 LL 25 14/2/2000
117 Vasumathi w/o Chakrabani
138, A.r.r road Chetti new street
F 53 RL 5 14/2/2000
125 Baskar s/o Samy
9, Palaniyappa colony M 35 LL 7 20/1/2000
177 Krishnamurthy s/o Ramasamy
22/23, Thuvarankurichi new street
M 63 RL 12 8/2/2000
175 K. Sethuraman s/o k. Subaiyan
40, Thuvarang kuruchi street
M 53 LL 8 8/2/2000
176 Rukmani 25-f, Thuvarang kuruchi middle street
F 60 RL&LL 25 8/2/2000
174 Krishnamurthy s/o Ramasamy Ayer
38, Thuvarang kuruchi street
M 61 RL&LL 10 27/1/2000
189 Kanagavalli w/o Paramanantham
Amman koil street F 43 RL 10 8/3/2000
197 Amsavalli w/o Kathiresan
2/920, Mullai nagar F 70 LL 10 27/7/2000
198 Sundarambal 2/998, Mullai nagar F 55 LL 10 27/7/2000 188 Lelismary
w/o Susai 17,Singarathoppu F 50 RL 15 6/3/2000
190 Arokyasamy d/o Thamburaj
41, Sengankanni F 17 RL 5 28/6/2000
195 Muthukrushnan 171,Vivekananthanagar M 76 LH 6 21/7/2000 193 Samboornam
w/o Gobalakrushnan 155, Vivekanantha nagar
F 65 L;L 10 21/7/2000
192 Pangajam w/o Ramaiyan
29, Vivekananda nagar F 44 LL 3 19/7/2000
194 Kamala w/o Paramasivam
169, Vivekanantha nagar
F 40 LL 15 21/7/2000
179 Rajeswari 636,Ottai south street F 55 RH 6 7/11/2000 180 Poonkothai
w/o Duraisamy 614,Ottai south street F 40 RL 8 8/11/2000
181 Maruthai 614,Ottai south street M 30 RL 10 9/11/2000 182 Panchauarnam
w/o Thangaraj 674,Ottai south street F 35 LL 20 20/2/2000
184 Sakthivel 45,Kothan ottai street M 29 RL 3 2/3/2000
186 Srinivasan 6,Kothan ottai street M 82 LL 5 6/3/2000 187 Jothi
w/o Swaminathan 3,Kothan ottai street F 40 RL 8 2/3/2000
183 Anchamal w/o Ramachandran
2, Kothan ottai street F 51 RL&LL 10 23/2/2000
199 Sornnamal w/o Ramamurthy
52,Thoppu street F 65 RL 15 18/3/2000
201 Vasudevan s/o Palaiya
46, Ramachandrapuram
M 50 RL&LL 20 23/3/2000
202 Lakshmanan s/o Thangamuthu
46, Ramachandrapuram
M 30 LL 20 25/3/2000
204 Padma w/o Balakrushnan
13, Sowrastra middle street
F 66 RL&LL 20 10/4/2000
208 S.p. Vijaya 22,Sowrastra middle street
F 61 RL 5 12/4/2000
207 Sonnammal c/o J.R.Venkatraman
51, Sowrastra middle street
F 65 LL 12 12/4/2000
206 Ramamani c/o Sethuraman
13, Sowrastra middle street
F 58 LL 15 10/4/2000
205 Saraswathi w/o Govindan
27,Sowrastra F 40 RL&LL 10 30/3/2000
222 Jayalaxmi c/o Kamaraj
63/64 Yadhava street F 45 RH 12 6/6/2000
220 Renuka w/o Jothiraman
20/13 North erthkara street
F 41 RL 20 12/5/2000
223 Vasanthi w/o Kirushnamurthy
58/27 Kumaran street F 40 LL 5 6/6/2000
221 Pattammal w/o Palanisamy
35/23 Maruthuva street F 60 LL 20 15/5/2000
219 Govindasamy s/o Srinivasan
19,South Erthukara street
M 65 LL 3 3/5/2000
226 Alamelu ammal 57/23 Kaduvetti street F 70 LL 10 23/5/2000 227 Banumathi
w/o Sathiya 73/14 Indragandi salai F 42 LL 10 5/7/2000
231 Vachala c/o Prabu
10, Manai street F 35 LL 7 26/5/2000
230 Krishna Ayer 18,14 Manai street M 71 RL&LL 12 24/1/2000 228 Sarangapani
