Published February 24, 2020 | Version v1
Journal article Open

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

  • 1. University of Chicago
  • 2. University of California, Los Angeles
  • 3. London School of Tropical Hygiene and Medicine

Description

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 (https://github.com/kgostic/traveller_screening/releases/tag/v2.1, copy archived at https://github.com/elifesciences-publications/traveller_screening).

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Additional details

Identifiers

DOI
10.7554/eLife.55570
Other
oai:uchicago.tind.io:10017

Funding

James S. McDonnell Foundation
Postdoctoral fellowship in dynamic and multiscale systems
Wellcome
206250/Z/17/Z
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
Science without borders fellowship
National Science Foundation
DEB-1557022
Defense Advanced Research Projects Agency
PREEMPT D18AC00031
Strategic Environmental Research and Development Program
RC-2635

UChicago Information

Division(s)
Biological Sciences Division
Department(s)
Ecology and Evolution