Impacts of social and economic factors on the transmission of coronavirus disease (COVID-19) in China

Yun Qiu; Xi Chen; Wei Shi

in city c and date t. τ denotes the preceding first or second week. d cr is the distance between cities c and r in log, and r =c d −1 crȳ τ rt is the inverse distance weighted average of new infections in other cities. We include lagged y ct up to 14 days based on the estimates of the durations of the infectious period and the incubation period in the literature 5 . We take average of lagged y ct by week, asȳ τ ct = 1 7 7 s=1 y ct−7(τ −1)−s andz τ t = 1 7 7 s=1 z t−7(τ −1)−s . In addition, a notable feature of the COVID-19 epidemic is that it was originated in one city (Wuhan) and most of the early cases outside Wuhan can be traced to previous contacts with persons in Wuhan. To model how the virus spreads to other cities from its source, we include the number of new confirmed cases in Wuhan in the model (z τ t ). x ct includes weather controls, city, and day fixed effects 6 . ct is the error term. Standard errors are clustered within provinces. In a simplified model, we consider only within city transmissions,