{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,16]],"date-time":"2026-07-16T18:04:50Z","timestamp":1784225090072,"version":"3.55.0"},"reference-count":26,"publisher":"Public Library of Science (PLoS)","issue":"7","license":[{"start":{"date-parts":[[2026,7,16]],"date-time":"2026-07-16T00:00:00Z","timestamp":1784160000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["www.plosone.org"],"crossmark-restriction":false},"short-container-title":["PLoS One"],"abstract":"<jats:sec id=\"sec001\">\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Measures of excess mortality are generally regarded as providing the best metric for countries\u2019 experience during the Covid pandemic of 2020\u20132022. Such measures, however, need to be adjusted to take account of the different age structures of different countries as Covid-related mortality can differ substantially by age.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"sec002\">\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>This paper analyses excess mortality data for a selection of countries using the Short Term Mortality Fluctuations dataset. A standardised age distribution is applied to the data to obtain age-adjusted excess mortality and this is compared to crude excess mortality data. The metric of years of life lost (YLL) is also calculated for the same dataset and cluster analysis is applied to investigate relationships between the mortality metrics and GDP per capita and inequality.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"sec003\">\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>The age adjustment makes a significant difference for some countries but the overall ranking of countries in terms of excess mortality changes very little, with rank correlation coefficients in excess of 0.95 for the metrics of crude mortality, age adjusted mortality and YLL Age adjusted excess mortality has a rank correlation of \u22120.69 with GDP per capita but the rank correlation with the Gini coefficient of 0.11 is not statistically significant.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec id=\"sec004\">\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>Rankings of countries by excess mortality during the Covid period are robust to age adjustment and choice of mortality metric. Cluster analysis suggests distinct clusterings of countries with similar outcomes, particularly the former planned economies of central and eastern Europe.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1371\/journal.pone.0353766","type":"journal-article","created":{"date-parts":[[2026,7,16]],"date-time":"2026-07-16T17:27:26Z","timestamp":1784222846000},"page":"e0353766","update-policy":"https:\/\/doi.org\/10.1371\/journal.pone.corrections_policy","source":"Crossref","is-referenced-by-count":0,"title":["Covid-19 related excess mortality: An analysis by age for selected countries"],"prefix":"10.1371","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0953-364X","authenticated-orcid":true,"given":"David","family":"Madden","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2026,7,16]]},"reference":[{"issue":"7942","key":"pone.0353766.ref001","doi-asserted-by":"crossref","first-page":"130","DOI":"10.1038\/s41586-022-05522-2","article-title":"The WHO estimates of excess mortality associated with the COVID-19 pandemic","volume":"613","author":"W Msemburi","year":"2023","journal-title":"Nature"},{"key":"pone.0353766.ref002","doi-asserted-by":"crossref","first-page":"113754","DOI":"10.1016\/j.envres.2022.113754","article-title":"Comparison of pandemic excess mortality in 2020-2021 across different empirical calculations","volume":"213","author":"M Levitt","year":"2022","journal-title":"Environ Res"},{"issue":"5","key":"pone.0353766.ref003","doi-asserted-by":"crossref","DOI":"10.1002\/bimj.202300386","article-title":"Years of life lost to COVID-19 and related mortality indicators: An Illustration in 30 Countries","volume":"66","author":"V Rousson","year":"2024","journal-title":"Biom J"},{"issue":"1","key":"pone.0353766.ref004","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1186\/s12963-024-00346-w","article-title":"Population age structure dependency of the excess mortality P-score","volume":"22","author":"N Ullrich-Kniffka","year":"2024","journal-title":"Popul Health Metr"},{"issue":"4","key":"pone.0353766.ref005","doi-asserted-by":"crossref","DOI":"10.1136\/bmjgh-2023-013018","article-title":"Magnitude and determinants of excess total, age-specific and sex-specific all-cause