Modelling and prediction of malaria vector distribution in Bangladesh from remote-sensing data

Abstract

Epidemic malaria cases and satellite-based vegetation health (VH) indices were investigated to be used as predictors of malaria vector activities in Bangladesh. The VH indices were derived from radiances, measured by the Advanced Very High Resolution Radiometer (AVHRR) on National Oceanic and Atmospheric Administration (NOAA) afternoon polar orbiting satellites. Two indices characterizing moisture and thermal conditions were investigated using correlation and regression analysis applied to the number of malaria cases recorded in the entire Bangladesh region and three administrative divisions (Chittagong, Sylhet and Dhaka) during 1992–2001. It is shown that during the cooler months (November to March), when mosquitoes are less active, the correlation between number of malaria cases and two investigated indices was near zero. From April, when the mosquito activity season starts, the correlation increased, reaching a maximum value of 0.5–0.8 by the middle of the high season (June to July), reducing thereafter to zero by the beginning of the cool season in November. Following these results, regressional equations for the number of malaria cases as a function of VH indices were built and tested independently. They showed that, in the main malaria administrative division (Chittagong) and the entire Bangladesh region, the regressional equations can be used for early prediction of malaria development.