  This study explored how population mobility flows form commuting networks
across US counties and influence the spread of COVID-19. We utilized 3-level
mixed effects negative binomial regression models to estimate the impact of
network COVID-19 exposure on county confirmed cases and deaths over time. We
also conducted weighting-based analyses to estimate the causal effect of
network exposure. Results showed that commuting networks matter for COVID-19
deaths and cases, net of spatial proximity, socioeconomic, and demographic
factors. Different local racial and ethnic concentrations are also associated
with unequal outcomes. These findings suggest that commuting is an important
causal mechanism in the spread of COVID-19 and highlight the significance of
interconnected of communities. The results suggest that local level mitigation
and prevention efforts are more effective when complemented by similar efforts
in the network of connected places. Implications for research on inequality in
health and flexible work arrangements are discussed.
