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Background In most developing economies particularly in Africa, more people are likely to die of HIV/AIDS and malaria compared to other diseases. HIV/AIDS tends to be superimposed on the long standing malaria burden particularly in sub-Saharan Africa. The detection and understanding of spatial overlaps in disease occurrence is important for integrated and targeted disease control. Integrated disease...
Accurate modelling of the geographic distribution of disease vectors is an important step towards developing strategies for effective control of vector borne diseases. In this study, we used maximum entropy (Maxent) to develop a spatially explicit model to predict the habitat of a malaria causing vector, Anopheles arabiensis, based on key environmental factors. Our results show that altitude combined...
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