What Are the Reasons for the Different COVID-19 Situations in Different Cities of China? A Study from the Perspective of Population Migration
Abstract
:1. Introduction
2. Materials and Methods
2.1. Data
2.2. Methods
3. Results and Discussion
3.1. Geographical Distribution of Confirmed COVID-19 Cases
3.2. Estimation and Analysis of Population Migration from Wuhan
3.3. Model Results and Analysis
3.4. Effects of Demographic Characteristics on the Spread of COVID-19
4. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
- Chan, J.F.; Yuan, S.; Kok, K.H.; To, K.K.; Chu, H.; Yang, J.; Xing, F.; Liu, J.; Yip, C.C.; Poon, R.W.; et al. A familial cluster of pneumonia associated with the 2019 novel coronavirus indicating person-to-person transmission: A study of a family cluster. Lancet 2020, 395, 514–523. [Google Scholar] [CrossRef] [Green Version]
- Mask-Wearing Governors of Hubei and Wuhan in the Press Conference: More than 5 Million People Left Wuhan. Available online: http://www.chinanews.com/gn/2020/01-27/9070527.shtml (accessed on 27 March 2020).
- Du, Z.; Wang, L.; Cauchemez, S.; Xu, X.; Wang, X.; Cowling, B.J.; Meyers, L.A. Risk for Transportation of Coronavirus Disease from Wuhan to Other Cities in China. Emerg. Infect. Dis. 2020, 26, 1049–1052. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Wu, J.T.; Leung, K.; Bushman, M.; Kishore, N.; Niehus, R.; de Salazar, P.M.; Cowling, B.J.; Lipsitch, M.; Leung, G.M. Estimating clinical severity of, COVID-19 from the transmission dynamics in Wuhan, China. Nat. Med. 2020, 26, 506–510. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Wu, J.T.; Leung, K.; Leung, G.M. Nowcasting and forecasting the potential domestic and international spread of the 2019-nCoV outbreak originating in Wuhan, China: A modelling study. Lancet 2020, 395, 689–697. [Google Scholar] [CrossRef] [Green Version]
- Zhan, C.; Tse, C.K.; Fu, Y.; Lai, Z.; Zhang, H. Modeling and Prediction of the 2019 Coronavirus Disease Spreading in China Incorporating Human Migration Data. PLoS ONE 2020, 15, e0241171. [Google Scholar] [CrossRef] [PubMed]
- Chinazzi, M.; Davis, J.T.; Ajelli, M.; Gioannini, C.; Litvinova, M.; Merler, S.; Piontti, A.P.; Mu, K.; Rossi, L.; Sun, K.; et al. The effect of travel restrictions on the spread of the 2019 novel coronavirus (COVID-19) outbreak. Science 2020. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Zhang, R.; Li, Y.; Zhang, A.L.; Wang, Y.; Molina, M.J. Identifying airborne transmission as the dominant route for the spread of, COVID-19. Proc. Natl. Acad. Sci. USA 2020. [Google Scholar] [CrossRef] [PubMed]
- Liu, L. Emerging study on the transmission of the Novel Coronavirus (COVID-19) from urban perspective: Evidence from China. Cities 2020. [Google Scholar] [CrossRef]
- Conversation by Writing|Niu Xinyi|The Negative Effects of Large-Scale Inter-City Population Migration during the Development of Urban Agglomerations Shall Be Paid Attention. Available online: https://mp.weixin.qq.com/s/PPmnIFYC_3YgkPMkzBkzUQ (accessed on 17 December 2020).
- Sirkeci, I.; Yucesahin, M.M. Coronavirus and Migration: Analysis of Human Mobility and the Spread of, COVID-19. Migr. Lett. 2020, 17, 379–398. [Google Scholar] [CrossRef] [Green Version]
- 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. [Google Scholar] [CrossRef] [Green Version]
- Jia, J.S.; Lu, X.; Yuan, Y.; Xu, G.; Jia, J.; Christakis, N.A. Population flow drives spatio-temporal distribution of, COVID-19 in China. Nature 2020, 1–5. [Google Scholar] [CrossRef]
- Fan, C.; Liu, L.; Guo, W.; Yang, A.; Ye, C.; Ji, M.; Ren, M.; Xu, P.; Long, H.; Wang, Y. Prediction of Epidemic Spread of the 2019 Novel Coronavirus Driven by Spring Festival Transportation in China: A Population-Based Study. Int. J. Environ. Res. Public Health 2020, 17, 1679. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Kraemer, M.U.; Yang, C.H.; Gutierrez, B.; Wu, C.H.; Klein, B.; Pigott, D.M.; Du Plessis, L.; Faria, N.R.; Li, R.; Hanage, W.P.; et al. The effect of human mobility and control measures on the, COVID-19 epidemic in China. Science 2020, 368, 493–497. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Baidu Map Insight Platform. Available online: https://qianxi.baidu.com (accessed on 1 August 2020).
