Novel Approach of Geographic Information Systems on Recent Out-Breaks of Chikungunya in Tamil Nadu, India
The study aimed to provide detailed picture and baseline data about recent outbreak of chikungunya virus in public health sectors. The data were collected from the Director of Medical Science (DMS) department of economic and statistics in Chennai. The present investigation, chikungunya outbreak in different districts of Tamil Nadu was plotted in Geographic Information Systems (GIS) software and rainfall was correlated to forecast with recent outbreak. Smoothing methods was adapted to filter the data. Chikungunya outbreak was high at 8 districts; chikungunya fever cases were not recorded in 1 district, chikungunya prevalence was very low in 2 districts and in the rest of 19 districts, chikungunya fever cases were moderately recorded in Tamil Nadu. The re-emergence and epidemics are unpredictable phenomena but the impact of such events can be ameliorated by appropriate knowledge and by being in the right state of preparedness.
Received: August 31, 2010;
Accepted: January 06, 2011;
Published: February 01, 2011
Chikungunya is a crippling disease caused by a chikungunya virus (CHIKV) belonging
to the genus alpha virus of the family Togaviridae. It is an enveloped, positive-strand
RNA virus capable of causing an acute infection characterized by joint pain,
muscle aches, head ache and rash. It is a mosquito borne disease transmitted
by Aedes aegypti or Aedes albopictus. The genus Aedes are
considered disease vectors as they are responsible for the transmission of a
number of viral and parasitic human pathogens worldwide. This is because this
genus has a cosmotropical distribution and exhibits a distinct preference for
human habitats (Ahmed et al., 2008).
This disease is almost always self-limited and rarely fatal. Chikungunya has
become a global concern due to an escalation in the disease outbreaks in Africa,
India and south East Asian countries (Yadav and Murthy,
2006). In India, first outbreak of chikungunya virus infection was reported
in 1963. Consequently, there has been no active or passive surveillance carried
out in the country and therefore, it seemed that the virus had disappeared
from the sub-continent. How ever, recent reports of large scale outbreak of
fever caused by chikungunya virus infection in several parts of southern India
have confirmed the re-emergence of this virus. Vector borne disease exhibits
a distinct seasonal pattern, which clearly suggests that weather sensitive.
Rainfall, temperature and other weather variables affect in many ways both vector
and the pathogens they transmit. The epidemics were a consequence of heavy rains
favoring the active breeding of these mosquito species in urban habitats that
host chikungunya virus (Yadav and Murthy, 2006). Geographical
Information system has become another major tool for public health professionals
to track the status and distribution of health indicators. Epidemiologists,
public health administrators, certified environmental hygienists and other public
health professionals are utilizing GIS to map out the spatial distribution of
various diseases and its variation over space and time. In addition they use
these maps for decision making and design the health policies accordingly. At
present GIS is playing a very important role in public health in many spheres.
In addition, the virus gained the ability to infect a new vector A.
albopictus, enhancing the opportunity for that mosquito concurrently infected
with microfilaria transmit arboviruses more effectively (Zytoon
et al., 1993). Because a large proportion of reported cases of chikungunya
from India belong to areas where the prevalence of filarial parasitic infection
could be modulating the re-emergence of chikungunya Mishra
and Ratho (2006). Chikungunya virus, also known as buggy creek virus belongs
to the Family-Togaviridae and the Genus alpha virus. Chikungunya fever is a
self-limiting viral disease characterized by arthritis mostly involving the
wrist, ankle, knee and small joints of the extremities associated with rashes
and fever (Benenson, 1995). Many question concerning health
and ill-health to space, however the incorporation of geography analysis into
public health science and practice has been slow. A major deterrent has been
the lack of adequate tools for the management and analysis of spatially defined
date, the use of geo-information technology is offering new opportunities for
research and planning public and policy (Loslier, 1995).
GIS has been described as one of the most exciting of the new information technology
(Yasnoff and Sondik, 1999).
Intuitively, GIS can be defined as an information technology that uses to take
new relationship between variables, as one can bring together many different
types of data (i.e., health, resource use/allocation, census, transportation,
etc.). This in turn provides the social and physical context necessary for enhancing
analysis in health planning and policy to emerge (Maguire
et al., 1991). The analysis of spatial data can focus on the relationships
between attribute variables, or on the spatial and space-time dimensions or
a combination of attribute and space/space-time. The methods used in spatial
data analysis can be broadly categorized into those concerned with visualizing
data, those for exploratory data analysis and methods for the development of
statistical models (Bailey and Gatrell, 1995). Globally,
there are many studies proving applicability of remote sensing in vector habitat
identification and for optimization of vector control operations (Hugh-Jones,
1989). Using satellite remote sensing data, identification and categorization
of mosquito larval habitat associated with plant communities, wetlands and other
aquatic locations as well as relationship between land use and land cover categories
have also been reported (Bergquitst, 2001). The temporal
multi-spectral remote sensing data provide a means for understanding varying
degrees of victor born disease incidence with vegetation cover, moisture and
waterlogged areas and associated environmental factors, including social and
economical factors (Sabesan, 2003). In addition three
human trends have to be taken into account: population growth, urbanization
and the growing demand for water and food, these factors indicated the survival
cannot be separated nor can the impacts of climate change on future security
policy be analyzed in isolation (Matouq, 2008). The
main objective of the study was to generate the basic information on the recent
outbreak of chikungunya in the state of Tamil Nadu.
