Cited by 159COVID-19 epidemiological studiesInsurance, Mortality, Demography, Risk ManagementCOVID-19 and healthcare impacts

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Estimating the burden of the COVID-19 pandemic on mortality, life expectancy and lifespan inequality in England and Wales: a population-level analysis

Open access
Aburto, Jose Manuel, Kashyap, Ridhi, Schöley, Jonas, Angus, Colin, Ermisch, John, Mills, Melinda C, Dowd, Jennifer Beam·2021·Journal of Epidemiology and Community Health

Published version of a preprint

Abstract

Background: Deaths directly linked to COVID-19 infection may be misclassified, and the pandemic may have indirectly affected other causes of death. To overcome these measurement challenges, we estimate the impact of the COVID-19 pandemic on mortality, life expectancy and lifespan inequality from week 10 of 2020, when the first COVID-19 death was registered, to week 47 ending 20 November 2020 in England and Wales through an analysis of excess mortality. Methods: We estimated age and sex-specific excess mortality risk and deaths above a baseline adjusted for seasonality with a systematic comparison of four different models using data from the Office for National Statistics. We additionally provide estimates of life expectancy at birth and lifespan inequality defined as the SD in age at death. Results: There have been 57 419 (95% prediction interval: 54 197, 60 752) excess deaths in the first 47 weeks of 2020, 55% of which occurred in men. Excess deaths increased sharply with age and men experienced elevated risks of death in all age groups. Life expectancy at birth dropped 0.9 and 1.2 years for women and men relative to the 2019 levels, respectively. Lifespan inequality also fell over the same period by 5 months for both sexes. Conclusion: Quantifying excess deaths and their impact on life expectancy at birth provide a more comprehensive picture of the burden of COVID-19 on mortality. Whether mortality will return to—or even fall below—the baseline level remains to be seen as the pandemic continues to unfold and diverse interventions are put in place.

Overview

AI snapshot

Written from the paper’s full text.

TL;DR

Using ONS weekly death registrations for England and Wales, the study estimates 57,419 excess deaths from week 10 to week 47 of 2020 and finds life expectancy at birth fell 0.9 years for women and 1.2 years for men versus 2019. Lifespan inequality also declined by about 5 months for both sexes, a pattern the authors attribute to mortality being concentrated at older ages.

Key findings

  • There were 57,419 (95% prediction interval 54,197–60,752) excess deaths in weeks 10–47 of 2020, a 15.1% (14.2–16.2) increase above baseline; 55.4% (31,791) were male and 44.6% (25,629) female. Male deaths exceeded expectation by 16.8% (15.4–18.0) and female deaths by 13.6% (12.2–14.9).
  • Excess deaths rose sharply with age: none among those younger than 15; 652 (395–903) at ages 15–44; 7,859 (7,065–8,645) at 45–64; 9,835 (8,814–10,833) at 65–74; 18,591 (16,845–20,435) at 75–84; and 20,641 (18,271–22,916) at 85+.
  • Life expectancy at birth over the first 47 weeks of 2020 was 82.6 (82.5–82.6) years for women and 78.7 (78.6–78.7) for men, reductions of 0.9 and 1.2 years relative to 2019. Lifespan inequality fell to 13.1 (13.0–13.1) years for women and 14.2 (14.2–14.3) for men, a reduction of nearly 5 months for both sexes.
  • Cumulative excess deaths at the end of the first wave (week 26) were 53,937 (53,092–54,746), followed by no excess mortality over summer months and an uptick from October 2020 as a second wave emerged.

Methods

  • Data: Office for National Statistics all-cause weekly death counts by week and sex from 2010 to week 47 of 2020 for England and Wales, plus population estimates/projections; six age groups (0–14, 15–44, 45–64, 65–74, 75–84, 85+) were used for weekly modelling, and 5-year age intervals for life expectancy and lifespan inequality.
  • Excess mortality: baseline deaths were estimated with four models—negative binomial generalised additive model, Poisson generalised additive model, extended Serfling generalised Poisson model, and an average of 2015–2019 weekly death rates; main estimates use the negative binomial model based on out-of-sample predictive performance. Excess deaths are observed weekly deaths minus baseline, summed from week 10 to week 47, with 95% prediction intervals.
  • Demographic analysis: life expectancy and lifespan inequality (SD in age at death) by sex were estimated using standard demographic techniques; 2020 estimates use the first 47 weeks with a proportionally adjusted mid-year population.

Limitations

  • The paper states that estimates are based on deaths registered so far, so registration delays may mean excess deaths and life expectancy losses are underestimated; no correction factors were applied because the extent of registration-delay bias is not properly understood. It also states that estimates do not account for weeks 48–52 of 2020 and that it is too early to clarify mortality displacement.
  • The paper states that cause-of-death attribution is not disentangled: preliminary ONS cause analysis suggests some unexplained excess may be undiagnosed COVID-19, while indirect effects on other causes remain uncertain.
  • Evident from the text: baseline model choice affects magnitude, with four models producing central excess-death estimates between 49,056 and 57,419, though the pattern of results did not substantively change; the analysis uses aggregated data and covers only through week 47, limiting inference beyond that period.

