The DOI matches its Crossref record; 11 of the 12 references it cites were found in a registry or an index.
Effectiveness of airport screening at detecting travellers infected with novel coronavirus (2019-nCoV)
Open accessPublished version of a preprint
Abstract
We evaluated effectiveness of thermal passenger screening for 2019-nCoV infection at airport exit and entry to inform public health decision-making. In our baseline scenario, we estimated that 46% (95% confidence interval: 36 to 58) of infected travellers would not be detected, depending on incubation period, sensitivity of exit and entry screening, and proportion of asymptomatic cases. Airport screening is unlikely to detect a sufficient proportion of 2019-nCoV infected travellers to avoid entry of infected travellers.
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“The large numbers of false-positive and false-negative results mean that this is unlikely to have a substantial effect beyond increasing awareness 51,52 .”
From Digital technologies in the public-health response to COVID-19 (2020) · cites this paper as [52]
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Early transmission dynamics in Wuhan, China, of novel coronavirus-infected pneumonia
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Early dynamics of transmission and control of COVID-19: a mathematical modelling study
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Self-citationFactors influencing compliance with quarantine in Toronto during the 2003 SARS outbreak
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Entry screening for severe acute respiratory syndrome (SARS) or influenza: policy evaluation
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Thermal Image Scanning for Influenza Border Screening: Results of an Airport Screening Study
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Self-citationSleeping sickness—a growing problem?
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SAN FRANCISCO INTERNATIONAL AIRPORT
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Feasibility of controlling COVID-19 outbreaks by isolation of cases and contacts
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Self-citationPrem, K., Liu, Y., Russell, T., Kucharski, A. J., Eggo, R. M., Davies, N. G. M., Flasche, S., Clifford, S., Pearson, C. A. B., Munday, J. D., et al. (2020) · The Lancet Public Health · doi:10.1016/s2468-2667(20)30073-6 · Cited by 2,149
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Linton, N. M., Kobayashi, T., Yang, Y., Hayashi, K., Akhmetzhanov, A. R., Jung, S.-M., Yuan, B., Kinoshita, R., & Nishiura, H. (2020) · Journal of Clinical Medicine · doi:10.3390/jcm9020538 · Cited by 1,376
Digital technologies in the public-health response to COVID-19
Budd, J., Miller, B. S., Manning, E. M., Lampos, V., Zhuang, M., Edelstein, M., Rees, G., Emery, V. C., Stevens, M. M., Keegan, N., et al. (2020) · Nature Medicine · doi:10.1038/s41591-020-1011-4 · Cited by 1,195
Metadata
- Authors
- Quilty, B. J., Clifford, S., group2, C. N. W., Flasche, S., & Eggo, R. M.
- Affiliations
- London School of Hygiene & Tropical Medicine (GB)
- Centre for the Mathematical Modelling of Infectious Diseases, Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom
- Corresponding author
- Quilty, Billy J
- Venue
- Eurosurveillance
- Published
- 2020-02-06
- Volume
- 25
- Issue
- 5
- ISSN
- 1025-496X (ISSN-L)
- 1560-7917
- PMC
- PMC7014668
- OpenAlex
- W3005151538
- Cited by
- 321
- References
- 12
- Citations by year
- 2026: 10 · 2025: 10 · 2024: 13 · 2023: 27 · 2022: 36 · 2021: 80 · 2020: 144
- FWCI
- 11.41
- Type
- journal article
- Language
- en
- Update notices
- correction (2020-02-13)
- Open access
- diamond
- doi.org
- Locations
- Eurosurveillance (publishedVersion, cc-by)
- medRxiv (acceptedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- LSHTM Research Online (London School of Hygiene and Tropical Medicine) (acceptedVersion)
- Funders
- Wellcome Trust (206250, 210758/Z/18/Z, 206250/Z/17/Z, Z/17/Z, 208812, 03010, 210758, 208812/Z/17/Z)
- Government of the United Kingdom
- National Institute for Health and Care Research (ITCRZ 03010, 16/137/109, 16/137/10)
- Department of Health and Social Care (ITCRZ 03010)
- Royal Society (208812, Z/17/Z, 206250/Z/17/Z, 208812/Z/17/Z)
- Research Councils UK (MR/S003975/1, ES/P010873/1)
- Medical Research Council (MR/S003975/1)
- Economic and Social Research Council (ES/P010873/1)
- Topics
- Physical Sciences › Mathematics › Modeling and Simulation › COVID-19 epidemiological studies
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Travel-related health issues
- Health Sciences › Medicine › Infectious Diseases › SARS-CoV-2 detection and testing
- Keywords
- SARS-CoV-2, airport security screening, thermal screening, infection detection, asymptomatic infection, incubation period, screening sensitivity, public health decision-making
- MeSH terms
- COVID-19, Body Temperature, Decision Making, Fever, Humans, Mass Screening, Models, Theoretical, Pneumonia, Viral, Population Surveillance, Public Health, Coronavirus Infections, Communicable Diseases, Emerging, Air Travel
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