Risk maps and spatial models for clinical infectious disease decision-making

Abstract

Risk maps and spatial models provide key information about the endemicity and spread of infectious diseases. Novel data streams and statistical techniques, with the aid of artificial intelligence, create the opportunity for modern risk maps. To ensure that these tools are useful for clinical decision-making, we need to understand how risk maps are used, how they are developed, and how they can be improved. This will be especially important for zoonotic, vector-borne, and environmental infectious diseases in the era of environmental change and globalization.