s/o Kuppusamy 14, Manai street M 65 LL 20 24/1/2000
233 Vengatraman 18/38 Manai street M 55 RL 14 11/7/2000 232 Vasantha 22/23 Manai street F 40 RL&LL 5 5/7/2000 264 Amul
w/o Santhanam 36, Arasallar vazhinadappu
M 70 LL 10 31/8/2000
263 Laxmi w/o Krishnasami
59, Arasallar vazhinadappu
F 65 RL 20 29/8/2000
266 Amirtham w/o Sadayappan
29g, Mariyamman koil street
F 50 RL 6 10/5/2000
262 Mohan s/o Moorthy
28, Mariyamman koil street
F 30 RH 6 28/7/2000
265 Umahabeba Mariyamman koil M 50 RL&LL 8 4/9/2000
w/o Mohamed street 258 Ganambal
w/o Subramaniyan 15, South valluvar street
F 48 RL 15 24/11/2000
267 Dhanalakshmi w/o Palanivel
33/14b, Veerapandiyan street
F 40 LL 10 23/9/2000
271 Saroja w/o Sowndarajan
7, Needamangalam main road
F 56 LL 7 18/8/2000
272 Marimuthu
30, Ambethkar street M 67 LL 20 19/8/2000
270 Segathambal w/o Thenyappan
87, Needamangalam main road
F 44 LL 2 10/8/2000
269 Kamala w/o Sampantham
33/6-B Karaikal main road
F 45 LL 3 9/8/2000
157 Kaliyamoorthy 18/7,Thilakar mela street
M 61 LL 12 11/2/2000
158 Cathedra 16/3, Whitaker mela street
F 48 LL 5 12/1/2000
159 Meenakshiyammal c/o Susila
23-a, Thilakar mela street
F 60 RL 10 20/1/2000
160 G. Chanthira w/o Krishna moorthy
18/c, Thilakar mela street
F 48 LL 10 20/1/2000
156 Kunchupillai 18, Thilakar mela street M 75 LL 22 11/1/2000 256 Yasotha 18/54-A, Kamarajar
salai F 50 LL 25 6/11/2000
257 Swaminathan 196 Prabu cycle company
M 50 LL 20 24/11/2000
255 Sowndaravalli S.b.m.c street F 65 LL 20 8/9/2000 164 Jenifar 16-a, Pathimapuram
new bus stand F 14 RL 6 14/12/2000
165 S. Esthar 7, Pathimapuram new bus stand
F 50 LL 10 14/12/2000
151 Ahamadhunachiya w/o Ebrakin
2-f, Mothilal street F 60 LL 10 24/6/2000
152 Vangmanirao s/o Ramaiya rao
Krishnappanakan north street
M 70 LL &RH 10 24/6/2000
149 Kartik s/o Kaliyamoorthy
18-n, Mothi lal street M 17 LL & RL 4 12/6/2000
150 Nalini c/o Janakarajan
18-m, Mothilal street F 42 RL & LL 10 12/6/2000
57 G.D. Shagunthala 79/36, Periyar colony F 44 LL 20 5/1/2000 59 Nallammal
w/o Arunachalam 10, Kuyavan street F 70 RL & RH 7 12/9/2000
60 Subbammal w/o Sokkaiya
1-a, Kuyavan street F 60 RL 15 12/9/2000
38 Jagaparali w/o Karimravuthar
kms Nagar M 40 LL 5 9/6/2000
17 Sellanal w/o Ganesan
18, Earakaram Val nadappu
F 37 LL 37 28/6/2000
31 Ambiga 40, Asath colony F 50 RL 3 19/3/2000
w/o Krishnamoorthy 32 Rukkumani
d/o Manikkam 45, Puthupettai M 60 LL 20 10/3/2000
26 R. Veeramani s/o Rmachandran
Chekkadi st. Melacaueri
M 20 LL 41 13/7/2000
25 Chinnapilai w/o Mottiyapathar
19/20, Cheakkadi st. Melacauveri
F 18 RL & LL 18 12/7/2000
24 Naduncheliyan s/o Chenniyan
61, Kaliyamman koil st. Melacauveri
M 27 LL 27 3/7/2000
23 Saravanan
s/o Thirunawgrasu Kelarkudi st. Melacauvari
M 30 RL 5 3/7/2000
22 Devi w/o A. Moorthy
19/45, Cheakadi st. Melacauvari
F 32 LL 6 3/7/2000
