Evidence map›Paper›PMID 41742875›Full record

ArticleFuture science OA2026

Significant but small: the modest impact of population ageing on reported COVID-19 case rates worldwide.

Wenpeng You, Frank Donnelly, Luisa Garcia, Rita Chang

Abstract read
In one paragraph

Article in Future science OA, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Wenpeng YouSchool of Pharmacy and Biomedicine, Adelaide University, Adelaide, SA, Australia.ORCID 0000-0002-6229-1064
Frank DonnellySchool of Nursing, Murdoch University, Murdoch, Australia.
Luisa GarciaSchool of Nursing and Midwifery, Western Sydney University, Sydney, Australia.
Rita ChangSchool of Nursing and Midwifery, Western Sydney University, Sydney, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundOlder adults experienced disproportionate morbidity during the COVID-19 pandemic; however, the independent contribution of population ageing to cross-national variation in reported COVID-19 case rates remains insufficiently examined. RESEARCH DESIGN AND

methodsThis global ecological study analyzed data from 215 "countries" to assess whether ageing independently predicts COVID-19 case rates, which are influenced by national testing capacity and reporting practices. Confounding variables included economic affluence, the Henneberg Index, urbanization, and vaccination coverage. Analyses comprised bivariate correlations, principal component analysis, and multiple linear regression (enter and stepwise), with subgroup analyses by income level, development status, and World Health Organization region.

resultsPopulation ageing demonstrated a strong bivariate association with COVID-19 case rates; however, its independent contribution was modest. In adjusted models, population ageing remained statistically significant but explained only 1.7% of the total variance, whereas economic affluence and the Henneberg Index emerged as dominant predictors. The association between ageing and reported case rates was strongest in high-income settings.

conclusionsPopulation ageing contributes modestly to cross-national variation in COVID-19 case rates. Broader structural factors and the Henneberg Index play a substantially larger role, underscoring the importance of public health strategies that strengthen surveillance capacity and interpretation of pandemic data at the global level.

Indexed as

COVID-19 surveillancedemographiceconomic developmentglobal health inequalitiespandemic vulnerabilityPopulation ageingpublic health preparednessstructure

Identifiers

PMID41742875
PMCPMC12940146

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LicenceCC BY-NC
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.