A Statistical Analysis Of CoV-19 Positive Test Frequency Data Indicates A Need For Greater Attention To CoV-19 Test Quality And Pre-Wuhan Cov-19 Prevalence
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Abstract
Increased attention to analysis of SARS-CoV-2 (CoV-19) positive test frequency data is essential for achievement of better knowledge of the natural history of the virus in human populations, improved accuracy of CoV-19 epidemiological data, and development of public response policies that are better crafted to address the current CoV-19-induced global crisis. A statistical analysis of currently available positive test frequency data reveals a surprisingly uniform relationship between the number of CoV-19 test performed and the number of positive tests obtained. The uniformity is particularly striking for United States CoV-19 test data. Such observations warrant closer evaluation of other factors, besides virus spread, that may also contribute to the nature of the coronavirus pandemic. These include indigenous CoV-19 and the quality of CoV-19 testing.
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SciScore for 10.1101/2020.04.24.20078402: (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 10.1101/2020.04.24.20078402: (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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