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Quantifying the Effect of Public Activity Intervention Policies on COVID-19 Pandemic Containment Using Epidemiologic Data From 145 Countries

OBJECTIVES: Most countries have adopted public activity intervention policies to control the coronavirus disease 2019 (COVID-19) pandemic. Nevertheless, empirical evidence of the effectiveness of different interventions on the containment of the epidemic was inconsistent. METHODS: We retrieved time-...

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Detalles Bibliográficos
Autores principales: Sun, Jichao, Zheng, Yefeng, Liang, Wenhua, Yang, Zifeng, Zeng, Zhiqi, Li, Tiegang, Luo, Junjie, Alexander Ng, Man Tat, He, Jianxing, Zhong, Nanshan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Academy of Allergy, Asthma & Immunology 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8651490/
https://www.ncbi.nlm.nih.gov/pubmed/35500944
http://dx.doi.org/10.1016/j.jval.2021.10.007
Descripción
Sumario:OBJECTIVES: Most countries have adopted public activity intervention policies to control the coronavirus disease 2019 (COVID-19) pandemic. Nevertheless, empirical evidence of the effectiveness of different interventions on the containment of the epidemic was inconsistent. METHODS: We retrieved time-series intervention policy data for 145 countries from the Oxford COVID-19 Government Response Tracker from December 31, 2019, to July 1, 2020, which included 8 containment and closure policies. We investigated the association of timeliness, stringency, and duration of intervention with cumulative infections per million population on July 1, 2020. We introduced a novel counterfactual estimator to estimate the effects of these interventions on COVID-19 time-varying reproduction number (R(t)). RESULTS: There is some evidence that earlier implementation, longer durations, and more strictness of intervention policies at the early but not middle stage were associated with reduced infections of COVID-19. The counterfactual model proved to have controlled for unobserved time-varying confounders and established a valid causal relationship between policy intervention and R(t) reduction. The average intervention effect revealed that all interventions significantly decrease R(t) after their implementation. R(t) decreased by 30% (22%-41%) in 25 to 32 days after policy intervention. Among the 8 interventions, school closing, workplace closing, and public events cancellation demonstrated the strongest and most consistent evidence of associations. CONCLUSIONS: Our study provides more reliable evidence of the quantitative effects of policy interventions on the COVID-19 epidemic and suggested that stricter public activity interventions should be implemented at the early stage of the epidemic for improved containment.