Infection fatality rate of COVID-19 in community-dwelling elderly populations
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Abstract
This mixed design synthesis aimed to estimate the infection fatality rate (IFR) of Coronavirus Disease 2019 (COVID-19) in community-dwelling elderly populations and other age groups from seroprevalence studies. Protocol: https://osf.io/47cgb . Eligible were seroprevalence studies done in 2020 and identified by any of four existing systematic reviews; with ≥ 500 participants aged ≥ 70 years; presenting seroprevalence in elderly people; aimed to generate samples reflecting the general population; and whose location had available data on cumulative COVID-19 deaths in elderly (primary cutoff ≥ 70 years; ≥ 65 or ≥ 60 also eligible). We extracted the most fully adjusted (if unavailable, unadjusted) seroprevalence estimates; age- and residence-stratified cumulative COVID-19 deaths (until 1 week after the seroprevalence sampling midpoint) from official reports; and population statistics, to calculate IFRs adjusted for test performance. Sample size-weighted IFRs were estimated for countries with multiple estimates. Thirteen seroprevalence surveys representing 11 high-income countries were included in the main analysis. Median IFR in community-dwelling elderly and elderly overall was 2.9% (range 1.8–9.7%) and 4.5% (range 2.5–16.7%) without accounting for seroreversion (2.2% and 4.0%, respectively, accounting for 5% monthly seroreversion). Multiple sensitivity analyses yielded similar results. IFR was higher with larger proportions of people > 85 years. The IFR of COVID-19 in community-dwelling elderly is lower than previously reported.
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SciScore for 10.1101/2021.07.08.21260210: (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
Antibodies Sentences Resources Similar to a previous project (3), we extracted from eligible studies information on location, recruitment and sampling strategy, dates of sample collection, sample size (overall and elderly group), and types of antibody measured (immunoglobulin G (IgG), IgM and IgA). IgG), IgMsuggested: NoneIgAsuggested: NoneResults from OddPub: Thank you for sharing your data.
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Our analysis has several limitations. First, seroprevalence estimates among elderly reported by the included studies could over- or …
SciScore for 10.1101/2021.07.08.21260210: (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
Antibodies Sentences Resources Similar to a previous project (3), we extracted from eligible studies information on location, recruitment and sampling strategy, dates of sample collection, sample size (overall and elderly group), and types of antibody measured (immunoglobulin G (IgG), IgM and IgA). IgG), IgMsuggested: NoneIgAsuggested: NoneResults from OddPub: Thank you for sharing your data.
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:Our analysis has several limitations. First, seroprevalence estimates among elderly reported by the included studies could over- or underestimate the proportion infected. We explored adjusted estimates accounting for 1-10% relative seroreversion per month; however, higher seroreversion is likely (19, 20, 56). Higher seroreversion will affect more prominently studies carried out later in the pandemic. Also, the current estimates do not fully account for the unknown share of people who may have tackled the infection without generating detectable serum/plasma antibodies (e.g., by mucosal, innate, or cellular immune mechanisms) (57-61). Sensitivity estimates for antibody assays typically use positive controls from symptomatic individuals with clinically manifest infection; sensitivity may be lower for asymptomatic infections. All seroprevalence studies may have substantial residual biases despite whatever adjustments (6). Even well-designed general population studies may specifically fail to reach and recruit highly vulnerable populations, e.g. disadvantaged groups, immigrants, homeless, and other people at high exposure risks and poor health. Second, the number of deaths may be biased for various reasons (3) leading to potential under- or over-counting. Using excess mortality data is an alternative that has caveats, as those data depend heavily on the reference time period; availability in specific age groups can be restricted; and the proportion of deaths that is directly attri...
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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