Epidemiological Tools that Predict Partial Herd Immunity to SARS Coronavirus 2
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Abstract
The outbreak of SARS coronavirus 2 (SARS-CoV-2), which occurred in Wuhan, China in December 2019, has caused a worldwide pandemic of coronavirus disease 2019 (COVID-19). However, there is a lack of epidemiological tools to guide effective public policy development. Here we present epidemiological evidence that SARS-CoV-2 S type exited Wuhan or other epicenters in China earlier than L type and conferred partial resistance to the virus on infected populations. Analysis of regional disparities in incidence has revealed that a sharp decline in influenza epidemics is a useful surrogate indicator for the undocumented spread of SARS-CoV-2. The biggest concern in the world is knowing when herd immunity has been achieved and scheduling a time to regain the living activities of each country. This study provides a useful tool to guide the development of local policies to contain the virus.
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SciScore for 10.1101/2020.03.25.20043679: (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
Software and Algorithms Sentences Resources Analyses of Spearman correlation coefficient were performed with the use of the Statcel4 add-in package (OMS Publishing, Tokorozawa, Japan) for Microsoft Excel. Microsoft Excelsuggested: (Microsoft Excel, RRID:SCR_016137)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 …SciScore for 10.1101/2020.03.25.20043679: (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
Software and Algorithms Sentences Resources Analyses of Spearman correlation coefficient were performed with the use of the Statcel4 add-in package (OMS Publishing, Tokorozawa, Japan) for Microsoft Excel. Microsoft Excelsuggested: (Microsoft Excel, RRID:SCR_016137)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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