|| Description of the study area
MATERIALS AND METHODS
Study area: Tamil Nadu is a state at the southern tip of India. It is situated in (8 5 13° 35' N and 76 15' 80° 20' E (Fig. 1). It is bordered by Pondicherry, Kerala, Karnataka and Andhra Pradesh. Tamil Nadu has a population of approximately 6, 24,05,679. It is 1,30,058 km2 and comprise 16,317 villages and 832 towns and the area is more epidemic with Chikungunya during 2006. The Chikungunya fever cases and Rainfall data of Tamil Nadu was taken from the Director of Medical Science (DMS) department of economic and statistics in Chennai. The fever cases files that provide statistics on all the districts in the county level for individual month for the period of one year (2006).
Study methods: Two commonly used methods for mapping spatial variation
in disease are maps of relative risk and maps of statistical significance. The
former approach is a popular choice and has the advantage of easy interpretation.
The software GIS Arcview (version 8) was used to plot the data and has the advantage
of easy interpretation. However, such maps tend to display the most extreme
values in areas of small population (Clayton and Kaldor,
1987). The approach, including maps of probabilities, has the problem of
potentially extreme significant level in areas of large population, due to sample
size effects. Alternatively, smoothing methods have been suggested as a compromise,
and are often used as an alternative approach. Smoothing methods were designed
to filter out variability in a data set based on function on the data in surrounding
areas and kernel-based smoothing methods have received much attention in recently
years by Bailey and Gatrell (1995). GIS is highly scaleable
software and as such can handle any volume of data. It can be integrated with
any existing software across a wide range of hardware/operating platform.
RESULTS AND DISCUSSION
Chikungunya is spread by the bite of an Aedes aegypti, humans are thought
to be the major source or reservoir of chikungunya virus for the mosquitoes.
In India, the dominant carrier of chikungunya virus is A. aegypti,
which breeds mainly in stored fresh water in urban and semi-urban environments.
|| Climate forecasts for early warning of favorable conditions
for diseases transmission
Outbreak dynamics characterized by the absence of an animal reservoir and the
ability to spread rapidly among human beings via domestic and peridomestic mosquitoes.
Indian chikungunya outbreak seems to have followed the outbreak in the Indian
Ocean islands and may be related to the heavy tourist traffic between the two
regions. The transmission patterns of these diseases may, therefore, be affected
by ambient rainfall. However, rainfall is only one of many factors that influence
transmission dynamics (Fig. 2).
Chikungunya fever cases of each districts, monthly average of rainfall and total population of each districts in the state of Tamil Nadu during 2006, which was plotted in geographical information system, soft ware Map-Info. Figure 3 shows that chikungunya out-break was high at Namakkal district (11498) followed by Vellore (7666), Krishnagiri (5747), Tirunelveli (5062), Chennai (4569), Coimbatore (4170), Dinidigul (3808) and Ramanathapuram (3265). Chikungunya fever cases were not recorded at Nilgiri (0) and the prevalence was very low at Tiruvannamalai (9) and Thiruvallur (44) districts. In rest of the districts chikungunya outbreak was noticed in different frequencies. The rainfall was recorded in different frequencies and the population of district was very high in Chennai (4343646), Coimbatore (4271856) and Vellore (3477317) and very low in Perambalur (493646) and Nilgiri district (762141) (Table 1). Among the entire district Coimbatore and Vellore ranked high in both chikungunya and rainfall, respectively. So it is clearly understood that rainfall is one of the climatic factor which enables the transmission of CHIK-V virus from mosquitoes to humans at irregular intervals. The intra-outbreak studies, point towards recent changes in the viral genome facilitating the rapid spread and enhanced pathogenecity. The available published scientific literature on chikungunya virus was searched to understand the natural history of this disease, reasons for the current outbreak and the causes behind re-emergence of the virus in India.
