Mass Migration and COVID-19 Epidemic in China During Spring Festival 2020

Abstract

The global pandemic of the coronavirus infection COVID-19, which broke out in early 2020, has become a serious test for all of humanity and for China. The epidemic was accompanied by mass migration in the most populous country in the world ahead of the Chunjie Spring Festival (春节) on January 25, 2020. This further aggravated the situation. Scientists from China and other countries have conducted large-scale studies using Big Data to establish the relationship between the number of migrants and the total number of confirmed cases. This article aims to determine the contribution of these works, carried out using methods such as scale-invariant network, correlation analysis and Bayesian approach, and provide recommendations for further research on the implementation of scientific innovations to solve migration problems in a pandemic. The paper provides an overview of the main ideas of foreign scientists, examines the research methods they used, identifies their advantages and disadvantages, presents recommendations for further research on the role of migration in the spread of infectious diseases. The novelty lies in the review of similar methods that were not previously used in similar studies by Russian demographers. In particular, the use of Big Data allowed scientists to establish that the population that left Wuhan was the main source of transmission of the virus to other cities and regions of China. The scale-invariant network method allowed for an analysis of the temporal and spatial distribution of cases, which shows that in Hubei province, where the largest number of cases and deaths were recorded, their growth slowed down rapidly. In other “hot spots”, on the contrary, the number of cases was initially low, but the increase in the number of cases at the beginning of the epidemic continued. The application of the Bayesian approach in research allowed scientists to prove that more attention should be paid to eliminating the negative socio-economic consequences of the epidemic among migrants as a particularly vulnerable group and to provide them with timely medical assistance, including psychological.