27 Murugesan s/o Govindan
12-a, Korikkaithotam Melacauveri
M 50 LL 9 21/8/2000
21 Hajamaydeen s/o Bhair mohamad
5. Main road muslim st. Melacauvari
M 65 RL 2 16/8/2000
28 Narayanaswamy s/o Diraiswamy
19-c, Chekkadai st. Melacauveri
M 70 RL 10 16/8/2000
82 Viswanathan s/o Rathinam
Thirumanjan st. Cauvery badithurai
M 60 LL 4 25/4/2000
81 Alamelu 46-b, Kalyanaraman street
F 55 RL 6 10/5/2000
80 Nagarajan s/o Subramaniyan
3-e, Kalyanaraman street
M 60 LL & RL 15 9/5/2000
78 Santhi w/o Marimuthu
15-d, Appukutti lane F 35 LL 8 2/5/2000
79 Sarasvathi w/o Banchanathan
26, Balacheetti street F 52 LL 30 8/5/2000
76 Laxmi w/o Muthiya pillai
14-b, Appukutti lane F 77 LL & RL 10 2/5/2000
77 Ananthi w/o Maruthu
11, Appukutti lane F 28 LL 3 2/5/2000
69 Ganasen 23, Chakrabani east street
M 50 LL 2 4/4/2000
68 Pangajam w/o Krishna moorthy
14, Chakrabani east street
F 28 RL 5 27/2/2000
74 Singaravel s/o Kunjithapatham
5, P.S. Shanmugam street
M 48 LL 3 25/4/2000
72 Vijayam w/o Veeraragavan
20, Chakrabani st. south madavilagam
F 55 LL & RL 8 25/4/2000
71 Vasantha w/o subramaniyan
9-a, Sakrabani st. south madavilagam
F 48 LL 2 2/11/2000
75 Danam w/o Natrajan
19, Thiyaki ramasamy street
F 50 RL 5 25/4/2000
73 Gokila w/o Pakkirisamy
6, Keelaiyyan street F 50 RL 3 17/4/2000
70 Balasubramaniyan 5, Chakrabani north street
M 73 LL 20 7/4/2000
65 Hemalatha w/o Shankaran
80, Kamashi joshiyar street
F 25 LL 2 27/4/2000
66 Bhuvaneswari 16, kamakshi joshiyar street
F 28 RL 5 27/2/2000
61 Parani kumar s/o Laksmanan
13, Karunai kollai north street
M 30 RL 5 26/3/2000
63 Aboorvam w/o Muthiya
Karunai kolai north street
F 80 RL & LL 15 28/3/2000
64 Shanmugam s/o Pakriswamy
47, Karunaikollai west street
M 76 RL 7 30/3/2000
62 Ramalingam s/o Saravanamuthu
16, Karunai kollai north street
M 65 RL 10 27/3/2000
144 Vijaya Pattusariyar street F 41 RL & LL 10 22/2/2000 142 Subramanian 9, Pattusariyar street M 63 RL 15 21/2/2000 143 R. Rajavelu 17, Pattusariyar street M 39 LL 20 22/2/2000 141 Chinnaponnu 25, Moorthi chetti street F 55 LL 2 4/1/2000 140 Balaraman 28-a, Moorthi chetti
street M 45 RL 20 4/1/2000
132 Durgadevi 1, Kumbeswarar F 13 RL 2 4/1/2000 131 Jayalakshmi
w/o Ravichandran 68/27, Kumbeswarar F 35 RL 4 4/1/2000
136 Sethuraman 6, Kumbeswarar sanathi
M 62 RL 8 4/1/2000
133 Viswanathan s/o Rathinam
4-a, Thirumajan street. Cauveri badithurai
M 55 RL 20 4/1/2000
139 Swaminathan 26-d, Periyakadai street. Kumbeswara koil
M 58 RH 5 4/1/2000
135 Subbaiyan Senbagam lorry booking
M 55 LL 2 4/1/2000
146 Krishnamurthy Kathiravan hard ware, Dukkambalayam street
M 42 RL 5 7/3/2000
147 Daramalingam Fruit vendor tip street M 66 RL 3 8/3/2000 148 Muthammal Arunagiripettai F 63 RL 15 9/3/2000 145 Pechimuthu 27, F.S.R. big street M 60 LL 5 4/1/2000 166 PeriyanayakiS
w/o Veeramuthu 54, Selva sarangabani street
