Spatiotemporal patterns and influencing factors of human migration networks in China during COVID-19

Abstract

The social lockdowns and strict control measures initiated to combat the COVID-19 pandemic have had an impact on human migration. In this study, big data was used to analyze spatial patterns of population migration in 369 Chinese cities during the COVID-19 outbreak and to identify determinants of population migration. We found that the overall migration intensity decreased by 39.87% compared to the same period in 2019 prior to the COVID-19 outbreak. COVID-19 severely affected human migration. The public holidays and weekends have impacted human migration from the perspective of time scale. The spatial pattern of China's population distribution presents a diamond structure that is dense in the east and sparse in the west, which is bounded by the Hu line and the cities such as Beijing, Shanghai, Guangzhou and Chengdu as nodes to connect. There is a strong consistency between the population distribution center and the level of urban development. The urban human migration network is centered on provincial capitals or municipalities at the regional scale, showing a prominent ''center-periphery'' structure. COVID-19 dispersed the forces of human migration in time and changed the direction of human migration in space. But it did not change the pattern of national migration. The most critical factors influencing mass migration are income levels and traditional culture. This study reveals the impacts of major public health emergencies on conventional migration patterns and provides a scientific theoretical reference for COVID-19 prevention and control.

Keywords

• Human migration
• COVID-19, Influencing factors
• Baidu big data