Improving geospatial models of risk for vector-borne, zoonotic diseases
Public health surveillance data are often incomplete, particularly where resources are lacking, but geospatial models can help to fill the gaps by providing estimates where data are sparse. By combining information on locations where diseases have been recorded with geographic data on environmental...
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University of Oxford
2017
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| Online Access: | https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.748879 |