Sustaining Social Distancing Policies to Prevent a Dangerous Second Peak of COVID-19 Outbreak
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Abstract
Governments around the world have enacted strict social distancing policies in order to slow the spread of COVID-19. The next step is figuring out when to relax these restrictions and to what degree. Our results predict potentially disastrous implications of ending these policies too soon, based on projections made from a Susceptible-Exposed-Infectious-Removed (SEIR) epidemic model. Even when infection rates appear to be slowing down or decreasing, prematurely returning to “business as usual” produces a severe second peak far worse than the first. Furthermore, such a second peak is made more likely when very severe restrictions are initially enacted. Only an appropriately measured and committed set of restrictions can appropriately control COVID-19 outbreak levels.
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SciScore for 10.1101/2020.04.17.20069351: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.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…
SciScore for 10.1101/2020.04.17.20069351: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.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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