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An investigation of transmission control measures during the first 50 days of the COVID-19 epidemic in China.
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Abstract
Abstract Respiratory illness caused by a novel coronavirus (COVID-19) appeared in China during December 2019. Attempting to contain infection, China banned travel to and from Wuhan city on 23 January and implemented a national emergency response. Here we evaluate the spread and control of the epidemic based on a unique synthesis of data including case reports, human movement and public health interventions. The Wuhan shutdown slowed the dispersal of infection to other cities by an estimated 2.91 days (95%CI: 2.54-3.29), delaying epidemic growth elsewhere in China. Other cities that implemented control measures pre-emptively reported 33.3% (11.1-44.4%) fewer cases in the first week of their outbreaks (13.0; 7.1-18.8) compared with cities that started control later (20.6; 14.5-26.8). Among interventions investigated here, the most effective were suspending intra-city public transport, closing entertainment venues and banning public gatherings. The national emergency response delayed the growth and limited the size of the COVID-19 epidemic and, by 19 February (day 50), had averted hundreds of thousands of cases across China. One sentence summary Travel restrictions and the national emergency response delayed the growth and limited the size of the COVID-19 epidemic in China.
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“recent international studies have reported increased symptoms of anxiety, depression, sleep disorders, and psychological distress during lockdown (4–10)”
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Metadata
- Authors
- Tian, H., Liu, Y., Li, Y., Wu, C.-H., Chen, B., Kraemer, M. U. G., Li, B., Cai, J., Xu, B., Yang, Q., Wang, B., Yang, P., Cui, Y., Song, Y., Zheng, P., Wang, Q., Bjornstad, O. N., Yang, R., Grenfell, B. T., Pybus, O. G., & Dye, C.
- Affiliations
- Beijing Normal University (CN)
- University of Southampton (GB)
- Department of Land, Air and Water Resources, University of California Davis, Davis, CA, USA.
- Boston Children's Hospital (US)
- Tsinghua University (CN)
- Beijing Center for Disease Prevention and Control (CN)
- Beijing Institute of Microbiology and Epidemiology (CN)
- University of Hong Kong (HK)
- Peking University (CN)
- Center for Infectious Disease Dynamics, Department of Biology, Pennsylvania State University, University Park, PA, USA.
- National Institutes of Health (US)
- University of Oxford (GB)
- Corresponding author
- Tian, Huaiyu
- Yang, Ruifu
- Grenfell, Bryan T.
- Pybus, Oliver G.
- Dye, Christopher
- ORCID
- Venue
- Science
- Published
- 2020-05-08
- Volume
- 368
- Issue
- 6491
- Pages
- 638-642
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- PMC
- PMC7164389
- OpenAlex
- W3013188135
- Cited by
- 2,010
- References
- 32
- Citations by year
- 2026: 45 · 2025: 75 · 2024: 129 · 2023: 214 · 2022: 386 · 2021: 627 · 2020: 532
- FWCI
- 70.26
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Science (publishedVersion, cc-by)
- medRxiv (acceptedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- The HKU Scholars Hub (University of Hong Kong) (publishedVersion)
- ePrints Soton (University of Southampton) (acceptedVersion)
- Greater South Information System
- Funders
- National Natural Science Foundation of China (81673234)
- Young Elite Scientist Sponsorship Program by CAST (2018QNRC001)
- Beijing Natural Science Foundation (JQ18025)
- Beijing Advanced Innovation Program for Land Surface Science (None)
- Topics
- Physical Sciences › Mathematics › Modeling and Simulation › COVID-19 epidemiological studies
- Social Sciences › Sociology and Political Science › COVID-19 Prevention and Impact
- Health Sciences › Medicine › Infectious Diseases › SARS-CoV-2 and COVID-19 Research
- Keywords
- COVID-19 pandemic, Wuhan lockdown, public health interventions, epidemic spread, human mobility
- MeSH terms
- Betacoronavirus, COVID-19, SARS-CoV-2, China, Communicable Disease Control, Humans, Pneumonia, Viral, Regression Analysis, Travel, Models, Statistical, Public Health Practice, Incidence, Coronavirus Infections, Epidemics, Pandemics
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