Assessing the potential impact of COVID-19 on life expectancy
The COVID-19 virus pandemic has caused a significant number of deaths worldwide. If the prevalence of the infection continues to grow, this could impact life expectancy. This paper provides first estimates of the potential direct impact of the COVID-19 pandemic on period life expectancy. From the es...
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| description | The COVID-19 virus pandemic has caused a significant number of deaths worldwide. If the prevalence of the infection continues to grow, this could impact life expectancy. This paper provides first estimates of the potential direct impact of the COVID-19 pandemic on period life expectancy.
From the estimates of bias-adjusted age-specific infection fatality rates in Hubei (China) and a range of six prevalence rate assumptions ranging from 1% to 70%, we built a discrete-time microsimulation model that simulates the number of people infected by COVID-19, the number dying from it, and the number of deaths from all causes week by week for a period of one year. We applied our simulation to four broad regions: North America and Europe; Latin America and the Caribbean; Southeastern Asia; and sub-Saharan African. For each region, 100,000 individuals per each 5-year age group are simulated.
At a 10% COVID-19 prevalence rate, the loss in life expectancy at birth is likely above 1 year in North America and Europe and in Latin America and the Caribbean. In Southeastern Asia and sub-Saharan Africa, one year lost in life expectancy corresponds to an infection prevalence of about 15% and 25%, respectively. Given the uncertainty in fatality rates, with a 50% prevalence of COVID-19 infections under 95% prediction intervals, life expectancy would drop by 3 to 9 years in North America and Europe, by 3 to 8 years in Latin America and the Caribbean, by 2 to 7 years in Southeastern Asia, and by 1 to 4 years in sub-Saharan Africa. In all prevalence scenarios, as long as the COVID-19 infection prevalence rate remains below 1 or 2%, COVID-19 would not affect life expectancy in a substantial manner.
In regions with relatively high life expectancy, if the infection prevalence threshold exceeds 1 or 2%, the COVID-19 pandemic will break the secular trend of increasing life expectancy, resulting in a decline in period life expectancy. With life expectancy being a key indicator of human development, mortality increase, especially among the vulnerable subgroups of populations, would set a country back on its path of human development. |
| doi_str_mv | 10.1371/journal.pone.0238678 |
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From the estimates of bias-adjusted age-specific infection fatality rates in Hubei (China) and a range of six prevalence rate assumptions ranging from 1% to 70%, we built a discrete-time microsimulation model that simulates the number of people infected by COVID-19, the number dying from it, and the number of deaths from all causes week by week for a period of one year. We applied our simulation to four broad regions: North America and Europe; Latin America and the Caribbean; Southeastern Asia; and sub-Saharan African. For each region, 100,000 individuals per each 5-year age group are simulated.
At a 10% COVID-19 prevalence rate, the loss in life expectancy at birth is likely above 1 year in North America and Europe and in Latin America and the Caribbean. In Southeastern Asia and sub-Saharan Africa, one year lost in life expectancy corresponds to an infection prevalence of about 15% and 25%, respectively. Given the uncertainty in fatality rates, with a 50% prevalence of COVID-19 infections under 95% prediction intervals, life expectancy would drop by 3 to 9 years in North America and Europe, by 3 to 8 years in Latin America and the Caribbean, by 2 to 7 years in Southeastern Asia, and by 1 to 4 years in sub-Saharan Africa. In all prevalence scenarios, as long as the COVID-19 infection prevalence rate remains below 1 or 2%, COVID-19 would not affect life expectancy in a substantial manner.
In regions with relatively high life expectancy, if the infection prevalence threshold exceeds 1 or 2%, the COVID-19 pandemic will break the secular trend of increasing life expectancy, resulting in a decline in period life expectancy. With life expectancy being a key indicator of human development, mortality increase, especially among the vulnerable subgroups of populations, would set a country back on its path of human development.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0238678</identifier><identifier>PMID: 32941467</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Adult ; Africa South of the Sahara - epidemiology ; Age Distribution ; Aged ; Americas - epidemiology ; Asia - epidemiology ; Betacoronavirus ; Biology and Life Sciences ; Computer Simulation ; Coronavirus Infections - mortality ; Coronaviruses ; COVID-19 ; Demography ; Developing Countries ; Epidemics ; Europe - epidemiology ; Fatalities ; Female ; Forecasts and trends ; Global Health ; Humans ; Infections ; Influence ; Life Expectancy ; Life span ; Male ; Medical research ; Medical statistics ; Medicine and Health Sciences ; Middle Aged ; Models, Theoretical ; Mortality ; Pandemics ; People and Places ; Pneumonia, Viral - mortality ; Prevalence ; SARS-CoV-2 ; Subgroups ; Viral diseases ; Viruses</subject><ispartof>PloS one, 2020-09, Vol.15 (9), p.e0238678-e0238678</ispartof><rights>COPYRIGHT 2020 Public Library of Science</rights><rights>2020 Marois et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2020 Marois et al 2020 Marois et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c692t-4c5a9f18377b4a56237750b5dad464f33e99436615df04c17f4dfd43e183cafd3</citedby><cites>FETCH-LOGICAL-c692t-4c5a9f18377b4a56237750b5dad464f33e99436615df04c17f4dfd43e183cafd3</cites><orcidid>0000-0002-2701-6286</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7498023/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC7498023/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,864,885,2102,2928,23866,27924,27925,53791,53793,79600,79601</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/32941467$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Masquelier, Bruno</contributor><creatorcontrib>Marois, Guillaume</creatorcontrib><creatorcontrib>Muttarak, Raya</creatorcontrib><creatorcontrib>Scherbov, Sergei</creatorcontrib><title>Assessing the potential impact of COVID-19 on life expectancy</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>The COVID-19 virus pandemic has caused a significant number of deaths worldwide. If the prevalence of the infection continues to grow, this could impact life expectancy. This paper provides first estimates of the potential direct impact of the COVID-19 pandemic on period life expectancy.
