Estimated effectiveness of symptom and risk screening to prevent the spread of COVID-19

Author:

Gostic Katelyn1ORCID,Gomez Ana CR2,Mummah Riley O2,Kucharski Adam J3ORCID,Lloyd-Smith James O24ORCID

Affiliation:

1. Department of Ecology and Evolution, University of Chicago, Chicago, United States

2. Department of Ecology and Evolutionary Biology, University of California, Los Angeles, Los Angeles, United States

3. Department of Infectious Disease Epidemiology, London School of Tropical Hygiene and Medicine, London, United Kingdom

4. Fogarty International Center, National Institutes of Health, Bethesda, United States

Abstract

Traveller screening is being used to limit further spread of COVID-19 following its recent emergence, and symptom screening has become a ubiquitous tool in the global response. Previously, we developed a mathematical model to understand factors governing the effectiveness of traveller screening to prevent spread of emerging pathogens (Gostic et al., 2015). Here, we estimate the impact of different screening programs given current knowledge of key COVID-19 life history and epidemiological parameters. Even under best-case assumptions, we estimate that screening will miss more than half of infected people. Breaking down the factors leading to screening successes and failures, we find that most cases missed by screening are fundamentally undetectable, because they have not yet developed symptoms and are unaware they were exposed. Our work underscores the need for measures to limit transmission by individuals who become ill after being missed by a screening program. These findings can support evidence-based policy to combat the spread of COVID-19, and prospective planning to mitigate future emerging pathogens.

Funder

James S. McDonnell Foundation

Wellcome

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

National Science Foundation

Defense Advanced Research Projects Agency

Strategic Environmental Research and Development Program

Publisher

eLife Sciences Publications, Ltd

Subject

General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,General Medicine,General Neuroscience

Reference57 articles.

1. Incubation period of 2019 novel coronavirus (2019-nCoV) infections among travellers from Wuhan, China, 20–28 January 2020;Backer;Eurosurveillance,2020

2. China restricts movement to fight coronavirus;BBC News,2020

3. Bhatia S, Imai N, Cuomo-Dannenburg G, Baguelin M, Boonyasiri A, Cori A, Cucunubá Z, Dorigatti I, FitzJohn R, Fu H, Gaythorpe K, Ghani A, Hamlet A, Hinsley W, Laydon D, Nedjati-Gilani G, Okell L, Riley S, Thompson H, Elsland S, Volz E, Wang H, Wang Y, Whittaker C, Xi X, Donnelly C, Ferguson N. 2020. Imperial College. Report 6: Relativesensitivity of International Surveillance. https://www.imperial.ac.uk/media/imperial-college/medicine/sph/ide/gida-fellowships/Imperial-College---COVID-19---Relative-Sensitivity-International-Cases.pdf.

4. Fast detection is critical to contain deadly 2019 Wuhan coronavirus;Biomeme,2020

5. International travels and fever screening during epidemics: a literature review on the effectiveness and potential use of non-contact infrared thermometers;Bitar;Euro Surveillance,2009

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