An open repository of real-time COVID-19 indicators
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Abstract
To study the COVID-19 pandemic, its effects on society, and measures for reducing its spread, researchers need detailed data on the course of the pandemic. Standard public health data streams suffer inconsistent reporting and frequent, unexpected revisions. They also miss other aspects of a population’s behavior that are worthy of consideration. We present an open database of COVID signals in the United States, measured at the county level and updated daily. This includes traditionally reported COVID cases and deaths, and many others: measures of mobility, social distancing, internet search trends, self-reported symptoms, and patterns of COVID-related activity in deidentified medical insurance claims. The database provides all signals in a common, easy-to-use format, empowering both public health research and operational decision-making.
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SciScore for 10.1101/2021.07.12.21259660: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Software and Algorithms Sentences Resources These data sources provide information not available from standard public health reporting or other common sources, such as: Health Insurance Claims: Based on de-identified medical insurance claims from Change Healthcare and other health system partners, we release indicators on the estimated per-centage of covered outpatient visits and hospitalizations that involved COVID diagnoses or symptoms. Change Healthcaresuggested: NoneThe R and Python package software is public and open-source, at https://github.com/cmu-delphi/covidcast/. Pythonsuggested: (IPython, RRID:SCR_001658)Lastly, most … SciScore for 10.1101/2021.07.12.21259660: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Software and Algorithms Sentences Resources These data sources provide information not available from standard public health reporting or other common sources, such as: Health Insurance Claims: Based on de-identified medical insurance claims from Change Healthcare and other health system partners, we release indicators on the estimated per-centage of covered outpatient visits and hospitalizations that involved COVID diagnoses or symptoms. Change Healthcaresuggested: NoneThe R and Python package software is public and open-source, at https://github.com/cmu-delphi/covidcast/. Pythonsuggested: (IPython, RRID:SCR_001658)Lastly, most data sources are provided under the Creative Commons Attribution license, and a small number have additional restrictions imposed by the data source; see https://cmu-delphi.github.io/delphi-epidata/api/covidcast_licensing.html. 1.5 Interactive Visualization: Since April 2020, Delphi has been maintaining and continually improving various online visualization tools for the COVIDcast indicators [22]. Delphisuggested: (DelPhi, RRID:SCR_008669)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.
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