Abstract
AbstractReliable testing data for new infectious diseases like COVID‐19 is scarce in developing countries making it difficult to rapidly diagnose spatial disease transmission and identify at‐risk areas. We propose a method that uses readily available data on bi‐lateral migration channels combined with COVID‐19 cases at respective migrant destinations to construct a spatially oriented risk index. We find significant and consistent association between our measure and various types of outcomes including actual COVID‐19 cases and deaths, indices of government policy responses, and community mobility patterns. Results suggest that future pandemic models should incorporate migration‐linkages to predict regional socio‐economic and health risk exposure.
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