mortality in 24 countries worldwide during 2020 and 2021: Results on the impact of the COVID-19 pandemic from the C-MOR project","volume":"9","author":"CT Pallari","year":"2024","journal-title":"BMJ Glob Health"},{"issue":"3","key":"pone.0353766.ref006","first-page":"289","article-title":"Clustering countries of the world based on the trend of the COVID-19 incidence: An application of shape-based k-means algorithm","volume":"19","author":"A Tafti","year":"2024","journal-title":"Asia Pacific Journal of Health Management"},{"issue":"1","key":"pone.0353766.ref007","doi-asserted-by":"crossref","DOI":"10.2174\/0118749445260995230925103838","article-title":"Clustering countries based on the trend of COVID-19 mortality rates: An application of growth mixture models","volume":"16","author":"M Balooch Hasankhani","year":"2023","journal-title":"The Open Public Health Journal"},{"key":"pone.0353766.ref008","doi-asserted-by":"crossref","DOI":"10.7554\/eLife.69336","article-title":"Tracking excess mortality across countries during the COVID-19 pandemic with the World Mortality Dataset","volume":"10","author":"A Karlinsky","year":"2021","journal-title":"Elife"},{"key":"pone.0353766.ref009","doi-asserted-by":"crossref","first-page":"101118","DOI":"10.1016\/j.ssmph.2022.101118","article-title":"What should be the baseline when calculating excess mortality? New approaches suggest that we have underestimated the impact of the COVID-19 pandemic and previous winter peaks","volume":"18","author":"VM Shkolnikov","year":"2022","journal-title":"SSM-population health"},{"issue":"10268","key":"pone.0353766.ref010","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1016\/S0140-6736(20)32647-7","article-title":"Reduced mortality in New Zealand during the COVID-19 pandemic","volume":"397","author":"S Kung","year":"2021","journal-title":"Lancet"},{"issue":"8","key":"pone.0353766.ref011","doi-asserted-by":"crossref","first-page":"785","DOI":"10.1001\/jama.2020.24243","article-title":"All-cause excess mortality and COVID-19\u2013related mortality among US adults aged 25-44 years, March-July 2020","volume":"325","author":"JS Faust","year":"2021","journal-title":"JAMA"},{"issue":"2","key":"pone.0353766.ref012","doi-asserted-by":"crossref","first-page":"279","DOI":"10.1111\/padr.12475","article-title":"Sensitivity analysis of excess mortality due to the COVID-19 Pandemic","volume":"48","author":"MR Nepomuceno","year":"2022","journal-title":"Popul Dev Rev"},{"issue":"10334","key":"pone.0353766.ref013","doi-asserted-by":"crossref","first-page":"1513","DOI":"10.1016\/S0140-6736(21)02796-3","article-title":"Estimating excess mortality due to the COVID-19 pandemic: A systematic analysis of COVID-19-related mortality, 2020\u201321","volume":"399","author":"H Wang","year":"2022","journal-title":"The Lancet"},{"key":"pone.0353766.ref014","author":"Global Burden of Disease Collaborative Network","year":"2020"},{"key":"pone.0353766.ref015","author":"HMD"},{"key":"pone.0353766.ref016","author":"STMF","year":"2021"},{"issue":"5","key":"pone.0353766.ref017","doi-asserted-by":"crossref","first-page":"1549","DOI":"10.1093\/ije\/dyv105","article-title":"Data resource profile: The human mortality database (HMD)","volume":"44","author":"M Barbieri","year":"2015","journal-title":"Int J Epidemiol"},{"issue":"10375","key":"pone.0353766.ref018","doi-asserted-by":"crossref","first-page":"432","DOI":"10.1016\/S0140-6736(23)00115-0","article-title":"Conflicting COVID-19 excess mortality estimates","volume":"401","author":"P Bager","year":"2023","journal-title":"The Lancet"},{"issue":"10375","key":"pone.0353766.ref019","doi-asserted-by":"crossref","first-page":"431","DOI":"10.1016\/S0140-6736(23)00112-5","article-title":"Conflicting COVID-19 excess mortality estimates","volume":"401","author":"M Moeti","year":"2023","journal-title":"The Lancet"},{"issue":"10375","key":"pone.0353766.ref020","doi-asserted-by":"crossref","first-page":"433","DOI":"10.1016\/S0140-6736(23)00227-1","article-title":"Conflicting COVID-19 excess mortality estimates - Authors\u2019 reply","volume":"401","author":"COVID-19 Excess Mortality Collaborators","year":"2023","journal-title":"Lancet"},{"key":"pone.0353766.ref021","doi-asserted-by":"crossref","DOI":"10.1002\/9780470977811","volume-title":"Cluster Analysis","author":"BS Everitt","year":"2011","edition":"55"},{"key":"pone.0353766.ref022","unstructured":"United Nations Department of Economic and Social Affairs Population Division. 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