Partial unlock model for COVID-19 or similar pandemic averts medical and economic disaster
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Abstract
Data as of March 29, 2020 show that the “flattening” strategy for COVID-19 in the U.S. is working so well that a clean removal of social distancing (aka “unlock”) at any time in 2020 will produce a renewed catastrophe, overloading the healthcare system. Leaving the economy locked down for a long time is its own catastrophe. An SIR-type model with clear parameters suitable for public information, and both tracking and predictive capabilities which “learns” disease spread characteristics rapidly as policy changes, suggests that a solution to the problem is a partial unlock. Case load can be managed so as not to exceed critical resources such as ventilators, yet allow enough people to get sick that herd immunity develops and a full unlock can be achieved in as little as five weeks from beginning of implementation. The partial unlock could be for example 3 full working days per week. Given that not all areas or individuals will respond, and travel and public gatherings are still unlikely, the partial unlock might be 5 full working days per week. The model can be regionalized easily, and by expediting the resolution of the pandemic in the U.S. medical equipment and volunteers, many of them with already acquired immunity, can be made available to other countries.
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SciScore for 10.1101/2020.03.30.20048082: (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 10.1101/2020.03.30.20048082: (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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