GH010-12
Identifying environmental risk factors for malaria in different geographic contexts

Monday, 14 December 2020: 10:33
Virtual
Andrea Hess1, Dawn M Nekorchuk2, Justin Davis2, Abere Mihretie3, Adem Agmas Ahmed4, Mastewal Worku5 and Michael C Wimberly2, (1)University of Oklahoma, Department of Geography and Environmental Sustainability, Norman, OK, United States, (2)University of Oklahoma, Geography and Environmental Sustainability, Norman, OK, United States, (3)Health, Development, and Anti-Malaria Association, Addis Ababa, Ethiopia, (4)Malaria Control and Elimination partnership in Africa, Bahir Dar, Ethiopia, (5)Amhara Public Health Institute, Bahir Dar, Ethiopia
Abstract:
Despite global intervention efforts, malaria remains a major public health concern in many parts of the world. New strategies to target interventions rely on spatially explicit information about disease transmission risk. Because the transmission of mosquito borne diseases is influenced by environmental conditions, environmental data are often used to predict malaria risk. However, the relationships between the environmental and malaria transmission are not universal across different geographic regions and therefore require a context-dependent understanding.

In this study, we investigated differences in the responses of malaria cases to environmental variation depending on geographic context. Our study area encompassed two landscapes within the Amhara region in Ethiopia: one located primarily in the plains south of lake Tana (1700 – 3000 m elevation) and one located along the escarpment of the Blue Nile River (1000 – 3600 m elevation).

We studied annual malaria cases from 197 kebeles (sub-districts with an average area of 58km2) for the years 2014 to 2017. We used boosted regression trees to analyze spatiotemporal variation of P. falciparum and P. vivax malaria cases in relation to climate, human settlement patterns, land cover, and topography.

We used geospatial datasets derived from Earth-observing satellites to characterize environmental variation and studied how these factors influence the spatial and temporal patterns of malaria occurrence. Measured variables included land surface temperature from MODIS, rainfall from the Global Precipitation Mission, spectral indices derived from MODIS, a settlement classification based on very-high resolution PlanetScope data, a land cover classification based on Landsat, and topographic indices derived from SRTM elevation.

Settlement structure played an important role in malaria occurrence in both landscapes. Climatic factors were also important, with relative risk following a precipitation gradient in the area by lake Tana and following a temperature gradient in the area along the Blue Nile River escarpment. Irrigated agriculture did not influence malaria transmission. Our research suggests that studies aiming to understand malaria-environmental relationships should be geographic context specific so they can account for such differences.

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