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Reductions of Migrant Population Reduces the Number of COVID-19 Epidemic: A Case Study in China
28 Pages Posted: 5 May 2020
More...Abstract
Background: The novel coronavirus disease (COVID-19) broke out worldwide in 2020, with more than 80 000 people infected in China. The purpose of this paper was to find out the impact of population migration on the epidemic. We hope to provide data support and suggestions for control measures in various epidemic arears.
Methods: Generalized additive model (GAM) was utilized to model the relationship between migrant population and the number of confirmed cases of COVID-19 (covering 75 major cities). The difference of spatial distribution was analyzed through spatial autocorrelation and hot spot analysis in ArcGIS software, and mapped.
Findings: GAM model demonstrated that the number of confirmed cases of COVID-19 were correlated with the population migration and regional population density (R2adj = 0·873, Deviance explained = 89·6%), and the number of confirmed cases will increase with the growth of these variables (population migration index, urban travel intensity and population density ). The predictive results showed that the total number of confirmed cases of COVID-19 will reach 27 483 (95% CI: 16 074, 48 097) due to the population movement after returning to work (the actual number was 23 177). The average increase in 73 cities was 85·53% (95% CI: 19·53%, 189·81%). Meanwhile, the high prevalence areas in Hubei province and its surrounding areas will be further expanded.
Interpretation: The reduced population mobility and population density caused by the delayed resumption of work can greatly slow down the spread of the epidemic. We recommend that all epidemic areas should suspend the transportation between cities, comprehensively and strictly control the population travel and decrease the population density, so as to reduce the spread of COVID-19. Moreover, it is absolutely necessary not to return to work and school early until the regional epidemic is completely under control.
Funding Statement: The study was supported by grants from the Peking University Start-up Grant (71015Y2088).
Declaration of Interests: The authors claim that the researchers in this study have no conflict of interest.
Keywords: COVID-19; migration; GAM; spatial distribution
Suggested Citation: Suggested Citation