- Baidu Maps. Available online: https://map.baidu.com (accessed on 1 August 2020).
- Li, R.; Pei, S.; Chen, B.; Song, Y.; Zhang, T.; Yang, W.; Shaman, J. Substantial undocumented infection facilitates the rapid dissemination of novel coronavirus (SARS-CoV2). Science 2020. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Li, J.; He, S. Population migration, information dissemination efficiency and epidemic prevention and control: Evidence from, COVID-19. J. Cent. Univ. Financ. Econ. 2020, 4, 116–128. (In Chinese) [Google Scholar]
- Liu, S.; Qin, Y.; Xie, Z.; Zhang, J. The Spatio-Temporal Characteristics and Influencing Factors of Covid-19 Spread in Shenzhen, China—An Analysis Based on 417 Cases. Int. J. Environ. Res. Public Health 2020, 17, 7450. [Google Scholar] [CrossRef] [PubMed]
- Shi, Q.; Liu, T. Should internal migrants be held accountable for spreading, COVID-19? Environ. Plan. A 2020, 52, 695–697. [Google Scholar] [CrossRef]
- Wuhan Railway: Three Stations in Wuhan Sent 299,600 Passengers on 22 January 2020. Available online: http://news.sina.com.cn/c/2020-01-23/doc-iihnzhha4240400.shtml (accessed on 23 December 2020).
- Zhong Nanshan: Human to Human Transmission of SARS-CoV-2 Can Be Confirmed! Available online: https://xw.qq.com/cmsid/20200121A009XU00 (accessed on 20 December 2020).
- A Visit to Jinan University by Masters: Professor Edward Glaeser from Harvard University Talks about the Influences of Epidemic Situation on Cities. Available online: https://mp.weixin.qq.com/s/TGqK-QyOh9PpJhtDMYoPKQ (accessed on 20 December 2020).
- China Urban Planning Society Provides Suggestions for 2020 UN High Level Forum on Sustainable Development. Available online: http://www.cast.org.cn/art/2020/7/10/art_590_127464.html (accessed on 10 December 2020).
- Why Does Wenzhou, a City That Is Thousands of Miles away from Wuhan, Become the Most Serious City Outside Hubei Province? Available online: https://www.sohu.com/a/369876571_119038 (accessed on 1 December 2020).
- Xiang, Y.; Wang, S. Spatial relationship between the spread of, COVID-19 and population migration and its implications for classified governance of urban public health in China. Trop. Geogr. 2020, 40, 408–421. (In Chinese) [Google Scholar]
- The Double Pressure of Wenzhou’s “Closed City”: 180,000 Businessmen in Wuhan and 330,000 People from Hubei Province to Work in Wenzhou. Available online: https://baijiahao.baidu.com/s?id=1657592321414041198 (accessed on 4 December 2020).
- The Closer to Wuhan, the Higher the Incidence Rate of COVID-19 Is? The Reality May Be More Complicated. Available online: https://mp.weixin.qq.com/s/GENDjbB6z3JgDxlVptMaaA (accessed on 1 December 2020).
- Chongqing, Please Don’t Keep a Low Profile. Available online: https://mp.weixin.qq.com/s/B1nR0kJG9RGKM4-W-PQ36w (accessed on 3 December 2020).
- Luo, S.; Morone, F.; Sarraute, C.; Travizano, M.; Makse, H.A. Inferring personal economic status from social network location. Nat. Commun. 2017. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Henan’s Hard-Core Epidemic Prevention Measures Have Taught a Profound Lesson To Many Places! Available online: https://mp.weixin.qq.com/s/AsETj7lQ0mQyThxB-e4CMQ (accessed on 24 December 2020).
- Henan Province Deserves Salute, This Is the Epidemic Prevention Mobilization Capability We Are Supposed to Have. Available online: https://mp.weixin.qq.com/s/hNSO8iCdLPbjtdjf-Wb1Yw (accessed on 16 December 2020).
- Zhao, P. Some Villages in Henan Province Were Isolated by Blocking Roads with Soil Piles and Personnel on Duty Were Observed at All Intersections in order to Prevent the Spread of COVID-19. Available online: http://www.bjnews.com.cn/news/2020/01/26/679902.html (accessed on 13 December 2020).
- Chen, Y.T.; Yen, Y.F.; Yu, S.H.; Su, E.C.Y. An Examination on the Transmission of, COVID-19 and the Effect of Response Strategies: A Comparative Analysis. Int. J. Environ. Res. Public Health 2020, 17, 5687. [Google Scholar] [CrossRef]
- Tian, H.; Liu, Y.; Li, Y.; Wu, C.H.; Chen, B.; Kraemer, M.U.; Li, B.; Cai, J.; Xu, B.; Yang, Q.; et al. An investigation of transmission control measures during the first 50 days of the, COVID-19 epidemic in China. Science 2020, 368, 638–642. [Google Scholar] [CrossRef] [PubMed] [Green Version]
Variable | Definition | Unit |
---|---|---|
Disease | Accumulated number of confirmed COVID-19 cases | Persons |
Migration | Population migration from Wuhan between 10 and 26 January 2020 | Persons |
Dist | Road distance from Wuhan | Kilometers |
Pergdp | GDP per capita | Yuan |
Population | Resident population at the end of 2018 | 10,000 persons |
Hospital | Number of hospital beds per 1000 residents | - |
Pop_density | Population density | Persons/km2 |
Road | Road area per capita | m2 |
Garbage | Domestic garbage collected and transported per capita | kg |
Wastewater | Annual quantity of wastewater per capita | m3 |
Greenspace | Public recreational green space per capita | m2 |
Capital_city | Is the city the capital of the province? (Yes = 1, No = 0) | N.A. |
Variable | (1) | (2) | (3) | (4) | (5) | (6) | (7) | (8) | (9) | (10) |
---|---|---|---|---|---|---|---|---|---|---|
(1) Migration | 1.000 | |||||||||
(2) Dist | −0.591 | 1.000 | ||||||||
(3) Pergdp | 0.070 | 0.223 | 1.000 | |||||||
(4) Population | 0.154 | 0.207 | 0.091 | 1.000 | ||||||
(5) Hospital | 0.058 | 0.283 | 0.503 | 0.212 | 1.000 | |||||
(6) Pop_density | 0.112 | −0.011 | −0.268 | 0.271 | −0.036 | 1.000 | ||||
(7) Road | −0.121 | −0.204 | −0.001 | −0.180 | −0.254 | −0.242 | 1.000 | |||
(8) Garbage | 0.012 | 0.204 | 0.307 | −0.081 | 0.038 | −0.258 | 0.190 | 1.000 | ||
(9) Wastewater | −0.097 | 0.196 | 0.425 | −0.005 | 0.130 | −0.148 | 0.153 | 0.359 | 1.000 | |
(10) Greenspace | −0.251 | 0.184 | 0.240 | 0.044 | −0.131 | −0.278 | 0.328 | 0.157 | 0.175 | 1.000 |
Variable | Full Sample | Subsample without Hubei Province | ||||||
---|---|---|---|---|---|---|---|---|
(1) | (2) | (3) | (4) | (5) | (6) | (7) | (8) | |
23 Jan | 8 Feb | 17 Feb | 3 Mar | 23 Jan | 8 Feb | 17 Feb | 3 Mar | |
Migration | −0.071 ** | 0.082 *** | 0.079 *** | 0.080 *** | −0.072 ** | 0.060 *** | 0.058 *** | 0.058 *** |
