The Role of Spatial Statistics in the Control and Elimination of Neglected Tropical Diseases in Sub-Saharan Africa: A Focus on Human African Trypanosomiasis, Schistosomiasis and Lymphatic Filariasis.
Disease control and elimination programmes can benefit greatly from accurate information on the spatial variability of disease risk, particularly when risk is highly spatially heterogeneous. Due to advances in statistical methodology, coupled with the increased availability of geospatial technology, this information is becoming increasingly accessible. In this chapter we describe recent advancements in spatial methods associated with the analysis of disease data measured at the point-level and demonstrate their application to the control and elimination of neglected tropical diseases (NTDs). We further provide information on spatially referenced data sources and software that can be used to create NTD risk maps, concentrating on those that can be freely obtained. Examples relating to three NTDs affecting populations in sub-Saharan Africa are presented throughout the chapter, i.e., human African trypanosomiasis, schistosomiasis and lymphatic filariasis. These three diseases, with differing routes of transmission, control methods and level of spatial heterogeneity, demonstrate the flexibility and applicability of the methods described.
Liverpool School of Tropical Medicine, Liverpool, United Kingdom. Electronic address: Michelle.Stanton@lstmed.ac.uk.
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D017954:Africa South of the Sahara / Q000453:epidemiology; D000818:Animals; D004605:Elephantiasis, Filarial / Q000469:parasitology / Q000517:prevention & control*; D006801:Humans; D058069:Neglected Diseases / Q000469:parasitology / Q000517:prevention & control*; D012552:Schistosomiasis / Q000469:parasitology / Q000517:prevention & control*; D014330:Tropical Medicine; D014353:Trypanosomiasis, African / Q000469:parasitology / Q000517:prevention & control*
Disease mapping; GIS; Geostatistics; Human African trypanosomiasis; Lymphatic filariasis; MaxEnt; Neglected tropical diseases; Schistosomiasis; Spatial statistics; Species distribution models