Mathematical modeling suggests pre-existing immunity to SARS-CoV-2
This article has been Reviewed by the following groups
Listed in
- Evaluated articles (ScreenIT)
Abstract
Mathematical models have largely failed to predict the unfolding of the COVID-19 pandemic. We revisit several variants of the SEIR-model and investigate various adjustments to the model in order to achieve output consistent with measured data in Manaus, India and Stockholm. In particular, Stockholm is interesting due to the almost constant NPI’s, which substantially simplifies the mathematical modeling. Analyzing mobility data for Stockholm, we argue that neither behavioral changes, age and activity stratification nor NPI’s alone are sufficient to explain the observed pandemic progression. We find that the most plausible hypothesis is that a large portion of the population, between 40 to 60 percent, have some protection against infection with the original variant of SARS-CoV-2.
Article activity feed
-
-
SciScore for 10.1101/2021.04.21.21255782: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics not detected. Sex as a biological variable not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Table 2: Resources
No key resources detected.
Results from OddPub: Thank you for sharing your code and data.
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 …
SciScore for 10.1101/2021.04.21.21255782: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Ethics not detected. Sex as a biological variable not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Table 2: Resources
No key resources detected.
Results from OddPub: Thank you for sharing your code and data.
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.
Results from scite Reference Check: We found no unreliable references.
-