The environmental Risk Factors Significant to Anopheles Species Vector Mosquito Profusion, P.falciparum, P.vivax Parasite Development, and Malaria Transmission, Using Remote Sensing and Gis: Review Article

Abstract

The prevalence of spatial distribution and the seasonal variation of malaria epidemics in India have beenmost significantly determined by the environmental variables including climate, landscape, and the manmade factors. The risk factors are acting as decisive factors on the development of Anopheles genusmosquitoes. The landscape environments (slope, altitude, land use / land covers), human settlementsproximity to permanent water bodies of mosquito breeding habitats (lake, pool, streams, rivers, tanks etc),agricultural wet rice cultivation land, land use dynamics, population density, urbanization, increase of manwater resource projects. The coefficient model of climate determinants (rainfall and temperature) with themosquito abundance are highly associated with the Normalized Difference Vegetation Index (NDVI) valuederived from multispectral satellite data, and is useful in the assess the ground situation of Anophelinemalaria vector mosquito larval abundance 7 days in advance in the wet irrigation rice fields using remotelysensed data. The result of logistic regression model provides the spatial agreement between the observedand predicted values of larval index within buffer zones 2.5 KM around the trap location in the wetcultivation rice fields much appropriate for Anopheline vector mosquito breeding. However, transmissionof Plasmodium vivax requires a minimum average temperature 15.0°C and transmission by Plasmodiumfalciparum, requires a minimum average temperature of 19.0°C. The P.vivax vector requires 15 to 25 daysto complete the parasite development cycle within the temperature range between 15°C to 20°C, the relativehumidity for both species requires range between 55% to 80% and its life cycle may be completed within 6to 10 days, if the temperature range remains within 25°C to 30°C. Multivariate analysis could be predictedaccurately the relative abundance of malaria vectors breeding habitats suitability and epidemics. The malariacases in the endemic districts and the relative abundance of the malaria vectors are directly controlled by theclimate variables with >85 % accuracy.