Bhatia, Sangeeta; Imai, Natsuko; Cuomo-Dannenburg, Gina; Baguelin, Marc; Boonyasiri, Adhiratha; Cori, Anne; Cucunubá, Zulma; Dorigatti, Ilaria; FitzJohn, Rich; Fu, Han; +17 more... Gaythorpe, Katy; Ghani, Azra; Hamlet, Arran; Hinsley, Wes; Laydon, Daniel; Nedjati-Gilani, Gemma; Okell, Lucy; Riley, Steven; Thompson, Hayley; van Elsland, Sabine; Volz, Erik; Wang, Haowei; Wang, Yuanrong; Whittaker, Charles; Xi, Xiaoyue; Donnelly, Christl A; Ferguson, Neil M; (2020) Estimating the number of undetected COVID-19 cases among travellers from mainland China. Wellcome open research, 5. p. 143. ISSN 2398-502X DOI: https://doi.org/10.12688/wellcomeopenres.15805.3
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Abstract
Background: As of August 2021, every region of the world has been affected by the COVID-19 pandemic, with more than 196,000,000 cases worldwide. Methods: We analysed COVID-19 cases among travellers from mainland China to different regions and countries, comparing the region- and country-specific rates of detected and confirmed cases per flight volume to estimate the relative sensitivity of surveillance in different regions and countries. Results: Although travel restrictions from Wuhan City and other cities across China may have reduced the absolute number of travellers to and from China, we estimated that up to 70% (95% CI: 54% - 80%) of imported cases could remain undetected relative to the sensitivity of surveillance in Singapore. The percentage of undetected imported cases rises to 75% (95% CI 66% - 82%) when comparing to the surveillance sensitivity in multiple countries. Conclusions: Our analysis shows that a large number of COVID-19 cases remain undetected across the world. These undetected cases potentially resulted in multiple chains of human-to-human transmission outside mainland China.
Item Type | Article |
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Faculty and Department | Faculty of Epidemiology and Population Health > Dept of Infectious Disease Epidemiology & Dynamics (2023-) |
PubMed ID | 34632083 |
Elements ID | 154342 |
Official URL | http://dx.doi.org/10.12688/wellcomeopenres.15805.1 |
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Licence: Creative Commons: Attribution 4.0
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