Apparent reductions in COVID-19 Case Fatality Rates reflect changes in average age of those testing positive
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Abstract
Numbers of COVID-19 infections are rising in many countries, while death and hospitalisation rates remain low. Infection Fatality Rates (IFR) for individual year classes calculated from seroprevalence data and the ages of those dying in England show a very strong log-linear relationship with age, and allow us to predict fatality rates for those testing positive on each day based on their ages. Since the peak of the epidemic, reductions in the ages of cases account for an eight fold fall in fatality rates. Over the same period, increased testing intensity appears to have increased infections detected amongst the most vulnerable by a factor of at least five, and between 15 and 24 fold in the population as a whole. Together these two factors are sufficient to explain the large observed change in the ratio of deaths to reported cases. We can also use these methods to give a more precise early warning system of future increases in mortality rates than raw case numbers. Although case numbers are currently increasing markedly, a continuing reduction in numbers of older individuals being infected means that the predicted increase in mortality rates is much slower.
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SciScore for 10.1101/2020.09.18.20197160: (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 10.1101/2020.09.18.20197160: (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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