Age-specific mortality and immunity patterns of SARS-CoV-2
Open accessPublished version of a preprint
Abstract
Estimating the size of the coronavirus disease 2019 (COVID-19) pandemic and the infection severity of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is made challenging by inconsistencies in the available data. The number of deaths associated with COVID-19 is often used as a key indicator for the size of the epidemic, but the observed number of deaths represents only a minority of all infections 1,2. In addition, the heterogeneous burdens in nursing homes and the variable reporting of deaths of older individuals can hinder direct comparisons of mortality rates and the underlying levels of transmission across countries 3. Here we use age-specific COVID-19-associated death data from 45 countries and the results of 22 seroprevalence studies to investigate the consistency of infection and fatality patterns across multiple countries. We find that the age distribution of deaths in younger age groups (less than 65 years of age) is very consistent across different settings and demonstrate how these data can provide robust estimates of the share of the population that has been infected. We estimate that the infection fatality ratio is lowest among 5-9-year-old children, with a log-linear increase by age among individuals older than 30 years. Population age structures and heterogeneous burdens in nursing homes explain some but not all of the heterogeneity between countries in infection fatality ratios. Among the 45 countries included in our analysis, we estimate that approximately 5% of these populations had been infected by 1 September 2020, and that much higher transmission rates have probably occurred in a number of Latin American countries. This simple modelling framework can help countries to assess the progression of the pandemic and can be applied in any scenario for which reliable age-specific death data are available.
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Based on India's estimated 2021 age-structure, the meta-analysis of O'Driscoll et al. 2021 predicts a COVID-19 infection fatality rate of 0.25%.
“the meta-analysis of O’Driscoll et al. 2021 [46] predicts a COVID-19 infection fatality rate (IFR) of 0.25%”
From Estimates of pandemic excess mortality in India based on civil registration data (2022) · cites this paper as [46]
Age-specific death data may help explain the heterogeneity in COVID-19 burden and COVID-19-attributable deaths in different countries.
“Age-specific death data may also help explain the heterogeneity in COVID-19 burden and COVID-19–attributable deaths in different countries (9).”
From Socioeconomic status determines COVID-19 incidence and related mortality in Santiago, Chile (2021) · cites this paper as [9]
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- Authors
- O’Driscoll, M., Ribeiro Dos Santos, G., Wang, L., Cummings, D. A. T., Azman, A. S., Paireau, J., Fontanet, A., Cauchemez, S., & Salje, H.
- Affiliations
- Centre National de la Recherche Scientifique (FR)
- University of Florida (US)
- Johns Hopkins University (US)
- Conservatoire National des Arts et Métiers (FR)
- Corresponding author
- O’Driscoll, Megan
- Cauchemez, Simon
- Salje, Henrik
- ORCID
- Venue
- Nature
- Published
- 2020-11-02
- Volume
- 590
- Issue
- 7844
- Pages
- 140-145
- ISSN
- 0028-0836 (ISSN-L)
- 1476-4687
- OpenAlex
- W3095683209
- Cited by
- 1,210
- References
- 29
- Citations by year
- 2026: 49 · 2025: 77 · 2024: 163 · 2023: 234 · 2022: 325 · 2021: 338 · 2020: 22 · 2017: 2
- FWCI
- 36.32
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Nature (publishedVersion)
- medRxiv (acceptedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- HAL (submittedVersion, cc-by-nc)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- European Commission (874735, HORIZON2020, 101003589, 804744)
- Agence Nationale de la Recherche (10-LABX-62-IBEID, ANR‐10‐LABX‐62‐IBEID, ANR-16-CONV-0005, ANR-10, ANR-10-LABX-0062, grant ANR-10-LABX-62-IBEID, ANR-10-LABX-62)
- Medical Research Council (MR/R015600/1, MC_PC_19012)
- Engineering and Physical Sciences Research Council (RG 90413)
- H2020 European Research Council (804744)
- Topics
- Physical Sciences › Mathematics › Modeling and Simulation › COVID-19 epidemiological studies
- Health Sciences › Medicine › Infectious Diseases › SARS-CoV-2 and COVID-19 Research
- Health Sciences › Medicine › Infectious Diseases › COVID-19 Clinical Research Studies
- Keywords
- SARS-CoV-2, COVID-19 pandemic, age-specific mortality, infection fatality rate, seroprevalence, age distribution of deaths, children, nursing homes, age structure, cross-national comparison, transmission rate, Latin America, epidemic estimation
- MeSH terms
- COVID-19, SARS-CoV-2, COVID-19 Serological Testing, Adolescent, Adult, Age Factors, Aged, Aged, 80 and over, Aging, Child, Child, Preschool, Female, Humans, Infant, Infant, Newborn, Male, Middle Aged, Age Distribution, Internationality, Young Adult, Pandemics
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