The chikungunya virus was first isolated in India in Calcutta in 1963 (Dandawate
et al., 1965). Subsequently, it seems that the virus has 'disappeared'
from the subcontinent (Pavri, 1986). However, outbreaks
of fever caused by chikungunya virus infection in several parts of South India
in 2006 have confirmed the re-emergence of this virus. Chikungunya fever cases
was first recorded in Calcutta in 1963, after that episode, there have been
several reports of chikungunya virus infection in different parts of India.
In Tamil Nadu, we investigated the outbreak in Gowripet area (2006 population:
2,649) of Avadi, a suburban locality of Chennai City where a large number of
persons with fever and joint pain were reported in June 2006 (Kaur
et al., 2006).
|| District map showing different degrees of chikungunya out-breaks
in Tamil Nadu (2006)
However, large scale outbreaks of fever caused by chikungunya virus infection
in several parts of Southern India have confirmed the re-emergence of this virus
(Yadav and Murthy, 2006). Therefore, it should be included
in the differential diagnosis of disease with influenza-like symptoms, especially
when patient present with the triad of fever, rash and joint pains. Although
chikungunya fever is not a fatal disease, it may cause significant morbidity
due to sever and prolonged duration of joint pains. GIS has been extensively
used in natural resource management, public work, transportation and government
but until recently, has been largely ignored in public health and socio-behavioral
research (Albert et al., 2000). They explorer this
further with GIS using statistical analysis and visualization to generate hypotheses
for further study. Findings from traditional epidemiological methods can also
be used to corroborate GIS findings further study and test hypotheses generated
by the GIS (Lewis-Michl et al., 1996). This study
confirms the sudden outbreak of chikungunya fever in Tamil Nadu is because sporadic
vectors transmission of the virus from the Aedes aegypti and Aedes
albopictus mosquitoes under suitable climate. The high density of vector
mosquitoes and suitable wheather conditions like rainfall and temperature which
enables the route of opportunity to the CHIK-V to show their impact.
|| Average rain fall, chikungunya cases and total population
of Tamil Nadu
Like other mosquitoes borne diseases, e.g., dengue fever, avoiding contact
with mosquitoes and maintaining good environmental sanitation can prevent transmission.
A. aegypti already showed increased tolerance to both insecticides, indicating
that a portion of the population has already developed resistance to the insecticides.
If treatment using insecticides is still applied continuously, there is the
possibility that those populations will become resistant in the future (Ahmad
et al., 2007).
Health education programme to improve public awareness of the disease and to
encourage mass participation in basic sanitary measures and source reduction
to prevent breeding of mosquitoes in peridomestic and carelessly discarded containers
should be intensified (Adebote et al., 2006).
Less than 5% of 2, 500 described mosquito species regularly breed in brackish
water, they represent a rather diverse group of species (Balakrishnan
et al., 2011). Researchers have recently concentrated their efforts
on the search of active natural products derived from marine sponges as alternatives
to conventional insecticides. The ethanol extract of Clathria gorgonids
and Callyspongia diffusa were found more effective against A. aegypti
(Sujatha and Joseph, 2011). Vector control measures
include the elimination of potential breeding places of mosquitoes inside and
outside homes, schools and offices. Drums, plastic containers and pails used
to store water should be covered. Discarded natural and artificial containers,
e.g., coconut shells, old tires, empty bottles and cans, should be properly
disposed of. Water in flower vases should be frequently changed. Screening of
sleeping quarters and bedrooms or the use of insect repellents and mechanical
barriers such as mosquito nets help minimize exposure to mosquitoes. Therefore,
continuous monitoring of resistance in the future that consequently might lead
to more severe DF/DHF/CHIKV outbreaks. For the first time, extensive studies
on controlling diseases transmissions by mosquitoes through GIS technology in
Tamil nadu have been undertaken and it provides the basic information for future
studies in the field of epidemiology.
Authors are greatful to Dr. S. John William, Dr. D. Sudarsanam and Dr. M. Selvanayagam, Department of Advanced Zoology and Biotechnology, Loyola College Chennai for their motivation and help during the study period and also special thanks to Rev. Dr. S. Ignacimuthu, s.j. Director and Research Supervisor, Dr. M. Gabriel Paulraj and Dr. S. Kingsley Scientist and Research Supervisor, Entomology Research Institute (ERI), Chennai 600 034, for valuable information and suggestions.
1: Adebote, A.D., J.S. Oniye, S.I. Ndams and K.M. Nache, 2006. The breeding of mosquitoes (Diptera: Culicidae) in peridomestic containers and implication in yellow fever transmission in villages around Zaria, Northern Nigeria. J. Entomol., 3: 180-188.
