Infection fatality rate of COVID-19 in community-dwelling elderly populations

We identified seroprevalence studies (peer-reviewed publications, official reports, or preprints) in four existing systematic reviews [3, 7, 12, 13] as for a previous project [14], using the most recent updates of these reviews and their respective databases as of November 23, 2021. All systematic reviews may miss some studies, despite their systematic efforts. Here, the risk is minimized by using several existing systematic reviews of seroprevalence studies, each of them very meticulous. The protocol of this study was registered at the Open Science Framework (https://​osf.​io/​47cgb) after piloting data availability in December 2020 but before extracting full data, communicating with local authorities and study authors for additional data and performing any calculations. Protocol amendments and their justification appear in Online Appendix Table 1.

In the original protocol, we aimed to include studies on SARS-CoV-2 seroprevalence that had sampled at least 1000 participants aged ≥ 70 years in the location and/or setting of interest, provided an estimate of seroprevalence for elderly people, explicitly aimed to generate samples reflecting the general population, and were conducted at a location for which there is official data available on the proportion of cumulative COVID-19 deaths among elderly (with a cutoff placed between 60 and 70 years; e.g., eligible cutoffs were ≥ 70, ≥ 65, or ≥ 60, but not ≥ 75 or ≥ 55). Following comments from peer-reviewers, we also included national-level general population studies without high risk of bias and with at least 500 participants aged ≥ 70 years (since studies with 500–1000 may still yield reasonably precise estimates of seroprevalence in the elderly) and we excluded samples of patient cohorts, insurance applicants, blood donors, and workers (that were intended for inclusion in the original protocol). These convenience samples with ≥ 1000 participants aged ≥ 70 years are now considered only in a sensitivity analysis. USA studies were excluded if they did not adjust seroprevalence for race or ethnicity, since these socio-economically related factors may associate strongly with both study participation [15, 16] and COVID-19 burden [17‐19]. Following comments from peer-reviewers, we have added another exclusion criterion: crude seroprevalence being less than 1-test specificity and/or the 95% confidence interval of the seroprevalence going to 0% (since the seroprevalence estimate would be extremely uncertain). Following comments from peer-reviewers, we also considered only studies from high-income countries in the primary analysis, since there can be substantial uncertainty about the number of deaths in other countries. We focused on studies sampling participants in 2020, since IFRs in 2021 may be further affected by wide implementation of vaccinations that may substantially decrease fatality risk and by other changes (new variants and better treatment). We applied risk of bias assessments reported by SeroTracker (based on the Joanna Briggs Institute Critical Appraisal Tool for Prevalence Studies) [20]. Two authors reviewed records for eligibility. Discrepancies were solved by discussion.

CA extracted each data point and JPAI independently verified the extracted data. Discrepancies were solved through discussion. For each location, we identified the age distribution of cumulative COVID-19 deaths and chose as primary age cutoff the one closest to 70, while placed between 60 and 70 years (e.g., ≥ 70, ≥ 65, or ≥ 60).

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). We also extracted, for the elderly stratum, the estimated unadjusted seroprevalence, the most fully adjusted seroprevalence, and the factors considered for adjustment. Antibody titers may decline over time. E.g. a modelling study estimated 3–4 months average time to seroreversion [21]. A repeated measurements study [22] suggests even 50% seroreversion within a month for asymptomatic/oligosymptomatic patients, although this may be an over-estimate due to initially false-positive antibody results. To address seroreversion, if there were multiple different time points of seroprevalence assessment, we selected the one with the highest seroprevalence estimate. If seroprevalence data were unavailable as defined by the primary cutoff, but with another eligible cutoff (e.g., ≥ 70, ≥ 65, or ≥ 60), we extracted data for that cut-off.

Population size (overall, and elderly) and numbers of long-term care residents for the location were obtained from multiple sources (Online Appendix Table 2).

Cumulative COVID-19 deaths overall and in the elderly stratum (using the primary age cutoff) for the relevant location were extracted from official reports. Total numbers, i.e., confirmed and probable, was preferred whenever available. We extracted the accumulated deaths until 1 week after the midpoint of the seroprevalence study period (or closest date with available data) to account for different delays in developing antibodies versus dying from infection [23, 24]. If the seroprevalence study claimed strong arguments to use another time point or approach, while reporting official statistics on number of COVID-19 deaths overall and in the elderly, we extracted that number instead.

The proportion of cumulative COVID-19 deaths that occurred among long-term care residents for the relevant location and date was extracted from official sources or the International Long Term Care Policy Network (ILTCPN) report closest in time [2, 25]. We defined community-dwelling individuals by excluding persons living in institutions. Types of institutions used for elderly in various countries differed in nature and in the frailty of residents. For each location, we extracted available definitions of institutions. We preferred numbers recorded per residence status, i.e., including COVID-19 deaths among nursing home residents occurring in hospital. If the latter were unavailable, we calculated total number of deaths in residents with a correction (by multiplying with the median of available ratios of deaths in nursing homes to deaths of nursing home residents in the ILTCPN 10/14/2020 report [2] for countries in the same continent). We considered 95%, 98%, and 99% of residents’ deaths to have occurred in people ≥ 70 years, ≥ 65 years and ≥ 60 years, respectively [26]. For other imputations, see the online protocol.

