SARS-CoV-2 waves in Europe: A 2-stratum SEIRS model solution
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Abstract
In order to design actionable SARS-CoV-2 strategies, we extended the SEIRS model to support stratified isolation levels for healthy <60 and vulnerable individuals. At first, we forced isolation levels to be uniform, showing that daily deaths curves of all metropolitan areas in the analysis can be fitted using homogeneous Ro=3.3. In the process, we established the possibility that an extremely short infectiousness period of 2 days coupled with 5 days exposure may be responsible for the multiple deaths valleys observed during the weeks following lockdowns. Regardless of the infectiousness period, we realized that is possible to infer non-uniform isolation levels for healthy <60 and vulnerable by forcing the model to match the <60 to >60 age serology ratio reported in seroprevalence studies. Since the serology ratio is more robust than absolute values, we argue immunity level estimations made in this way (Madrid 41%; Catalonia 23%; Brussels 49%; and Stockholm 62%) are closer to reality. In locations where we didn’t find reliable serology, we performed immunity estimations assuming Spain’s serology ratio (Paris: 23%; London: 33%). We predict that no location can return to normal life without having a second wave (albeit in Stockholm a smaller one). We searched what isolation values allow to return to normal life in 90 days minimizing final deaths, shockingly all found isolations for healthy <60 were negative (i.e. coronavirus parties minimize final deaths). Then, assuming an ideal 1-day long vaccination campaign with a 77% efficacy vaccine, we compared predicted final deaths of those 90-day strategies for all possible vaccination dates with a 180-day long vaccine waiting strategy that imposes 0.40 mandatory isolation to healthy <60 and results in 0.65 isolation to vulnerable. We found that 180-day of mandatory isolations to healthy <60 (i.e. schools and workplaces closed) produces more final deaths if the vaccination date is later than (Madrid: Feb 23 2021; Catalonia: Dec 28 2020; Brussels Apr 25 2021; Paris: Jan 14 2021; London: Jan 22 2021). We also modeled how average isolation levels change the probability of getting infected for a single individual that isolates differently than average. That led us to realize disease damages to third parties due to virus spreading can be calculated and to postulate that an individual has the right to avoid mandatory isolation during epidemics (SARS-CoV-2 or any other) if these damages can be covered with a novel proposed isolation exemption insurance policy. As secondary findings in Appendix III we hypothesize that an early D614 like strain wave might be the cause of low mortality in Asia, and show the negligible reduction of HIT due to heterogeneity. Finally we conclude that our 2-stratum SEIRS model is suitable to predict SARS-CoV-2 epidemic behavior and can be used to minimize covid-19 disease and isolations related damages. To the sole effect of understanding and verifying its content the same model used through this paper has been made available online at www.sars2seir.com/paper-12-2020/
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SciScore for 10.1101/2020.10.09.20210146: (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 10.1101/2020.10.09.20210146: (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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