Predicting malaria infection in Gambian children from satellite data and bed net use surveys: The importance of spatial correlation in the interpretation of results

In line with the renewed World Health Organization Global Malaria Control S trategy, we have advocated the use of satellite imagery by control services to provide environmental information for malaria stratification, monitorin g, and early warning. To achieve this operationally, appropriate methodolog ies must be developed for integrating environmental and epidemiologic data into models that can be used by decision-makers for improved resource alloc ation. Using methodologies developed for the Famine Early Warning Systems a nd spatial statistics, we show a significant association between age relate d malaria infection in Gambian children and the amount of seasonal environm ental greenness as measured using the normalized difference vegetation inde x derived from satellite data. The resulting model is used to predict chang es in malaria prevalence rates in children resulting from different bed net control scenarios.