Abstract
Objectives: In this data collation study, we aimed to provide a comprehensive database describing the epidemic trends and responses during the first wave of coronavirus disease 2019 (COVID-19) throughout the main provinces in China. Methods: From mid-January to March 2020, we extracted publicly available data regarding the spread and control of COVID-19 from 31 provincial health authorities and major media outlets in mainland China. Based on these data, we conducted descriptive analyses of the epidemic in the six most-affected provinces. Results: School closures, travel restrictions, community-level lockdown, and contact tracing were introduced concurrently around late January but subsequent epidemic trends differed among provinces. Compared with Hubei, the other five most-affected provinces reported a lower crude case fatality ratio and proportion of critical and severe hospitalised cases. From March 2020, as the local transmission of COVID-19 declined, switching the focus of measures to the testing and quarantine of inbound travellers may have helped to sustain the control of the epidemic. Conclusions: Aggregated indicators of case notifications and severity distributions are essential for monitoring an epidemic. A publicly available database containing these indicators and information regarding control measures is a useful resource for further research and policy planning in response to the COVID-19 epidemic.
Originalsprog | Engelsk |
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Tidsskrift | International Journal of Infectious Diseases |
Vol/bind | 102 |
Sider (fra-til) | 463-471 |
Antal sider | 9 |
ISSN | 1201-9712 |
DOI | |
Status | Udgivet - 2021 |
Udgivet eksternt | Ja |
Bibliografisk note
Funding Information:We acknowledge Joint Centre Funding from the UK Medical Research Council and Department for International Development [grant number MR/R015600/1 ]. This study was also supported by the National Institute for Health Research Health Protection Research Unit in Modelling Methodology , the Abdul Latif Jameel Foundation , and the EDCTP2 programme supported by the European Union .
Funding Information:
We acknowledge Joint Centre Funding from the UK Medical Research Council and Department for International Development [grant number MR/R015600/1]. This study was also supported by the National Institute for Health Research Health Protection Research Unit in Modelling Methodology, the Abdul Latif Jameel Foundation, and the EDCTP2 programme supported by the European Union.
Publisher Copyright:
© 2020 The Author(s)