Life expectancy changes since COVID-19

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Abstract

The COVID-19 pandemic triggered an unprecedented rise in mortality that translated into life expectancy losses around the world, with only a few exceptions. We estimate life expectancy changes in 29 countries since 2020 (including most of Europe, the United States and Chile), attribute them to mortality changes by age group and compare them with historic life expectancy shocks. Our results show divergence in mortality impacts of the pandemic in 2021. While countries in western Europe experienced bounce backs from life expectancy losses of 2020, eastern Europe and the United States witnessed sustained and substantial life expectancy deficits. Life expectancy deficits during fall/winter 2021 among people ages 60+ and <60 were negatively correlated with measures of vaccination uptake across countries ( r ₆₀₊ = −0.86; two-tailed P < 0.001; 95% confidence interval, −0.94 to −0.69; r _<60 = −0.74; two-tailed P < 0.001; 95% confidence interval, −0.88 to −0.46). In contrast to 2020, the age profile of excess mortality in 2021 was younger, with those in under-80 age groups contributing more to life expectancy losses. However, even in 2021, registered COVID-19 deaths continued to account for most life expectancy losses.

Abstract

In 2021, life expectancies returned to pre-pandemic levels in parts of western Europe but further worsened in eastern Europe, the United States and Chile. Life expectancy deficits were negatively correlated with vaccine uptake in later 2021.

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Most cited references 41

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Life Expectancy and Mortality Rates in the United States, 1959-2017

Steven H Woolf, Heidi Schoomaker (2019)

US life expectancy has not kept pace with that of other wealthy countries and is now decreasing.

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The epidemiologic transition. A theory of the epidemiology of population change.

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Tracking excess mortality across countries during the COVID-19 pandemic with the World Mortality Dataset

Ariel Karlinsky, Dmitry Kobak (2021)

Comparing the impact of the COVID-19 pandemic between countries or across time is difficult because the reported numbers of cases and deaths can be strongly affected by testing capacity and reporting policy. Excess mortality, defined as the increase in all-cause mortality relative to the expected mortality, is widely considered as a more objective indicator of the COVID-19 death toll. However, there has been no global, frequently updated repository of the all-cause mortality data across countries. To fill this gap, we have collected weekly, monthly, or quarterly all-cause mortality data from 103 countries and territories, openly available as the regularly updated World Mortality Dataset. We used this dataset to compute the excess mortality in each country during the COVID-19 pandemic. We found that in several worst-affected countries (Peru, Ecuador, Bolivia, Mexico) the excess mortality was above 50% of the expected annual mortality (Peru, Ecuador, Bolivia, Mexico) or above 400 excess deaths per 100,000 population (Peru, Bulgaria, North Macedonia, Serbia). At the same time, in several other countries (e.g. Australia and New Zealand) mortality during the pandemic was below the usual level, presumably due to social distancing measures decreasing the non-COVID infectious mortality. Furthermore, we found that while many countries have been reporting the COVID-19 deaths very accurately, some countries have been substantially underreporting their COVID-19 deaths (e.g. Nicaragua, Russia, Uzbekistan), by up to two orders of magnitude (Tajikistan). Our results highlight the importance of open and rapid all-cause mortality reporting for pandemic monitoring. Countries around the world reported 4.2 million deaths from SARS-CoV-2 (the virus that causes COVID-19) from the beginning of pandemic until the end of July 2021, but the actual number of deaths is likely higher. While some countries may have imperfect systems for counting deaths, others may have intentionally underreported them. To get a better estimate of deaths from an event such as a pandemic, scientists often compare the total number of deaths in a country during the event to the expected number of deaths based on data from previous years. This tells them how many excess deaths occurred during the event. To provide a more accurate count of deaths caused by COVID-19, Karlinsky and Kobak built a database called the World Mortality Dataset. It includes information on deaths from all causes from 103 countries. Karlinsky and Kobak used the database to compare the number of reported COVID-19 deaths reported to the excess deaths from all causes during the pandemic. Some of the hardest hit countries, including Peru, Ecuador, Bolivia, and Mexico, experienced over 50% more deaths than expected during the pandemic. Meanwhile, other countries like Australia and New Zealand, reported fewer deaths than normal. This is likely because social distancing measures reduced deaths from infections like influenza. Many countries reported their COVID-19 deaths accurately, but Karlinsky and Kobak argue that other countries, including Nicaragua, Russia, and Uzbekistan, underreported COVID-19 deaths. Using their database, Karlinsky and Kobak estimate that, in those countries, there have been at least 1.4 times more deaths due to COVID-19 than reported – adding over 1 million extra deaths in total. But they note that the actual number is likely much higher because data from more than 100 countries were not available to include in the database. The World Mortality Dataset provides a more accurate picture of the number of people who died because of the COVID-19 pandemic, and it is available online and updated daily. The database may help scientists develop better mitigation strategies for this pandemic or future ones.

