A simple stochastic theory of extinction shows rapid elimination of a Sars-like pandemic
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Abstract
The SARS-Cov-2 pandemic has seen the challenge of controlling novel zoonotic diseases that have high infection fatality rates, including a natural capacity for the evolution of variants that transmit more easily and evade immunity. In dealing with current and future similar pandemics, the question arises: what is the optimum strategy to control infections. Although a complex question, a key neglected component to appraise the elimination strategy is simple theory predicting the expected timescales of elimination. We use simple random walk and branching process theory to provide new insights on the process of elimination using non-pharmaceutical interventions. Our central achievement is a full theory of the distribution of extinction times — which we find is an extreme value Gumbel distribution — for any value of the reproductive number including some degree of population immunity. Overall, for the original SARS-Cov-2 variant our results predict rapid extinction — of order months — of an epidemic or pandemic if the reproductive number is kept to R e < 0.5; in a counterfactual scenario with global adoption of an elimination strategy in June 2020, SARS-Cov-2 could have been eliminated world-wide by early January 2021. Looking to the future, our results would suggest that elimination using NPIs is a more optimal strategy to control — and potentially eradicate — a Sars-like pandemic, in its early stages before the evolution of variants with greater transmissibility.
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SciScore for 10.1101/2020.08.10.20171454: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar …
SciScore for 10.1101/2020.08.10.20171454: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
No key resources detected.
Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
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