(−2.22) | (5.41) | (5.20) | (5.23) | (−2.26) | (4.16) | (3.98) | (4.00) | |
Dist | 0.015 | −0.115 *** | −0.117 *** | −0.114 *** | −0.057 | −0.070 * | −0.067 * | −0.064 |
(0.17) | (−3.15) | (−3.08) | (−2.98) | (−0.62) | (−1.79) | (−1.66) | (−1.55) | |
Pergdp | −0.086 | 0.124 *** | 0.119 *** | 0.115 *** | −0.049 | 0.119 *** | 0.112 *** | 0.109 *** |
(−0.77) | (3.28) | (3.32) | (3.19) | (−0.46) | (3.14) | (3.15) | (3.03) | |
Population | −0.020 | 0.096 *** | 0.086 *** | 0.090 *** | −0.020 | 0.132 *** | 0.124 *** | 0.128 *** |
(−0.27) | (4.16) | (3.83) | (3.88) | (−0.29) | (5.06) | (4.90) | (4.94) | |
Hospital | 0.074 | −0.059 ** | −0.044 | −0.041 | 0.018 | −0.074 *** | −0.059 ** | −0.055 ** |
(0.62) | (−2.04) | (−1.65) | (−1.49) | (0.16) | (−2.65) | (−2.27) | (−2.10) | |
Pop_density | −0.005 | −0.008 | −0.009 | −0.015 | 0.035 | 0.012 | 0.010 | 0.004 |
(−0.06) | (−0.27) | (−0.35) | (−0.57) | (0.44) | (0.43) | (0.37) | (0.15) | |
Road | 0.103 | −0.009 | −0.016 | −0.007 | 0.137 | 0.001 | −0.005 | 0.005 |
(1.03) | (−0.26) | (−0.50) | (−0.20) | (1.31) | (0.02) | (−0.16) | (0.16) | |
Garbage | −0.045 | 0.018 | 0.031 | 0.022 | −0.004 | 0.065 | 0.074 | 0.065 |
(−0.25) | (0.26) | (0.49) | (0.34) | (−0.02) | (0.92) | (1.14) | (0.97) | |
Wastewater | −0.250 | 0.046 | 0.024 | 0.020 | −0.371 *** | 0.046 | 0.027 | 0.023 |
(−1.64) | (0.97) | (0.52) | (0.43) | (−2.67) | (1.01) | (0.60) | (0.51) | |
Greenspace | −0.029 | 0.010 | 0.031 | 0.041 | −0.094 | −0.001 | 0.018 | 0.029 |
(−0.13) | (0.12) | (0.45) | (0.60) | (−0.42) | (−0.01) | (0.26) | (0.41) | |
Capital_city | −0.143 | −0.003 | −0.006 | −0.007 | −0.109 | 0.017 | 0.012 | 0.011 |
(−1.10) | (−0.08) | (−0.16) | (−0.18) | (−0.83) | (0.39) | (0.30) | (0.26) | |
_cons | 3.670 ** | −0.930 * | −0.689 | −0.619 | 3.737 ** | −1.693 *** | −1.465 *** | −1.402 *** |
(2.57) | (−1.75) | (−1.45) | (−1.29) | (2.56) | (−3.10) | (−2.95) | (−2.83) | |
N | 79 | 131 | 131 | 131 | 73 | 120 | 120 | 120 |
R2 | 0.260 | 0.708 | 0.719 | 0.708 | 0.305 | 0.621 | 0.632 | 0.619 |
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Zheng, Y.; Huang, J.; Yin, Q. What Are the Reasons for the Different COVID-19 Situations in Different Cities of China? A Study from the Perspective of Population Migration. Int. J. Environ. Res. Public Health 2021, 18, 3255. https://doi.org/10.3390/ijerph18063255
Zheng Y, Huang J, Yin Q. What Are the Reasons for the Different COVID-19 Situations in Different Cities of China? A Study from the Perspective of Population Migration. International Journal of Environmental Research and Public Health. 2021; 18(6):3255. https://doi.org/10.3390/ijerph18063255
Chicago/Turabian StyleZheng, Yanting, Jinyuan Huang, and Qiuyue Yin. 2021. "What Are the Reasons for the Different COVID-19 Situations in Different Cities of China? A Study from the Perspective of Population Migration" International Journal of Environmental Research and Public Health 18, no. 6: 3255. https://doi.org/10.3390/ijerph18063255