The Effects of Stringent and Mild Interventions for Coronavirus Pandemic

Ting Tian, Jianbin Tan, Wenxiang Luo, Yukang Jiang, Minqiong Chen, Songpan Yang, Canhong Wen, Wenliang Pan and Xueqin Wang

Journal of the American Statistical Association, 2021, vol. 116, issue 534, 481-491

Abstract: The pandemic of COVID-19 has caused severe public health consequences around the world. Many interventions of COVID-19 have been implemented. It is of great public health and social importance to evaluate the effects of interventions in the pandemic of COVID-19. With the help of a synthetic control method, the regression discontinuity, and a state-space compartmental model, we evaluated the treatment and stagewise effects of the intervention policies. We found statistically significant treatment effects of broad stringent interventions in Wenzhou and mild interventions in Shanghai to subdue the epidemic’s spread. If those reduction effects were not activated, the expected number of positive individuals would increase by 2.18 times on February 5, 2020, for Wenzhou and 7.69 times on February 4, 2020, for Shanghai, respectively. Alternatively, regression discontinuity elegantly identified the stringent (p-value:

Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:taf:jnlasa:v:116:y:2021:i:534:p:481-491

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DOI: 10.1080/01621459.2021.1897015

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