CrossRef | Direct Link |
2: Ahmad, I., S. Astari and M. Tan, 2007. Resistance of Aedes aegypti (Diptera: Culicidae) in 2006 to pyrethroid insecticides in Indonesia and its association with oxidase and esterase levels. Pak. J. Biol. Sci., 10: 3688-3692.
CrossRef | PubMed | Direct Link |
3: Ahmed, A.M., E.M. Al-Olayan and M.A. Amoudy, 2008. Enhancing the humoral and melanization responses of Aedes aegypti mosquito: A step towards the utilization of immune system against dengue fever. J. Entomol., 5: 305-321.
CrossRef | Direct Link |
4: Albert, D.P., W.M. Gesler and B. Levergood, 2000. Spatial Analysis, GIS and Remote Sensing: Applications in the Health Sciences. 1st Edn., Ann Arbor Press, Chelsea, MI., ISBN-13: 978-1575041018, pp: 217
5: Balakrishnan, S., M. Srinivasan and K. Elumalai, 2011. A survey on mosquitoe diversity in parangipettai coast, Southeast coast of Tamilnadu, India. J. Entomol., 8: 259-266.
CrossRef | Direct Link |
6: Bailey, T.C. and A.C. Gatrell, 1995. Interactive Spatial Data Analysis. Longman Scientific & Technical, Harlow, Essex, UK., ISBN: 9780582244931, Pages: 413
7: Bergquist, N.R., 2001. Vector-borne parasitic diseases: New trends in data collection and risk assessment. Acta Trop., 79: 13-20.
8: Clayton, D. and J. Kaldor, 1987. Empirical bayes estimates of age-standardized relative risks for use in disease mapping. Biometrics, 43: 671-681.
Direct Link |
9: Dandawate, C.N., K.V. Thiruvengadam, V. Kalyanasundaram, J. Rajagopal and T.R. Rao, 1965. Serological survey in Madras city with special reference to chikungunya. Indian J. Med. Res., 53: 707-714.
10: Benenson, A.S., 1995. Control of Communicable in Man. 16th Edn., American Public Health Association, USA
11: Hugh-Jones, M., 1989. Application of remote sensing to the identification of the habitats of parasites and disease vectors. Parasitol. Today, 5: 244-251.
12: Pavri, K., 1986. Disappearance of chikungunya virus from India and South East Asia. Trans. R. Soc. Trop. Med. Hyg., 80: 491-491.
13: Kaur, P., M. Ponniah, M.V. Murhekar, V. Ramachandran and R. Ramachandran et al., 2008. Chikungunya outbreak, South India.2006 Emerging Infectious Dis., 14: 1623-1625.
Direct Link |
14: Loslier, L., 1995. Geographical Information System (GIS) from a health perspective. Proceedings of the International Workshop held in Colombo, Sept. 5-10, Sri Lanka, Ottawa, Canada: International Development Research Centre, pp: 13-20
15: Lewis-Michl, E.L., J.M. Melius, L.R. Kaleenbach, C.L. Ju and T.O. Talbot et al., 1996. Breast cancer risk and residence near industry or traffic in Nassau and Suffolk Counties, Long Island, New York. Arch. Environ. Health, 51: 255-265.
16: Maguire, D.J., M.F. Goodchild and D.W. Rhind, 1991. Geographic Information Systems. Longman Scientific and Technical, Harlow, UK
17: Matouq, M., 2008. Predicting the impact of global warming on the Middle East region: Case study on Hashemite Kingdom of Jordan using the application of geographical information system. J. Applied Sci., 8: 462-470.
CrossRef | Direct Link |
18: Mishra, B. and R.K. Ratho, 2006. Chikungunya re-emergence: Possible mechanisms. Lancet, 368: 918-918.
19: Sabesan, S., 2003. Forecasting mosquito abundance to prevent Japanese encephalitis. Curr. Sci., 84: 1172-1173.
Direct Link |
20: Sujatha, S. and B. Joseph, 2011. Effect of few marine sponges and its biological activity against Aedes aegypti Linn. Musca domestica (Linnaeus, 1758) (Diptera: Culicidae). J. Fish. Aquat. Sci., 6: 170-177.
CrossRef | Direct Link |
21: Yasnoff, W.A. and E.J. Sondik, 1999. Geographic Information System (GIS) in public health practice in the new millennium. J. Public Health Manage. Practice, 5: 8-11.
Direct Link |
22: Yadav, J.S. and U.S.N. Murthy, 2006. A special issue on Chikungunya. Envis News Lett., 3: 1-9.
Direct Link |
23: Zytoon, E.M., H.I. El-Belbasi and T. Matsumura, 1993. Transovarial transmission of Chikungunya virus by Aedes albopictus mosquitoes ingesting microfilaria of Dirofiliaria immitis under laboratory control. Microbial. Immunol., 37: 419-421.