Abstract
The numbers of confirmed cases of SARS-CoV-2 infection are increasing in many places. Consequently, the number of individuals placed into quarantine is increasing too. The large number of individuals in quarantine has high societal and economical costs, as well as infringing on the freedom of the individual. This has led to a vigorous debate about the duration of quarantine, particularly in light of the potentially low specificity of quarantine (i.e. low probability of quarantined individuals indeed being infected). We present a mathematical model that leverages empirically determined distributions of incubation period, infectivity, and generation time to quantify how the duration of quarantine affects transmission. With this model we address the impact of shortening the quarantine for returning travellers and traced contacts of confirmed cases, both in terms of prevented transmission and the ratio of prevented transmission to days spent in quarantine. We also consider the impact of i) test-and-release strategies; ii) additional hygiene measures imposed upon release after a negative test; iii) the development of symptoms during quarantine; iv) the relationship between quarantine duration and adherence; and v) the specificity of quarantine. When considering the benefit versus cost utility of quarantine, we find that the diminishing impact of longer quarantine on transmission prevention may support a quarantine duration below 10 days, particularly for returning travellers. A greater gain of utility can be achieved through a test-and-release strategy, and this can be even further strengthened by imposed hygiene measures post-release. We also find that unless a test-and-release strategy is considered, the specificity of quarantine does not affect the optimal duration of quarantine. Therefore, the argument that we should shorten quarantine because of lack of specificity is misguided.
Competing Interest Statement
The authors have declared no competing interest.
Funding Statement
This work was supported by the Swiss National Science Foundation. The funders of the study had no role in study design, data collection, data analysis, data interpretation, or writing of the manuscript.
Author Declarations
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Yes
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Data Availability
Code is publicly available at http://github.com/ashcroftp.