Quarantine and the risk of COVID-19 importation.

J Arino, N Bajeux, S Portet, J Watmough
Author Information
  1. J Arino: Department of Mathematics & Data Science NEXUS, University of Manitoba, Winnipeg, ManitobaR3T 2N2, Canada. ORCID
  2. N Bajeux: Department of Mathematics, University of Manitoba, Winnipeg, ManitobaR3T 2N2, Canada.
  3. S Portet: Department of Mathematics & Data Science NEXUS, University of Manitoba, Winnipeg, ManitobaR3T 2N2, Canada.
  4. J Watmough: Department of Mathematics & Statistics, University of New Brunswick, Fredericton, New BrunswickE3B 5A3, Canada.

Abstract

Using a stochastic model, we assess the risk of importation-induced local transmission chains in locations seeing few or no local transmissions and evaluate the role of quarantine in the mitigation of this risk. We find that the rate of importations plays a critical role in determining the risk that case importations lead to local transmission chains, more so than local transmission characteristics, i.e. strength of social distancing measures (NPI). The latter influences the severity of the outbreaks when they do take place. Quarantine after arrival in a location is an efficacious way to reduce the rate of importations. Locations that see no or low-level local transmission should ensure that the rate of importations remains low. A high level of compliance with post-arrival quarantine followed by testing achieves this objective with less of an impact than travel restrictions or bans.

Keywords

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MeSH Term

COVID-19
Computer Simulation
Markov Chains
Models, Biological
Physical Distancing
Poisson Distribution
Probability
Quarantine
Risk Factors
Stochastic Processes
Travel
Treatment Adherence and Compliance

Word Cloud

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