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Masimalai Palaniyandi
At present, I am working as a Senior Technical Officer (Health Geography/ Spatial Epidemiology, Environmental Remote Sensing and GIS) at the ICMR-Vector Control Research Centre, Pondicherry Indian Council of Medical Research, Ministry of Health and Family Welfare, Government of India
Address: Dr.M.PALANIYANDI. M.Sc., M.Tech., Ph.D.,
Senior Technical Officer (GIS and Remote Sensing, Health Geography),
ICMR-Vector Control Research Centre (VCRC),
(A Permanent Research Unit of Indian Council of Medical Research)
Indira Nagar, Puducherry-605006, India
E-mail: smp.geog@gmail.com
Address: Dr.M.PALANIYANDI. M.Sc., M.Tech., Ph.D.,
Senior Technical Officer (GIS and Remote Sensing, Health Geography),
ICMR-Vector Control Research Centre (VCRC),
(A Permanent Research Unit of Indian Council of Medical Research)
Indira Nagar, Puducherry-605006, India
E-mail: smp.geog@gmail.com
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Background: The Indian sub-continent has not only wealthy landscapes environment to support huge population, but also has big challenging problems of vector borne disease epidemics across the country. India has become host for all kinds of virus of malaria, dengue, chikungunya, and JE, and also endemic host for filariasis parasites. The burden of vector borne disease is increasing day by day; and therefore, the both intervention measures of both mosquito vector control and the treatment to prevent the disease transmission through the appropriate control strategy in most efficient way. The implementation of conventional method of vector control in the field has significant effect, however, the problem is not manageable and it has been increased steadily. Therefore, the present study is designed for choosing the remote sensing and GIS for mapping the geographical distribution of vector borne diseases, and to study the environmental aspects of the vector borne diseases for 6 decades in India, and a geo-spatial analysis to study the both vector ecology and disease epidemics, and hence, to arrive the probability of spatial prediction of vector borne disease transmission risk in India.
Materials and Methods: The present study is designed for digital mapping of vector borne disease prevalence in the country for the past 58 years (1955 to 2012). The Remote sensing and GIS has been significantly developed for ecological modeling with special emphasis on vectors and vector borne disease epidemics. The Arc View 3.2, Arc View Spatial analysis and Arc View image analyst, GIS software used to create a systematic grid sampling method for conducting the reconnaissance survey and mapping mosquito breeding surface maps. GARMIN 12XL GPS was used to collect the mosquito reconnaissance survey for mosquito vectors in the city. A systematic grid sampling was applied to conduct a rapid survey for mapping Aedes species mosquitogenic condition in the urban areas and the site coordinates of houses information with breeding habitats positive in the grid sectors was collected using GPS. The Indian satellite data (IRS LISS-II, and LISS-III) was used to mapping the use/ land cover of metropolitan area, mapping of mosquitogenic condition, and linked with vector borne disease epidemic transmission. The Indian remote sensing IRS LISS-I, data and IRS WiFS remote sensing data was analyzed, using the maximum likelihood classification for land use land cover classification, and mapping of potential breeding habits of Malaria and JE vectors in India. The mosquito potential breeding surface of malaria, dengue, chikungunya, JE and filariasis was calculated for the each ward and which was mapped with graduated colors.
Result and Discussion: The image classification of the spectral signature of the satellite data imported in to the GIS platform to create the buffer zones of the average adult mosquito flight range of 2.5 km radius around the breeding habitats for mapping the breeding habitats and describing the areas at risk of disease transmission. Land use / land cover dynamics, urban sprawl and irregular growth of urban development and industrial growths are fueled to the development of suitable environment fuelling for malaria, JE, and dengue epidemics and also providing conducing environment for malaria and filariasis endemic. The coefficient model of rainfall and temperature with the mosquito abundance are highly correlated with the normalized difference vegetation index (NDVI), and it is useful in the estimation of mosquito larval abundance and used to predict adult abundance 7 days in advance and also estimating Anopheline malaria vector mosquito abundance in the mosquito habitats of rice fields using remote sensing spectral signatures. The results of logistic regression model provides the spatial agreement between the observed and predicted values of larval index within a buffer around the trap location of rice fields which suitable for vector breeding of malaria and JE. Discriminant analysis could able to correctly distinguish between villages with high and low vector abundance, with an overall accuracy of 90%. Regression results found both transitional swamp and unmanaged pasture proportions to be predictive of vector abundance during the wet season. The virtual GPS under the GIS umbrella was used to conduct a rapid survey with 0.5km distance interval (grid sampling procedures) for assessing the mosquitogenic condition and for mapping the sectors positives for dengue and chikungunya vector mosquitoes (Aedes aegypti or Ae. albopictus) breeding habitats (water storage vessels, plastic and cement containers, tires, plastic cups, coconut cells, tree holes, flower vessels, fridge, stone grinder, etc.,) with accurate site specifications, and the mean value of positive habitats was analyzed by quintiles method for mapping the field situation. The remote sensing data was used for landscape determinants of anopheline mosquito larval habitats. Since, the range of monsoon temperature and the relative humidity has the good agreement with the profusion of mosquito’s vector breeding with respect to space and time. The vegetation indices have the distinctiveness of high sensitivity to soil background, which alters the local environment to vector abundance (sand fly, the vector of Visceral Leishmaniasis / Kala-azar) and disease transmission. Climate and soil types have been progressively affect the vegetation growth and density, and then the conditions on the surrounding environment. Geographical information systems (GIS) and remote sensing were used to identify important geographical risk factors and stratify a region into different areas of transmission risk, thereby providing a guideline to mapping the areas under the risk of visceral leishmaniasis transmission in India. The present study shows that spatial agreement was existed between the environmental variables and the vector borne disease epidemic transmission, and thus, the remote sensing and GIS tool has been used to mapping disease transmission risk zones.
Conclusion: The integrated hybrid remote sensing and GIS techniques was used to mapping the vector breeding potential areas vulnerable to risk of disease transmission and is provided the possible information on reliable estimates of and mapping of malaria, filariasis, JE, and dengue vector breeding habitats, and facilitate to estimate the people at risk of vector borne disease transmission. And perhaps, provides the disease epidemiological information along with geo-coordinates of site specific combined with multispectral satellite data of land use / land cover. It is concluded that remote sensing, GPS, and GIS are effectively useful to identify, delineate and mapping of vector mosquitoes potential breeding surface areas and studying the mosquitogenic conditions in the urban agglomeration, and used to control and management of the vector borne disease transmission, perhaps, may also be GIS based surveillance is the best solution for epidemic control and management of the present situation epidemic in the country.