F 18 LL 15 7/4/2000
167 Rajalakshmi w/o Soundara rajan
64, Selva sarangabani street
F 45 RL 18 7/4/2000
168 Rasul bevi w/o Dajudeen
Selva sarangabani street
F 28 RH 28 3/8/2000
169 Lakshmi 11, Sarangabani street F 55 RL 9 4/1/2000 172 Nachiyappan 18, Kavara street M 55 LL 9 9/3/2000 171 Padmavathi
c/o Ravi 18-f, Kottan cheeti street
F 60 RL 15 9/3/2000
212 Logambal c/o Neelavathi
13 B.A road F 85 RL 18 18/4/2000
217 Gowri w/o Sekar
13, Palaniyandavar sannathi
F 30 RL 15 5/5/2000
214 Jayalaxmi c/o Kamaraj
63/64 Vadhava street F 45 RH 12 15/5/200
215 Srinivasan s/o Radhakrishnan
46, Palaniyandavar sannathi street
M 20 LL 10 4/5/2000
216 Lakshmi w/o Moorthy
80, Palaniyandavar sannathi street
F 65 LL 12 13/5/2000
218 Renganayaki
22, Machakkara street F 65 RL 10 17/5/2000
235 Lakshmi c/o Ganasekaran
Gowthameswarar north street
F 60 RL&LL 20 19/6/2000
238 Ganakam c/o Gurumoorthy
28/189 Gandhiyadigal salai
F 62 RL 20 1/7/2000
234 Saroja w/o Ranganathan
28/38 Manai street F 43 RL 20 5/7/2000
236 Manimeakalai w/o Ravichandran
61/26 a Kasiviswanathar north street
F 33 RL 10 30/10/2000
244 Ranga s/o Selvam
26/3, Bharathiyar street M 40 RL 45 3/1/2000
243 Gangaiyammal 11, Bharathiyar street F 82 RL 20 3/1/2000 249 Sagunthala
w/o Sundaram 330, Bharathiyar street F 60 LH 8 3/8/2000
245 Elangovan 11, Bharathiyar street M 30 RL 8 3/1/2000 248 Periyanayagi
w/o Ravi 4-d, Bharathiyar street F 70 RL 4 6/11/2000
250 Sengamalam 326, Bharathiyar street F 65 RL 10 8/8/2000 53 Anthoni mozhi
w/o Anthonidass 1061, Autonagar F 45 RL 2 5/6/2000
56 Nachithramary w/o Addikkalam
1009, Auto nagar F 58 RL 5 6/6/2000
55 Anthoniyammal w/o Adaikalaswamy
1006, Auto nagar F 52 RL 6 6/6/2000
54 Rajammal w/o Sakthvel
1055, Auto nagar F 62 LL 2 6/6/2000
52 Jayalakshmi w/o Chinnappillai
21, Sathira st.neelathanallur road
F 40 LL 2 26/5/2000
51 Unnamalai w/o Raja
136/6, Gandipattai F 60 LL 2 14/3/2000
49 K. Muthusamy s/o Krishnapadiyachi
11 b.c., Perumandi main road
M 52 LL 6 15/5/2000
48 Ramalingam s/o Kannusamy
8 a Perumandi main road
M 75 LL 2 15/5/2000
196 Mariyammal w/o Govindan
2/925, Mullai nagar F 80 RH 10 27/7/2000
185 Jebaludeen s/o Abdulrazhq
1,Kothan ottai street M 60 LL 22 2/3/2000
191 Sundareswari w/o
41,Sengankanni F 47 LL 2 28/6/2000
Thangaperumal ** Presence of disease for the period specified Source: Filarial Control Unit, Kumbakonam
Spatial Distribution of Filarial Cases: 2001
ID Name Address Sex Age Place of occurrence
Year **
Date_ Treat
10 Ramasamy s/o Venugopal
11-a, Swami main road M 86 R.L 28 12/6/01
11 Sivagamiammal w/o Rathinam
12, Swami main road M 70 R.L 3 12/601
15 Govindaraj s/o Natesan
4/5, Melakottiyur south street
M 59 LL&RL 45 18/6/01
3 Rani w/o Murugesan
26-f, Moopa koil west street.
F 50 RL & LL 5 21/8/01
2 Ananda kumar s/o Veeramuthu
26-c, Moopa koil west street.