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Author and article information

Contributors

Jonas Schöley:

ORCID: http://orcid.org/0000-0002-3340-8518

schoeley@demogr.mpg.de

José Manuel Aburto:

ORCID: http://orcid.org/0000-0002-2926-6879

jose.aburto@lshtm.ac.uk

Ridhi Kashyap:

ORCID: http://orcid.org/0000-0003-0615-2868

ridhi.kashyap@nuffield.ox.ac.uk

Journal

Journal ID (nlm-ta): Nat Hum Behav

Journal ID (iso-abbrev): Nat Hum Behav

Title: Nature Human Behaviour

Publisher: Nature Publishing Group UK (London )

ISSN (Electronic): 2397-3374

Publication date (Electronic): 17 October 2022

Publication date PMC-release: 17 October 2022

Publication date (Print): 2022

Volume: 6

Issue: 12

Pages: 1649-1659

Affiliations

[1 ]GRID grid.419511.9, ISNI 0000 0001 2033 8007, Max Planck Institute for Demographic Research, ; Rostock, Germany

[2 ]GRID grid.4991.5, ISNI 0000 0004 1936 8948, Leverhulme Centre for Demographic Science and Department of Sociology, , University of Oxford, ; Oxford, UK

[3 ]GRID grid.4991.5, ISNI 0000 0004 1936 8948, Nuffield College, , University of Oxford, ; Oxford, UK

[4 ]GRID grid.10825.3e, ISNI 0000 0001 0728 0170, Interdisciplinary Centre on Population Dynamics, , University of Southern Denmark, ; Odense, Denmark

[5 ]GRID grid.8991.9, ISNI 0000 0004 0425 469X, Department of Population Health, London School of Hygiene and Tropical Medicine, ; London, UK

[6 ]GRID grid.8207.d, ISNI 0000 0000 9774 6466, Estonian Institute for Population Studies, , Tallinn University, ; Tallinn, Estonia

[7 ]GRID grid.5335.0, ISNI 0000000121885934, Cambridge Group for the History of Population and Social Structure, Department of Geography, , University of Cambridge, ; Cambridge, UK

Author information

Jonas Schöley http://orcid.org/0000-0002-3340-8518

José Manuel Aburto http://orcid.org/0000-0002-2926-6879

Ilya Kashnitsky http://orcid.org/0000-0003-1835-8687

Maxi S. Kniffka http://orcid.org/0000-0001-6603-2724

Hannaliis Jaadla http://orcid.org/0000-0002-8569-347X

Ridhi Kashyap http://orcid.org/0000-0003-0615-2868

Article

Publisher ID: 1450

DOI: 10.1038/s41562-022-01450-3

PMC ID: 9755047

PubMed ID: 36253520

SO-VID: 6fb97c5b-9033-4c69-be0c-2ca78c561f11

License:

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

History

Date received : 8 March 2022

Date accepted : 17 August 2022

Funding

Funded by: Marie Sklodowska-Curie grant agreement No 896821 Leverhulme Trust Large Centre Grant University of Oxford John Fell Fund ROCKWOOL Foundation’s Excess Deaths grant

Funded by: FundRef https://doi.org/10.13039/501100002301, Eesti Teadusagentuur (Estonian Research Council);

Award ID: PSG 669

Award Recipient : Hannaliis Jaadla

Funded by: Estonian Research Council grant PSG 669

Funded by: University of Oxford John Fell Fund European Research Council grant ERC-2021-CoG-101002587

Funded by: ROCKWOOL Foundation’s Excess Deaths grant

Funded by: Leverhulme Trust Large Centre GrantUniversity of Oxford John Fell Fund

Funded by: Marie Sklodowska-Curie grant agreement No 896821Leverhulme Trust Large Centre GrantUniversity of Oxford John Fell Fund

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Keywords: infectious diseases,epidemiology

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Keywords: infectious diseases, epidemiology

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Life expectancy changes since COVID-19

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Novel Coronavirus Disease COVID-19

Most cited references 41

Life Expectancy and Mortality Rates in the United States, 1959-2017

The epidemiologic transition. A theory of the epidemiology of population change.

Tracking excess mortality across countries during the COVID-19 pandemic with the World Mortality Dataset

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Cited by 55

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