We communicated with the authors of the seroprevalence study and with officers responsible for compiling the relevant official reports to obtain missing information or when information was available but not for preferred age cut-offs. Email requests were sent, with two reminders to non-responders.

Statistical analyses used R version 4.0.2 [29]. Similar to a previous overview of IFR-estimating studies [3], we estimated the sample size-weighted IFR of community-dwelling elderly for each country and then estimated the median and range of IFRs across countries. As expected, there was extreme heterogeneity among IFR estimates (I² = 99.1%), thus weighted meta-analysis averages are not meaningful [30, 31].

We explored a seroreversion correction of the IFR by X^m-fold, where m is the number of months from the peak of the first epidemic wave in the specific location and X is 0.99, 0.95, and 0.90 corresponding to 1%, 5%, and 10% relative monthly rate of seroreversion [21, 22, 32]. We also added a non-prespecified sensitivity analysis to explore the percentage increase in the cumulative number of deaths and IFR, if the cutoff was put 2 weeks (rather than 1 week) after the study midpoint.

We expected IFR would be higher in locations with a higher share of people ≥ 85 years old among the analyzed elderly stratum. Estimates of log₁₀IFR were plotted against the proportion of people ≥ 85 years old among the elderly (for population pyramid sources see Online Appendix Table 2).

Not applicable to this study.

There was no involvement of patients nor the public in this research.

By November 23, 2021, 3138 SARS-CoV-2 seroprevalence reports were available in the four systematic reviews. Screening and exclusions are shown in Online Appendix Figure 1 and Online Appendix Table 3. Twelve seroprevalence studies were included, one of which contained two separate surveys; another 13 studies with convenience samples were considered in sensitivity analysis [33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48‐56].

Table 1 shows for each study the sampling period, sample size tested and positive, age cut-offs for the elderly group, antibody type(s), seroprevalence estimates, types of adjustments, number of deaths, and IFR estimates. The 13 seroprevalence surveys in the main analysis (Table 1) represented 11 countries (Americas n = 2, Europe n = 11). Three studies excluded upfront persons with previously diagnosed COVID-19 from participating in their sample [53, 57, 58]. Mid-sampling points ranged from May 2020 to November 2020. Sampling had a median length of 5.4 weeks (range 13 days to 5 months). The median number of elderly individuals tested was 1473 (range 788–21,953). Median seroprevalence was 3.2% (range 0.47–14.9%). Adjusted seroprevalence estimates were available for 12/13 surveys.

COVID-19 deaths and population data among elderly at each location are shown in Table 1 (for sources, see Online Appendix Table 2). The proportion of a location’s total COVID-19 deaths that happened among elderly had a median of 86% (range 70–93%) in high-income countries. The proportion of a location’s total COVID-19 deaths that occurred in long-term care residents had a median of 39% (range 20–67%) in in high-income countries with available data (for Qatar, the number was imputed). One study [55] included only COVID-19 deaths that occurred in nursing homes and was corrected to reflect also the deaths among residents occurring in hospitals. Among the population, the elderly group comprised a median of 14% (range 10–24%) in high-income countries. People residing in facilities were 4.8% (range 2.9–8.8%) in high-income countries.

Additional information was obtained from authors and agencies on four studies for seroprevalence data [50, 56, 59, 60]; four studies for mortality data [49, 50, 34, 43]; two studies for population data [49, 50]; and five excluded studies (clarifying non-eligibility).

For countries with more than one IFR estimate available sample size-weighted average IFRs were calculated. In 11 high-income countries, IFRs in community-dwelling elderly (Fig. 1, Table 1) had a median of 2.9% (range 1.8–9.7%). Figure 1 also shows 95% CIs for IFRs based on 95% CIs for seroprevalence estimates. For 5 studies, 95% CIs were direct extractions from the seroprevalence studies themselves, while complementary calculations were performed for the others as described in Online Appendix Table 1. For 9 studies, seroprevalence estimates were corrected for test performance using the Gladen–Rogan formula (Online Appendix Table 4). Median IFR in all elderly for all 11 high-income countries was 4.5% (range 2.5–16.7%). Of the 13 included estimates, the IFR in community-dwelling elderly was > 30% lower than the IFR among all elderly in 10/13 and > 50% lower in 1/13.

With 5% relative monthly seroreversion, median IFR in community-dwelling elderly in 11 high-income countries was 2.2% (4.0% in all elderly—see details on seroreversion analyses in Online Appendix Table 5). Online Appendix Table 6 shows calculations with later cut-off for counting deaths.

The median IFR was 2.7% upon excluding 3 studies where the selected time point with highest seroprevalence was not the latest available (seroprevalence had declined in the latest timepoint) [56‐58]. The median IFR was 2.8% in 15 countries when applying the non-peer-reviewed pre-specified original eligibility criteria (including convenience samples, including 2 middle-income countries, and correcting for unmeasured antibodies).

IFR tended to increase with larger proportions of people ≥ 85 years old (Fig. 2). A regression of logIFR against the proportion of people ≥ 85 years old had a slope of 0.03 (p = 0.17), and suggested an IFR in community-dwelling elderly of 1.21%, 1.79%, and 3.89% when the proportion of people > 85 in the elderly group was 5%, 10%, and 20%, respectively. Using the set of studies in the pre-specified original eligibility criteria, the slope was 0.06 (p = 0.001), with IFR 0.41%, 0.81%, and 3.25% for the respective proportions.