M 17 LL 7 21/8/01
5 Alamelu w/o Rajangam
34/70, Moopa koil west street.
F 70 RH 4 21/8/01
9 Pakrisamy s/o Kaliyappan
44, Swami main road M 42 LH 4 1/6/01
16 Mageswari w/o Shankar
14, Melakottiyur south st.
F 39 RL & LL 6 26/6/01
19 Ramjan 26/35, Vannaiyadi st. mela cauvery
F 35 R.L 4 25/801
18 Rasulpeew w/o Abdulrahman
5, Earakaram vazhi naddappu
F 50 R.L 10 10/7/01
30 Thanalakshmi 40, Puthupettai F 39 RH 4 12/8/01 33 Halinipeevi w/o.
Mohamadsalam North muslim st melacauvey
F 60 R.L 11 25/6/01
29 Mohammadibrahim Asath colony melacauvary
M 65 R.L 7 12/7/01
36 Ramesh s/o Appumani
15/25, Thattara st M 32 R.L 5 13/8/01
34 Makalakshmi d/o Ragavan
21, Thattara st F 40 R.L 7 10/8/01
35 Soundravalli Thattara st F 45 LL 9 10/8/01 85 Sellamal
w/o Vijaragavan 113/6, Solaiyappan st F 57 LL 2 2/1/01
86 Sarasvathi w/o Venkatraman
104/118, Solayappan st F 57 RL & LL 9 5/1/01
87 Chandrasekhar s/o Ramasamy
13, Babu reddikulam M 43 R.L 2 5/7/01
83 Barimalam w/o Selvaraj
2/47, Ellukuttai metu st F 35 R,L 6 29/3/01
84 Sundaramoorthi c/o Chakkrabani
46/4, Viyasar st M 58 R.L 8 9/4/01
91 Jegatham w/o Rethinam
309, Pettai pasikaran santhu
F 80 R.L 40 23/1/01
90 Danalakshmi w/o Ramakrishnan
30/31, Pettai pasikaran F 55 LL 20 23/1/01
95 Danalakshmi w/o Vadivel
50, Pettai north F 80 R.L 15 9/8/01
94 Vembu d/o Ramamurthy
40/7,Pettai north F 28 R.L 3 5/8/01
92 Pirema w/o Venkadasan
4, Pettai north F 40 R.L 57 19/3/01
93 Malika w/o Sokkalingam
59, Pettai north eastapuram
F 45 R.L 20 24/11/01
98 Kalidoss s/o Banchanathan
Rathamettal kuttiyan st M 38 R.L 6 13/3/01
101 Danalakshmi w/o Srinivasan
3/4, Mallukacheeti st F 65 RL & LL 10 12/3/01
105 Ganam w/o Kanakasabai
Poiyadhapillaiyar koil F 65 RL & LL 20 8/5/01
104 Cadbury w/o Madhavan
40, Viyabari st F 29 R.L 8 22/1/01
102 Maniyammal w/o Murukaiyan
89,Nanayakara st F 42 R.L 3 22/1/01
103 Visvalinkam s/o Ramalingam
32,Nanayakara st M 64 RL & LL 25 22/1/01
106 Meenakhi w/o Raman
25-a,Vinaithedhal st F 59 R.L 10 8/5/01
129 Jalaxmiw/o Selvam 22, K.V. Melaveethi F 41 LL 8 12/11/01 126 Anjammal
w/o Rathakrisnan 18-c, K.V keelaveethi M 40 R.L 11 4/5/01
127 Rajeswari w/o Chinnappa
5/3, K.V north F 50 LL 5 20/2/01
128 Karthikkannan s/o Magalingam
K.V north M 57 R.L 3 21/2/01
173 Vinayakamoorthi s/o Thangavel
6-c, Old place F 32 RH 7 21/6/01
130 Booma w/o Panneerselvam
76/41, Singara chetti st F 50 RL & LL 3 22/3/01
138 Ranjutham 29, Thanjai main road Kubaswaran koil
F 45 R.L 10 24/4/01
137 Jalaxmi w/o Krishnan
11,Kumbeswaran koil st
F 51 R.L 7 16/4/01
46 Manimaran w/o Theyakarajan
Perumandi st M 35 RH 8 26/4/01
47 Murugadass s/o Kaliyamoorthi
Perumandi st M 22 LL 7 26/4/01
