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Quantifying the impacts of human mobility restriction on the spread of coronavirus disease 2019: an empirical analysis from 344 cities of China.
Tan, Jing; Zhao, Shao-Yang; Xiong, Yi-Quan; Liu, Chun-Rong; Huang, Shi-Yao; Lu, Xin; Thabane, Lehana; Xie, Feng; Sun, Xin; Li, Wei-Min.
  • Tan J; Chinese Evidence-Based Medicine Center, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China.
  • Zhao SY; Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario L8S 4L8, Canada.
  • Xiong YQ; Biostatistics Unit, St Joseph's Healthcare-Hamilton, Ontario L8S 4L8, Canada.
  • Liu CR; School of Economics, Sichuan University, Chengdu, Sichuan 610041, China.
  • Huang SY; Chinese Evidence-Based Medicine Center, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China.
  • Lu X; Chinese Evidence-Based Medicine Center, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China.
  • Thabane L; Chinese Evidence-Based Medicine Center, National Clinical Research Center for Geriatrics, West China Hospital, Sichuan University, Chengdu, Sichuan 610041, China.
  • Xie F; College of Systems Engineering, National University of Defense Technology, Changsha, Hunan 410073, China.
  • Sun X; Department of Global Public Health, Karolinska Institute, Stockholm, Sweden.
  • Li WM; Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Ontario L8S 4L8, Canada.
Chin Med J (Engl) ; 134(20): 2438-2446, 2021 Oct 07.
Article in English | MEDLINE | ID: covidwho-1462529
ABSTRACT

BACKGROUND:

Since the outbreak of coronavirus disease 2019 (COVID-19), human mobility restriction measures have raised controversies, partly because of the inconsistent findings. An empirical study is promptly needed to reliably assess the causal effects of the mobility restriction. The purpose of this study was to quantify the causal effects of human mobility restriction on the spread of COVID-19.

METHODS:

Our study applied the difference-in-difference (DID) model to assess the declines of population mobility at the city level, and used the log-log regression model to examine the effects of population mobility declines on the disease spread measured by cumulative or new cases of COVID-19 over time after adjusting for confounders.

RESULTS:

The DID model showed that a continual expansion of the relative declines over time in 2020. After 4 weeks, population mobility declined by -54.81% (interquartile range, -65.50% to -43.56%). The accrued population mobility declines were associated with the significant reduction of cumulative COVID-19 cases throughout 6 weeks (ie, 1% decline of population mobility was associated with 0.72% [95% CI 0.50%-0.93%] reduction of cumulative cases for 1 week, 1.42% 2 weeks, 1.69% 3 weeks, 1.72% 4 weeks, 1.64% 5 weeks, and 1.52% 6 weeks). The impact on the weekly new cases seemed greater in the first 4 weeks but faded thereafter. The effects on cumulative cases differed by cities of different population sizes, with greater effects seen in larger cities.

CONCLUSIONS:

Persistent population mobility restrictions are well deserved. Implementation of mobility restrictions in major cities with large population sizes may be even more important.
Subject(s)

Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Experimental Studies / Observational study Limits: Humans Country/Region as subject: Asia Language: English Journal: Chin Med J (Engl) Year: 2021 Document Type: Article Affiliation country: CM9.0000000000001763

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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Experimental Studies / Observational study Limits: Humans Country/Region as subject: Asia Language: English Journal: Chin Med J (Engl) Year: 2021 Document Type: Article Affiliation country: CM9.0000000000001763