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Original Research

Evidence-Based Framework and Implementation of China’s Strategy in Combating COVID-19

ORCID Icon, &
Pages 1989-1998 | Published online: 07 Oct 2020
 

Abstract

Introduction

In less than two months, the COVID-19 outbreak in China was controlled through the stringent strategies of screening and isolation. This article aims to use empirical data from all cases from a prefecture-level city of China to introduce and examine the feasibility and efficiency of the screening and isolation strategies and how these were essential in combatting the COVID-19 outbreak.

Methods

For this retrospective study, all confirmed COVID-19 patients were recruited from the Taizhou prefecture-level city of Zhejiang province, China.

Results

Of the city’s total population, 24% were screened for COVID-19 and isolated at home or designated locations for two weeks. From these, a total of 146 confirmed cases of COVID-19 were analysed. Of all cases, 51% were traced from Wuhan, and 21% of patients were in close contact with confirmed cases from outside of the city. Initially, 13% of all patients reported having no clear symptoms, while 42% of patients presented with fever and/or other symptoms. Compared with local patients, new arrivals to the city had fewer days between their exposure and the development of symptoms of COVID-19 (P<0.001), and fewer days from the time they developed symptoms to the confirmation of COVID-19 (P<0.001), respectively.

Conclusion

This study has fully confirmed that controlling the COVID-19 outbreak through screening and isolation is effective, efficient, and essential. The evidence-based framework and implementation of China’s strategy to combat COVID-19 can explain how China contained the COVID-19 outbreak in a short time period. This study offers important references and implications for containing the COVID-19 pandemic in the global community.

Disclosure

The authors report no conflicts of interest for this work.

Additional information

Funding

This study was funded by Shanghai Philosophy and Social Science Foundation (2018BGL021), and Shanghai Shuguang Program (18SG13).