Impact of socioeconomic status，population mobility and control measures on COVID-10 development in major cities of China.
- Author:
Shu LI
1
;
Sicong WANG
1
;
Yong ZHU
1
;
Sisi WANG
1
;
Changzheng YUAN
1
;
Xifeng WU
1
;
Shuyin CAO
1
;
Xiaolin XU
1
;
Chen CHEN
1
;
Yuanqing YE
1
;
Wenyuan LI
1
;
Hao LEI
1
;
Kejia HU
1
;
Xin XU
1
;
Hui ZHU
1
Author Information
- Publication Type:Journal Article
- Keywords: Cluster analysis; Control measures; Coronavirus disease 2019；China; Population flows; Socioeconomic status
- MeSH: COVID-19; China/epidemiology*; Cities; Humans; SARS-CoV-2; Social Class
- From: Journal of Zhejiang University. Medical sciences 2021;50(1):52-60
- CountryChina
- Language:English
- Abstract: :To evaluate the impact of socioeconomic status，population mobility，prevention and control measures on the early-stage coronavirus disease 2019 (COVID-19) development in major cities of China. : The rate of daily new confirmed COVID-19 cases in the 51 cities with the largest number of cumulative confirmed cases as of February 19，2020 (except those in Hubei province) were collected and analyzed using the time series cluster analysis. It was then assessed according to three aspects，that is, socioeconomic status，population mobility，and control measures for the pandemic. : According to the analysis on the 51 cities，4 development patterns of COVID-19 were obtained，including a high-incidence pattern (in Xinyu)，a late high-incidence pattern (in Ganzi)，a moderate incidence pattern (in Wenzhou and other 12 cities)，and a low and stable incidence pattern (in Hangzhou and other 35 cities). Cities with different types and within the same type both had different scores on the three aspects. : There were relatively large difference on the COVID-19 development among different cities in China，possibly affected by socioeconomic status，population mobility and prevention and control measures that were taken. Therefore，a timely public health emergency response and travel restriction measures inside the city can interfere the development of the pandemic. Population flow from high risk area can largely affect the number of cumulative confirmed cases.
