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
Abstract
:1. Introduction
2. Methods
2.1. Data
2.1.1. China Migrant Population Dynamic Survey 2017 (CMDS 2017)
2.1.2. COVID-19 Infections Confirmed the Data from Prefecture-Level Cities
2.1.3. Cofactors for Disease Transmission
2.2. Residence–Birthplace Probability Matrix (R-B Matrix)
2.3. Correlation between the Transmission of the Disease and the Birthplace Probability of the Migrant Population by the R-B matrix
2.4. Prediction of Risk Levels in Prefecture-Level Cities and Similar Immigrant Cities and Outbreak Scenarios
3. Results
3.1. Construction of the R-B Matrix
3.2. Bivariate Correlation Test and Regression Results
3.3. Results of Prediction of Risk Levels in Prefecture-Level Cities with Outbreak Scenarios in Similar Immigrant Cities
3.4. Prefecture-Level City Risk Ranking of Disease Transmission
4. Discussion
4.1. COVID-19 Transmission in China is Highly Correlated with Factors that Return Migrants to Their Birthplace
4.2. Different Emergency Management and Control Plans for Different Disease Outbreak Scenarios in Immigrant Cities
4.3. Policy Intervention and Disease Prevention in the Important Migrant Birthplace Regions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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t1 | t2 | t3 | t4 | t5 | t6 | t7 | t8 | t9 | t10 | t11 | t12 | t13 | t14 | t15 | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
0.157 ** | 0.146 ** | 0.142 * | 0.136 * | 0.129 * | 0.128 * | 0.128 * | 0.127 * | 0.126 * | 0.125 * | 0.125 * | 0.120 * | 0.117 * | 0.117 * | 0.117 * | |
0.232 ** | 0.220 ** | 0.212 ** | 0.200 ** | 0.187 ** | 0.182 ** | 0.177 ** | 0.175 ** | 0.173 ** | 0.172 ** | 0.170 ** | 0.162 ** | 0.158 ** | 0.155 ** | 0.154 ** | |
0.836 ** | 0.849 ** | 0.857 ** | 0.883 ** | 0.907 ** | 0.915 ** | 0.917 ** | 0.915 ** | 0.915 ** | 0.915 ** | 0.916 ** | 0.913 ** | 0.915 ** | 0.916 ** | 0.918 ** | |
0.543 ** | 0.534 ** | 0.514 ** | 0.500 ** | 0.477 ** | 0.466 ** | 0.463 ** | 0.461 ** | 0.458 ** | 0.456 ** | 0.453 ** | 0.447 ** | 0.445 ** | 0.439 ** | 0.436 ** |
t1 | t2 | t3 | t4 | t5 | t6 | t7 | t8 | t9 | t10 | t11 | t12 | t13 | t14 | t15 | |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Beta | Beta | Beta | Beta | Beta | Beta | Beta | Beta | Beta | Beta | Beta | Beta | Beta | Beta | Beta | |
0.003 | −0.003 | 0.003 | 0.008 | 0.017 | 0.024 | 0.029 | 0.030 | 0.031 | 0.031 | 0.034 | 0.034 | 0.034 | 0.038 | 0.040 | |
0.119 ** | 0.108 ** | 0.102 * | 0.082 * | 0.063 | 0.056 | 0.049 | 0.048 | 0.047 | 0.046 | 0.044 | 0.036 | 0.032 | 0.029 | 0.027 | |
0.715 *** | 0.734 *** | 0.751 *** | 0.786 *** | 0.823 *** | 0.834 *** | 0.837 *** | 0.836 *** | 0.836 *** | 0.837 *** | 0.838 *** | 0.839 *** | 0.842 *** | 0.846 *** | 0.849 *** | |
0.303 *** | 0.295 *** | 0.270 *** | 0.250 *** | 0.221 *** | 0.206 *** | 0.204 *** | 0.202 *** | 0.200 *** | 0.198 *** | 0.195 *** | 0.191 *** | 0.190 *** | 0.183 *** | 0.179 *** | |
R2 | 0.826 | 0.835 | 0.836 | 0.865 | 0.881 | 0.887 | 0.887 | 0.883 | 0.882 | 0.880 | 0.880 | 0.883 | 0.885 | 0.885 | 0.887 |
N | 329 |
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Fan, C.; Cai, T.; Gai, Z.; Wu, Y. 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. Int. J. Environ. Res. Public Health 2020, 17, 2630. https://doi.org/10.3390/ijerph17082630
Fan C, Cai T, Gai Z, Wu Y. 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. International Journal of Environmental Research and Public Health. 2020; 17(8):2630. https://doi.org/10.3390/ijerph17082630
Chicago/Turabian StyleFan, Chenjing, Tianmin Cai, Zhenyu Gai, and Yuerong Wu. 2020. "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" International Journal of Environmental Research and Public Health 17, no. 8: 2630. https://doi.org/10.3390/ijerph17082630