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The relationship between the migrant population’s migration network and the risk of covid-19 transmission in china—empirical analysis and prediction in prefecture-level cities

Author/s
Fan C.,
Cai T.,
Gai Z.,
Wu Y.
Year
Language
English
Document Type
Article
Source Title
International Journal of Environmental Research and Public Health
Publisher
MDPI AG

Description

The outbreak of COVID-19 in China has attracted wide attention from all over the world. The impact of COVID-19 has been significant, raising concerns regarding public health risks in China and worldwide. Migration may be the primary reason for the long-distance transmission of the disease. In this study, the following analyses were performed. (1) Using the data from the China migrant population survey in 2017 (Sample size = 432,907), a matrix of the residence–birthplace (R-B matrix) of migrant populations is constructed. The matrix was used to analyze the confirmed cases of COVID-19 at Prefecture-level Cities from February 1–15, 2020 after the outbreak in Wuhan, by calculating the probability of influx or outflow migration. We obtain a satisfactory regression analysis result (R2 = 0.826–0.887, N = 330). (2) We use this R-B matrix to simulate an outbreak scenario in 22 immigrant cities in China, and propose risk prevention measures after the outbreak. If similar scenarios occur in the cities of Wenzhou, Guangzhou, Dongguan, or Shenzhen, the disease transmission will be wider. (3) We also use a matrix to determine that cities in Henan province, Anhui province, and Municipalities (such as Beijing, Shanghai, Guangzhou, Shenzhen, Chongqing) in China will have a high risk level of disease carriers after a similar emerging epidemic outbreak scenario due to a high influx or outflow of migrant populations. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.

Migration angle
Region/Country (by coverage)
Index Keywords

covid-19; disease transmission; empirical analysis; epidemic; health risk; immigrant population; prediction; social network; urban area; viral disease; Article; birthplace; China; city; controlled study; coronavirus disease 2019; data analysis; disease carrier; epidemic; geographic distribution; human; infection prevention; infection risk; major clinical study; migrant; migration; population research; prediction; probability; questionnaire; regression analysis; residential area; rural area; sample size; severe acute respiratory syndrome; simulation; virus transmission; Betacoronavirus; biological model; Coronavirus infection; disease transmission; health survey; pandemic; population dynamics; risk factor; travel; virus pneumonia; China; Betacoronavirus; China; Cities; Coronavirus Infections; Disease Outbreaks; Disease Transmission, Infectious; Epidemics; Humans; Models, Biological; Pandemics; Pneumonia, Viral; Population Dynamics; Population Surveillance; Risk Factors; Transients and Migrants; Travel