Leveraging big data for public health: Mapping malaria vector suitability in Malawi with Google Earth Engine.

ABSTRACT: In an era of big data, the availability of satellite-derived global climate, terrain, and land cover imagery presents an opportunity for modeling the suitability of malaria disease vectors at fine spatial resolutions, across temporal scales, and over vast geographic extents. Leveraging cloud-based geospatial analytical tools, we present an environmental suitability model that considers water resources, flow accumulation areas, precipitation, temperature, vegetation, and land cover. In contrast to predictive models generated using spatially and temporally discontinuous mosquito presence information, this model provides continuous fine-spatial resolution information on the biophysical drivers of suitability. For the purposes of this study the model is parameterized for Anopheles gambiae s.s.

SUBMITTER: Frake AN 

PROVIDER: S-EPMC7402481 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature