Recurring Spatiotemporal Patterns of COVID-19 in the United States
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SciScore for 10.1101/2021.11.23.21266775: (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: 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: We detected the following sentences addressing limitations in the study:This study has several limitations. There are inconsistencies and biases in case reporting among states and provinces and across states. In addition, reported incidence is a function of the number of tests administered which can fluctuate over time. To …
SciScore for 10.1101/2021.11.23.21266775: (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: 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: We detected the following sentences addressing limitations in the study:This study has several limitations. There are inconsistencies and biases in case reporting among states and provinces and across states. In addition, reported incidence is a function of the number of tests administered which can fluctuate over time. To reduce these testing and reporting biases, we scaled cases within each state and province to focus on the timing of the waves rather than their intensity. In addition, at the county level, the Gi* statistic incorporates the variability in a county and its neighbors, thus reducing the noise from any individual county. In addition, it is not yet possible to determine exactly how seasons have affected COVID-19 incidence. It is likely that human and virus factors interact differentially at various seasons shaping the epidemic’s waves. As future research investigates this complex relationship, we recommend that policies and decisions should seriously consider the seasonal patterns of COVID-19. This analysis shows that patterns of waxing and waning of COVID-19 incidence at the state and county level are driven by continental-scale seasonal and geographical patterns. This in turn suggests that future state and county level COVID-19 surges should be at least in part predictable, and therefore preventable.
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.
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