CovidRiskCalc: An online app to calculate the risk of COVID infection in a gathering
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Abstract
CovidRiskCalc is an evidence based online app which calculates the risk of COVID-19 infection for a person coming into contact during a specific event/gathering with a group of individuals, some of whom may be infected (available at CovidRiskCalc.eu ). The user is helped in providing a rough estimate of the COVID-19 prevalence rate in the group. She also inputs the size of the group, the number (and duration) of her contacts and the level of precautions (masks, social distancing, etc.). The app calculates the user’s risk of transmission in a single infected contact; her probability of infection during the entire event and the number of new infections within the group. Two numerical examples are given. The tool, designed for both professionals and the general public, thus quantifies the risks of infection in special populations (social gatherings, prisons, etc.), but also in general ones (stores, stadiums, etc.).
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SciScore for 10.1101/2020.12.01.20241646: (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
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:The app has limitations due to the model’s simplifying assumptions, namely the uniform mixing and person-to-person transmission, which preclude a spread of the disease via surface contacts or travelling aerosol droplets. Given these assumptions and the uncertainties concerning both the prevalence p and the probability of transmission …
SciScore for 10.1101/2020.12.01.20241646: (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
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:The app has limitations due to the model’s simplifying assumptions, namely the uniform mixing and person-to-person transmission, which preclude a spread of the disease via surface contacts or travelling aerosol droplets. Given these assumptions and the uncertainties concerning both the prevalence p and the probability of transmission ptr, the results should be viewed as orders of magnitudes only – although the model has been validated at least for the well-documented event at the White House on Sept 26. When driving to a social event or a stadium during the COVID-19 pandemic, you not only have an intuitive grasp of your chance of a flat tire - you can now have some idea of your risk of infection and of the approximate number of new cases during the event.
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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