Reductions of migrant population reduces the number of COVID-19 epidemic: a case study in China

The novel coronavirus disease (COVID-19) broke out worldwide in 2020. The purpose of this paper was to find out the impact of migrant population on the epidemic, aiming to provide data support and suggestions for control measures in various epidemic areas. Generalized additive model was utilized to model the relationship between migrant population and the cumulative number of confirmed cases of COVID-19. The difference of spatial distribution was analyzed through spatial autocorrelation and hot spot analysis. Generalized additive model demonstrated that the cumulative number of confirmed cases was positively correlated with migration index and population density. The predictive results showed that, if no travel restrictions are imposed on the migrant population as usual, this number of COVID-19 would have reached 27,483 (95% CI 16,074, 48,097; the actual number was 23,177). The increase in one city (Jian) would be 577.23% (95% CI 322.73%, 972.73%) compared with the real confirmed cases of COVID-19. The average increase in 73 cities was 85.53% (95% CI 19.53%, 189.81%). Among the migration destinations, the number of cases in cities of Hubei province, Chongqing, and Beijing was relatively high, and there were large-scale high-prevalence clusters in eastern Hubei province. Without restrictions on migration, the high prevalence areas in Hubei province and its surrounding areas will be further expanded. The reduced population mobility and population density can greatly slow down the spread of the epidemic. All epidemic areas should suspend the transportation between cities, strictly control the population travel, and decrease the population density, so as to reduce the spread of COVID-19. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11356-021-13195-z.