200 Nithiya Linekarai thoppu st M 52 LL 20 17/3/01
w/oRajaraman 203 Surya
w/o Janakiraman 13/8, Ramachandirapuram
F 45 R.L 25 4/5/01
224 Deenashkumar s/o Kaliyamoorthi
27/13, River bank st M 22 LL 5 23/1/01
240 Suriya w/o R.K.Kannan
4/40, J.P west st M 50 LL 20 24/5/01
241 Lakhmi w/o Krishnamurthy
102, J.P east st F 50 R.L 5 3/9/01
253 Hemavathi s/o Ashogan
25/10, Eallaieechetti st F 3 R.L 2 11/10/01
254 Rajamani w/o Balakrishnan
46,Visvanathan colony F 51 LL 6 13/2/01
239 Kaliani c/o Somu
188/3, Ganthiyadikal salai
F 65 RL & LL 2 22/6/01
237 M.Lakshmi w/o Krishnamurthy
50/6, Mahamagakula m F 50 R.L&LH 10 3/7/01
154 Muthulakshmi w/o Natarajan
1401, Kamakodinagar south
F 68 LL 16 6/2/01
110 Vijalakshmi w/o Thandabani
25, Mukkannar st F 68 R.L 20 30/1/01
213 Pusba w/o Krishnamoorthy
18/13, Natanagobal st F 52 LL 5 17/4/01
** Presence of disease for the period specified Source: Filarial Control Unit, Kumbakonam
Spatial Distribution of Filarial Cases: 2008
ID Name Address Sex Age Place of occurrence
Year **
Date_ Treat
123 Laxmiammal w/o Dulasiraman
163, Chetti new street F 68 RL 10 20/2/2008
121 Rajamannar w/o Santha
73/39, Chetti new street M 75 LL 7 14/2/2008
122 Indrani w/o Mani 91/48, Chetti new street F 39 LL 5 15/2/2008 120 Gowri w/o
Rengasamy 47/28, Chetti new street F 52 RH 20 14/2/2008
124 Annaborani c/o Loganathan
32/188, Chetti new st F 60 LL 17 21/2/2008
119 R.Rathakrishnan 1, Chetti new street M 62 R,L 25 13/2/2008 178 Saraswathi 22, Kothan new street F 57 LL& RL 15 19/2/2008 211 Sethuraman 13/18, Sourastra middle
street M 62 LL 8 22/4/2008
210 Sornammal 51, Sourastra middle st F 73 RL 5 23/4/2008 242 Suria 4/9, J.P. west street F 45 LL 15 16/5/2008 251 Gangaiyammal
w/o Mathavan Bharathiyar nagar F 52 RL 20 5/1/2008
252 Periyanayagi 11-c,Bharathiyar nagar F 45 LH 9 6/2/2008 268 Rani w/o Ratha 28/24,Veera pandiya st. F 44 RL 6 30/1/2008 161 Meenakshiammal 23-a, Thilakar mela st. F 62 LL 7 22/1/2008
163 Ganthimathi w/o Kaliyamoorthi
18/17, Thilakar mela street
M 63 LL 12 23/1/2008
162 Kunchupillai c/o Thangamani
18-c, Thilakar mela street
M 77 LL&lh 20 23/2/2008
58 D.Shagunthala 36, Periyar colani F 49 R,L 7 2/4/2008 170 Periyanayaki 38/54, Sarangabani st F 77 RL&LL 20 27/2/2008
** Presence of disease for the period specified Source: Filarial Control Unit, Kumbakonam
CORRELATION MATRIX
V.No Code X1 X2 X17 X18 X20 X21 X22 X23 X1 AOR -.248* -.203* X2 LOE -.294** .227* X3 PFD -.248* -.294** .337** X4 EID -.203* .337** X5 PAD .227* X6 PWS X7 PMM X8 PVC X9 PAD -.227*
X10 ADF .287** X11 ASP X12 ALF .261** .318** X13 AST .206* .270** X14 UMC -.271** .215* X15 UON .233* X16 UGB X17 HPA .276** X18 CBS X19 CFW X20 SOD -.301** X21 COT X22 NDT X23 SHE X24 SEJ X25 PEC .289** X26 PDP X27 PSD X28 TFM X29 TYN X30 TYR -.200* X31 PAB .222* .239* X32 PAF .290**
