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

Abstract
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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 travellers 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.

Data availability

There are no data inputs into our model.All parameter input values are specified in Table 1, or in the manuscript text.We provide a link to the github repository containing all code necessary to run the analyses and generate figures.

Article and author information

Author details

Katelyn Gostic

Ecology and Evolution, University of Chicago, Chicago, United States

For correspondence
kgostic@uchicago.edu

Competing interests
The authors declare that no competing interests exist.

"This ORCID iD identifies the author of this article:" 0000-0002-9369-6371
Ana C R Gomez

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

Competing interests
The authors declare that no competing interests exist.
Riley O Mummah

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

Competing interests
The authors declare that no competing interests exist.
Adam J Kucharski

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

Competing interests
The authors declare that no competing interests exist.

"This ORCID iD identifies the author of this article:" 0000-0001-8814-9421
James O Lloyd-Smith

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

For correspondence
jlloydsmith@ucla.edu

Competing interests
The authors declare that no competing interests exist.

"This ORCID iD identifies the author of this article:" 0000-0001-7941-502X

Funding

James S. McDonnell Foundation (Postdoctoral fellowship in dynamic and multiscale systems)

Katelyn Gostic

Wellcome (206250/Z/17/Z)

Adam J Kucharski

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (Science without borders fellowship)

Ana C R Gomez

National Science Foundation (DEB-1557022)

James O Lloyd-Smith

Defense Advanced Research Projects Agency (PREEMPT D18AC00031)

James O Lloyd-Smith

Strategic Environmental Reserach and Development Program (RC-2635)

Ana C R Gomez
Riley O Mummah
James O Lloyd-Smith

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Copyright

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.