From the estimates of bias-adjusted age-specific infection fatality rates in Hubei (China) and a range of six prevalence rate assumptions ranging from 1% to 70%, we built a discrete-time microsimulation model that simulates the number of people infected by COVID-19, the number dying from it, and the number of deaths from all causes week by week for a period of one year. We applied our simulation to four broad regions: North America and Europe; Latin America and the Caribbean; Southeastern Asia; and sub-Saharan African. For each region, 100,000 individuals per each 5-year age group are simulated.
At a 10% COVID-19 prevalence rate, the loss in life expectancy at birth is likely above 1 year in North America and Europe and in Latin America and the Caribbean. In Southeastern Asia and sub-Saharan Africa, one year lost in life expectancy corresponds to an infection prevalence of about 15% and 25%, respectively. Given the uncertainty in fatality rates, with a 50% prevalence of COVID-19 infections under 95% prediction intervals, life expectancy would drop by 3 to 9 years in North America and Europe, by 3 to 8 years in Latin America and the Caribbean, by 2 to 7 years in Southeastern Asia, and by 1 to 4 years in sub-Saharan Africa. In all prevalence scenarios, as long as the COVID-19 infection prevalence rate remains below 1 or 2%, COVID-19 would not affect life expectancy in a substantial manner.
In regions with relatively high life expectancy, if the infection prevalence threshold exceeds 1 or 2%, the COVID-19 pandemic will break the secular trend of increasing life expectancy, resulting in a decline in period life expectancy. With life expectancy being a key indicator of human development, mortality increase, especially among the vulnerable subgroups of populations, would set a country back on its path of human development.</description><subject>Adult</subject><subject>Africa South of the Sahara - epidemiology</subject><subject>Age Distribution</subject><subject>Aged</subject><subject>Americas - epidemiology</subject><subject>Asia - epidemiology</subject><subject>Betacoronavirus</subject><subject>Biology and Life Sciences</subject><subject>Computer Simulation</subject><subject>Coronavirus Infections - mortality</subject><subject>Coronaviruses</subject><subject>COVID-19</subject><subject>Demography</subject><subject>Developing Countries</subject><subject>Epidemics</subject><subject>Europe - epidemiology</subject><subject>Fatalities</subject><subject>Female</subject><subject>Forecasts and trends</subject><subject>Global Health</subject><subject>Humans</subject><subject>Infections</subject><subject>Influence</subject><subject>Life Expectancy</subject><subject>Life span</subject><subject>Male</subject><subject>Medical research</subject><subject>Medical statistics</subject><subject>Medicine and Health Sciences</subject><subject>Middle Aged</subject><subject>Models, Theoretical</subject><subject>Mortality</subject><subject>Pandemics</subject><subject>People and Places</subject><subject>Pneumonia, Viral - 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epidemiology</topic><topic>Age Distribution</topic><topic>Aged</topic><topic>Americas - epidemiology</topic><topic>Asia - epidemiology</topic><topic>Betacoronavirus</topic><topic>Biology and Life Sciences</topic><topic>Computer Simulation</topic><topic>Coronavirus Infections - mortality</topic><topic>Coronaviruses</topic><topic>COVID-19</topic><topic>Demography</topic><topic>Developing Countries</topic><topic>Epidemics</topic><topic>Europe - epidemiology</topic><topic>Fatalities</topic><topic>Female</topic><topic>Forecasts and trends</topic><topic>Global Health</topic><topic>Humans</topic><topic>Infections</topic><topic>Influence</topic><topic>Life Expectancy</topic><topic>Life span</topic><topic>Male</topic><topic>Medical research</topic><topic>Medical statistics</topic><topic>Medicine and Health Sciences</topic><topic>Middle Aged</topic><topic>Models, Theoretical</topic><topic>Mortality</topic><topic>Pandemics</topic><topic>People and Places</topic><topic>Pneumonia, Viral - mortality</topic><topic>Prevalence</topic><topic>SARS-CoV-2</topic><topic>Subgroups</topic><topic>Viral diseases</topic><topic>Viruses</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Marois, Guillaume</creatorcontrib><creatorcontrib>Muttarak, Raya</creatorcontrib><creatorcontrib>Scherbov, Sergei</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Opposing Viewpoints in Context (Gale)</collection><collection>Gale In Context: Science</collection><collection>ProQuest Central (Corporate)</collection><collection>Animal Behavior Abstracts</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Biotechnology Research Abstracts</collection><collection>Nursing & Allied Health Database</collection><collection>Ecology Abstracts</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Immunology Abstracts</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Nucleic Acids Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>Agricultural