Skip to main content
SearchLoginLogin or Signup

Review 2: "Quantifying the impact of quarantine duration on COVID-19 transmission"

A 10-day quarantine maximizes utility compared to longer quarantines, and 'test and release' strategies increase the utility of shorter quarantines. While methods were generally supported, authors could better outline modeling assumptions and clarify societal implications.

Published onNov 09, 2020
Review 2: "Quantifying the impact of quarantine duration on COVID-19 transmission"
1 of 2
key-enterThis Pub is a Review of
Quantifying the impact of quarantine duration on COVID-19 transmission

The numbers of confirmed cases of severe acute respiratory syndrome coronavirus 2 (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. There is ongoing debate about the duration of quarantine, particularly since the fraction of individuals in quarantine who eventually test positive is perceived as being low. We present a mathematical model that uses empirically determined distributions of incubation period, infectivity, and generation time to quantify how the duration of quarantine affects transmission. We use this model to examine two quarantine scenarios: traced contacts of confirmed SARS-CoV-2 cases and returning travellers. We quantify the impact of shortening the quarantine duration 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) reinforced hygiene measures upon release after a negative test; iii) the development of symptoms during quarantine; iv) the relationship between quarantine duration and adherence; and v) the fraction of individuals in quarantine that are infected. When considering the ratio of prevented transmission to days spent in quarantine, we find that the diminishing impact of longer quarantine on transmission prevention may support a quarantine duration below 10 days. This ratio can be increased by implementing a test-and-release strategy, and this can be even further strengthened by reinforced hygiene measures post-release. We also find that unless a test-and-release strategy is considered, the fraction of individuals in quarantine that are infected does not affect the optimal duration of quarantine under our utility metric. Ultimately, we show that there are quarantine strategies based on a test-and-release protocol that, from an epidemiological viewpoint, perform almost as well as the standard 10 day quarantine, but with a lower cost in terms of person days spent in quarantine. This applies to both travellers and contacts, but the specifics depend on the context.

RR:C19 Evidence Scale rating by reviewer:

  • Reliable. The main study claims are generally justified by its methods and data. The results and conclusions are likely to be similar to the hypothetical ideal study. There are some minor caveats or limitations, but they would/do not change the major claims of the study. The study provides sufficient strength of evidence on its own that its main claims should be considered actionable, with some room for future revision.



I have found the work of Ashcroft et al as interesting, and the topic of shortening the quarantine stay is important and is relevant to all of us. The study is well-written, however, there are few aspects that are crucial and currently missing in the study. The formulas look nice, however, they are rather expected if we do not take into account the superspreading events. The latter was shown as key for COVID-19 spread. Then, how the authors would account or at least discuss this factor for their framework? The second aspect is about comparing the results to the preprint of Clifford et al 2020. That preprint is very close to Ashcroft et al. What are the major achievements of the current preprint comparing to Clifford et al? I would recommend highlighting more of the differences in the results of both preprints, desirably, from the quantitative side and not just stating that both studies are aligned (L433).

Other remarks:

- The usage of the term "transmission" is a bit confusing (see e.g. L168). I assume that the authors talk more about the transmission potential rather than just the transmission. The difference can be subtle, but it would be nice to be more strict about it.

- L32: I don't think that "10-day quarantine" is the standard one. At least, most countries of South-East Asia region currently implement a 14-day quarantine. Actually, this is the first time I see the proposed quarantine length of 10 days.

- L91: Is the social distancing (such as refraining from going to the restaurants or bars) also included in one of the individual-level prevention measures considered by the authors? If yes, it would be nice to mention it.

- Figure 1B: the serial interval was not really introduced/explained in the text, so it may be confusing for a reader to find it in the figure.

- L132-140 and Eq. 2: it would be nice to discuss the case of arbitrarily large values of y, because they are also often the case (e.g., they were the majority of cases reported in Taiwan recently as some students who studied in Europe or US were returning home – in that case their y would be an order of one year). I am not sure but it may affect the result of Eq. 2. He et al 2020 NatMed used an upper boundary of 21 days for such y.

- L152: are the authors talking about the rapid RT-PCR test? I think it would be nice to specify it and give more details. I am also confused because Kucirka et al applied the Bayesian framework and their results were posterior distributions at each day. I suspect that the authors used the median/mean of those distributions, but what is about the uncertainty around them? Sometimes, the posterior can be rather wide. This can be adjusted and I recommend it to account for this factor.

- L209: The shiny app looks nice.

- (Structure) Most of Section 3.1 should be in the Methods section, not the results. For example, Eq. 8 is definitely about the used methodology. It is important because I expect to read the results of the study in the Results section. For example, Figure 3 could be explained in more details in the text. This also needs to be checked for other subsections of the Results section.

Vape Factory: