SPATIAL CORRELATIONS OF MALARIA INCIDENCE HOTSPOTS WITH ENVIRONMENTAL FACTORS IN ASSAM, NORTH EAST INDIA
Keywords: Malaria, GIS, Spatial autocorrelation, Moran’s I index, G statistics, vector habitat, Hotspot
Abstract. Malaria is endemic and a major public health problem in north east (NE) region of India and contributes about 8-12 % of India's malaria positives cases. Historical morbidity pattern of malaria in terms of API (Annual Parasite Incidence) in the state of Assam has been used for delineating the malaria incidence hotspots at health sub centre (HSC) level. Strong spatial autocorrelation (p < 0.01) among the HSCs have been observed in terms of API (Annual Parasite Incidence). Malaria incidence hot spots in the state could be identified based on General G statistics and tested for statistical significance. Spatial correlation of malaria incidence hotspots with physiographic and climatic parameters across 6 agro-climatic zones of the state reveals the types of land cover pattern and the range of elevation contributing to the malaria outbreaks. Analysis shows that villages under malaria hotspots are having more agricultural land, evergreen/semi-evergreen forests with abundant waterbodies. Statistical and spatial analyses of malaria incidence showed a significant positive correlation with malaria incidence hotspots and the elevation (p < 0.05) with villages under malaria hotspots are having average elevation ranging between 17 to 240 MSL. This conforms to the characteristics of two dominant mosquito species in the state Anopheles minimus and An. baimai that prefers the habitat of slow flowing streams in the foot hills and in forest ecosystems respectively.