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Integrity signals

Registry

Crossref · 10.1136/jech-2020-215505

Cites

40 of 40 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Figures

Figure 1 Cumulative excess deaths in England and Wales through the COVID-19 pandemic weeks 10–47 of 2020 by sex. Shaded areas represent 95% prediction intervals. Excess deaths are defined as the total observed deaths subtracting the estimated baseline death count.
Figure 1 Cumulative excess deaths in England and Wales through the COVID-19 pandemic weeks 10–47 of 2020 by sex. Shaded areas represent 95% prediction intervals. Excess deaths are defined as the total observed deaths subtracting the estimated baseline death count.CC BY · PubMed Central
Figure 2 Cumulative excess deaths in England and Wales through the COVID-19 pandemic weeks 10–47 of 2020 by sex and age groups. Shaded areas represent 95% prediction intervals. Excess deaths are defined as the total observed deaths subtracting the estimated baseline mortality.
Figure 2 Cumulative excess deaths in England and Wales through the COVID-19 pandemic weeks 10–47 of 2020 by sex and age groups. Shaded areas represent 95% prediction intervals. Excess deaths are defined as the total observed deaths subtracting the estimated baseline mortality.CC BY · PubMed Central
Figure 3 Life expectancy and lifespan inequality (SD of ages at death) estimates for the periods 2001–2019, and for 2020 considering the first 47 weeks of the year by sex. Shaded areas represent 95% prediction intervals.
Figure 3 Life expectancy and lifespan inequality (SD of ages at death) estimates for the periods 2001–2019, and for 2020 considering the first 47 weeks of the year by sex. Shaded areas represent 95% prediction intervals.CC BY · PubMed Central

Verification

Claims the paper makes

33 Own result · 17 Not checked yet · 8 Own interpretation · 4 Own method · 2 No basis given

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Show all 37 claims

  • It may state two separate claims as one. 11
  • The quote only partly states this claim. 9
  • Probably not a substantial claim. 12
27 of 27
  • The paper relies on this without support.

    Vital registration in England and Wales has complete population coverage.

    “The population coverage of vital registration in England and Wales is complete.”
  • The paper relies on this without support.

    In the absence of the COVID-19 pandemic, weekly deaths in England and Wales from week 10 to week 47 of 2020 would have followed the mortality baseline estimated from pre-pandemic data by the fitted models.

    “We estimated the baseline number of deaths in the absence of COVID-19 by fitting four different models.”
  • The paper relies on this without support.

    Based on trends from past years, 92% of deaths in England and Wales are registered within 1 month of occurrence.

    “Based on trends from past years, 92% of deaths are registered within 1 month of occurrence.”
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Metadata

Authors
Aburto, J. M., Kashyap, R., Schöley, J., Angus, C., Ermisch, J., Mills, M. C., & Dowd, J. B.
Affiliations
  • Leverhulme Centre for Demographic Science, Department of Sociology and Nuffield College, University of Oxford, Oxford, UK
  • University of Oxford (GB)
  • University of Southern Denmark (DK)
  • University of Sheffield (GB)
Corresponding author
Kashyap, Ridhi
Venue
Journal of Epidemiology and Community Health
Publisher
BMJ
Published
2021-01-19
Volume
75
Issue
8
Pages
735-740
ISSN
  • 0141-7681 (ISSN-L)
  • 0143-005X
  • 1470-2738
OpenAlex
W3125353637
Cited by
159
References
46
Citations by year
2026: 9 · 2025: 11 · 2024: 20 · 2023: 30 · 2022: 44 · 2021: 42
FWCI
13.12
Type
journal article
Language
en
Open access
Locations
  • Journal of Epidemiology & Community Health (publishedVersion, cc-by)
  • medRxiv (acceptedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • University of Southern Denmark Research Portal (University of Southern Denmark) (publishedVersion, cc-by)
  • White Rose Research Online (University of Leeds, The University of Sheffield, University of York) (acceptedVersion)
  • LSHTM Research Online (London School of Hygiene and Tropical Medicine) (acceptedVersion)
Funders
  • British Academy (NIFBA19190679)
  • H2020 European Research Council (835079)
Topics
  • Physical Sciences › Mathematics › Modeling and Simulation › COVID-19 epidemiological studies
  • Social Sciences › Demography › Insurance, Mortality, Demography, Risk Management
  • Health Sciences › Medicine › Oncology › COVID-19 and healthcare impacts
Keywords
COVID-19 pandemic, excess mortality, life expectancy, lifespan inequality, age-specific mortality risk, sex differences in mortality, England and Wales
MeSH terms
COVID-19, SARS-CoV-2, Adolescent, Cause of Death, Child, Child, Preschool, England, Female, Humans, Infant, Infant, Newborn, Life Expectancy, Longevity, Male, Mortality, Wales, Cost of Illness, Pandemics

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