V.No Code X24 X26 X27 X28 X29 X37 X38 X39G X1 AOR X2 LOE X3 PFD .261** .206* -.271** X4 EID .318** .270** .233* X5 PAD X6 PWS .287** X7 PMM .215* X8 PVC -.227* X9 PAD
X10 ADF X11 ASP -.247* -.296** X12 ALF .247* .944** X13 AST -.296** .944** X14 UMC -.237* X15 UON -.237* X16 UGB X17 HPA X18 CBS X19 CFW X20 SOD -.244* X21 COT X22 NDT X23 SHE X24 SEJ X25 PEC X26 PDP X27 PSD X28 TFM -.208* X29 TYN X30 TYR -.206* X31 PAB X32 PAF
V.No Code X41 X43 X46 X47 X49 X50 X51 X56 X1 AOR -.301** X2 LOE X3 PFD .276** X4 EID X5 PAD X6 PWS X7 PMM X8 PVC X9 PAD
X10 ADF X11 ASP X12 ALF X13 AST X14 UMC X15 UON X16 UGB -.244* X17 HPA X18 CBS .263** X19 CFW X20 SOD -.283** -.233* -.291** X21 COT .484** .327** X22 NDT -.283** .484** X23 SHE .263** -.233** .257** X24 SEJ -.291** -327** .257** X25 PEC -.253* X26 PDP X27 PSD X28 TFM .268** -.237* X29 TYN .327** -.227* X30 TYR .298** -.240* X31 PAB
X32 PAF V.No Code X58 X60 X62 X63 X65 X66 X67 X68 X1 AOR -.200* X2 LOE X3 PFD .289** X4 EID .222* X5 PAD .290** X6 PWS .239* X7 PMM X8 PVC X9 PAD
X10 ADF -.208* -.206* X11 ASP X12 ALF X13 AST X14 UMC X15 UON X16 UGB X17 HPA X18 CBS -.253* X19 CFW X20 SOD .268** .327** .298** X21 COT X22 NDT X23 SHE -.237* -.227** -.240* X24 SEJ X25 PEC X26 PDP .740** .200** X27 PSD .740** .2000** X28 TFM .920** .286** -.219* X29 TYN .200* .200** .920** -.963** -.285* X30 TYR .286** .963** -.273** X31 PAB -.384** X32 PAF -.219* -.255* -.273** -.384**
Source: Results of the SPSS package jkpH ;ehL - Fk;gnfhzk; ahidf;fhy; neha; jLg ;g [
ikaj;j pd ; ,lg ;gh pkhd';fs; : xU g [t pj ; jfty; bjhFg;gikg ;g pd ; mQFKiw
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murpdh; fiyf; fy;Y]hp (jd;dhl;rp)/ Fk;gnfhzk; - 612 001.
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,t;tha;tpw;fhf Fk;gnfhzk; ahidf;fhy; jLg;g[ ikaj;jpy; ,Ue;J bgwg;gl;l
g[s;sptptu';fisf; bfhz;L Fk;gnfhzk; efuj;ijr; rhh;e;j Rw;Wg;g[wr;NHy;/ kf;fspd;
eilKiw thH;f;if/ mjdhy; mth;fs; njhw;Wtpj;j fHpt[ePh; njf;f';fs; kw;Wk; mjid
gad;gLj;jp ahidf;fhy; Ez;fpUkpfs; tsUtjw;F VJthf cs;s NHiy gw;wpa[k;/ mjdhy;
ghjpf;fg;gl;l nehahspfis gw;wp 1998 Kjy; 2008 tiu xU rpy fhyfl;l';fspy;
g[s;sptptu';fis nrfhpj;J mitfisf; bfhz;L g[tpj;jfty; bjhFg;gikg;g[
cUthf;fg;gl;Ls;sJ. ghjpf;fg;gl;l ,e;nehahspfsplk; bkhj;jkhf 272 egh;fsplk; ,e;neha;
bjhlh;ghd gy nfs;tpfSf;F gjpy;fis bgw;W mtw;iw bfhz;L ,e;neha;f;F fhuzkhf
tps';Fk; kpf Kf;fpa fhuzpfis g[s;spapay; _yk; gFg;gha;t[ bra;J/ Ie;J kpfKf;fpakhd
fhuzpfisa[k;/ mitfs; xt;bthd;Wf;Fk; mtw;wpy; cs;sl';fpapUf;Fk; khwpfSld;
tptuzk; bra;ag;gl;Ls;sJ.