Science Collection</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Public Health Database</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>Coronavirus Research Database</collection><collection>ProQuest Materials Science Collection</collection><collection>ProQuest Central Korea</collection><collection>Engineering Research Database</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Materials Science Database</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>Meteorological & Geoastrophysical Abstracts - 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Academic</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Marois, Guillaume</au><au>Muttarak, Raya</au><au>Scherbov, Sergei</au><au>Masquelier, Bruno</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Assessing the potential impact of COVID-19 on life expectancy</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2020-09-17</date><risdate>2020</risdate><volume>15</volume><issue>9</issue><spage>e0238678</spage><epage>e0238678</epage><pages>e0238678-e0238678</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>The COVID-19 virus pandemic has caused a significant number of deaths worldwide. If the prevalence of the infection continues to grow, this could impact life expectancy. This paper provides first estimates of the potential direct impact of the COVID-19 pandemic on period life expectancy.
From the estimates of bias-adjusted age-specific infection fatality rates in Hubei (China) and a range of six prevalence rate assumptions ranging from 1% to 70%, we built a discrete-time microsimulation model that simulates the number of people infected by COVID-19, the number dying from it, and the number of deaths from all causes week by week for a period of one year. We applied our simulation to four broad regions: North America and Europe; Latin America and the Caribbean; Southeastern Asia; and sub-Saharan African. For each region, 100,000 individuals per each 5-year age group are simulated.
At a 10% COVID-19 prevalence rate, the loss in life expectancy at birth is likely above 1 year in North America and Europe and in Latin America and the Caribbean. In Southeastern Asia and sub-Saharan Africa, one year lost in life expectancy corresponds to an infection prevalence of about 15% and 25%, respectively. Given the uncertainty in fatality rates, with a 50% prevalence of COVID-19 infections under 95% prediction intervals, life expectancy would drop by 3 to 9 years in North America and Europe, by 3 to 8 years in Latin America and the Caribbean, by 2 to 7 years in Southeastern Asia, and by 1 to 4 years in sub-Saharan Africa. In all prevalence scenarios, as long as the COVID-19 infection prevalence rate remains below 1 or 2%, COVID-19 would not affect life expectancy in a substantial manner.
In regions with relatively high life expectancy, if the infection prevalence threshold exceeds 1 or 2%, the COVID-19 pandemic will break the secular trend of increasing life expectancy, resulting in a decline in period life expectancy. With life expectancy being a key indicator of human development, mortality increase, especially among the vulnerable subgroups of populations, would set a country back on its path of human development.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>32941467</pmid><doi>10.1371/journal.pone.0238678</doi><tpages>e0238678</tpages><orcidid>https://orcid.org/0000-0002-2701-6286</orcidid><oa>free_for_read</oa></addata></record> |
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| subjects | Adult Africa South of the Sahara - epidemiology Age Distribution Aged Americas - epidemiology Asia - epidemiology Betacoronavirus Biology and Life Sciences Computer Simulation Coronavirus Infections - mortality Coronaviruses COVID-19 Demography Developing Countries Epidemics Europe - epidemiology Fatalities Female Forecasts and trends Global Health Humans Infections Influence Life Expectancy Life span Male Medical research Medical statistics Medicine and Health Sciences Middle Aged Models, Theoretical Mortality Pandemics People and Places Pneumonia, Viral - mortality Prevalence SARS-CoV-2 Subgroups Viral diseases Viruses |
| title | Assessing the potential impact of COVID-19 on life expectancy |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-25T03%3A57%3A31IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-gale_plos_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Assessing%20the%20potential%20impact%20of%20COVID-19%20on%20life%20expectancy&rft.jtitle=PloS%20one&rft.au=Marois,%20Guillaume&rft.date=2020-09-17&rft.volume=15&rft.issue=9&rft.spage=e0238678&rft.epage=e0238678&rft.pages=e0238678-e0238678&rft.issn=1932-6203&rft.eissn=1932-6203&rft_id=info:doi/10.1371/journal.pone.0238678&rft_dat=%3Cgale_plos_%3EA635747801%3C/gale_plos_%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=2443876523&rft_id=info:pmid/32941467&rft_galeid=A635747801&rft_doaj_id=oai_doaj_org_article_2f90906e77dc4783871e8b0a18a89fa9&rfr_iscdi=true |