How Policy Mix Choices Affect the COVID-19 Pandemic Response Outcomes in Chinese Cities: An Empirical Analysis

Int J Environ Res Public Health. 2022 Jul 1;19(13):8094. doi: 10.3390/ijerph19138094.

Abstract

Since January 2020, the COVID-19 pandemic has caused millions of deaths and has posed a major public health threat worldwide. Such a massive and complex crisis requires quick and comprehensive policy responses. We developed an empirical dataset of policy mixes that included 4915 policies across 36 Chinese cities and investigated the relationships between the policy design choices and the COVID-19 pandemic response outcomes of a city. Using topic modeling and ordinary least squares regression analysis, we found considerable variation among cities in the compositions and design features of their policy mixes. Our analysis revealed that restriction measures did not significantly influence limiting the spread of the pandemic, but they were negatively correlated with the economic growth rate. By contrast, health protection measures greatly contributed to controlling viral spread. Intensive socioeconomic support reduced the occurrence of secondary disasters. The most effective policy strategy to deal with the COVID-19 pandemic appears to be a comprehensive policy design with a mix of restrictions, health protection measures, and socioeconomic support policies accompanied by a timely lockdown. Our empirical findings can help to improve pandemic policy design and contribute to generating broader lessons for how local governments should deal with similar crises in the future.

Keywords: COVID-19; compound crisis; pandemic management; policy design; policy mix; policy outcomes.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • COVID-19* / epidemiology
  • China / epidemiology
  • Cities / epidemiology
  • Communicable Disease Control
  • Humans
  • Pandemics / prevention & control
  • Policy
  • SARS-CoV-2

Grants and funding

This research was funded by the National Social Science Foundation of China (Grant No. 19BZZ082) and Zhejiang Science Foundation for Distinguished Young Scholars (Grant No. LR21G030001).