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α: calibrated so average coauthorship-adjusted count equals average raw count
The initial spread of COVID-19 halted economic activity as countries around the world restricted the mobility of their citizens. As a result, many migrant workers returned home, spreading the virus across borders. We investigate the relationship between migrant movements and the spread of COVID-19 using district-day-level data from Bangladesh, India, and Pakistan (the 1st, 6th, and 7th largest sources of international migrant workers). We find that during the initial stage of the pandemic, a 1 SD increase in prior international out-migration relative to the district-wise average in India and Pakistan predicts a 48% increase in the number of cases per capita. In Bangladesh, however, the estimates are not statistically distinguishable from zero. Domestic out-migration predicts COVID-19 diffusion in India, but not in Bangladesh and Pakistan. In all three countries, the association of COVID-19 cases per capita and measures of international out-migration increases over time. The results show how migration data can be used to predict coronavirus hotspots. More broadly, the results are consistent with large cross-border negative externalities created by policies aimed at containing the spread of COVID-19 in migrant-receiving countries.