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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 accessPublished 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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Claims the paper makes
33 Own result · 17 Not checked yet · 8 Own interpretation · 4 Own method · 2 No basis given
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“From that week until the end of week 47 on 20 November 2020, there were 436 102 registered deaths, from which an estimated 57 419 (54 197, 60 752) are excess mortality above the expected baseline (see figure 1).”
§ Estimating the burden of the COVID-19 pandemic on mortality, life expectancy and lifespan inequality in England and Wales: a population-level analysis > Results > Estimates of excess deaths
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
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In the paper
“Between 2 March and 20 November, male deaths exceeded the expectation by 16.8% (15.4, 18.0) and female death counts by 13.6% (12.2, 14.9).”
§ Estimating the burden of the COVID-19 pandemic on mortality, life expectancy and lifespan inequality in England and Wales: a population-level analysis > Results > Estimates of excess deaths
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Rests on an assumption: 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.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“First, we refitted the seasonal baseline without including the first 9 weeks of 2020. This adjustment did not have major effects on our estimates, and by taking the first 9 weeks into account, we aligned our predictions with the observed trend at the beginning of the year.”
§ Estimating the burden of the COVID-19 pandemic on mortality, life expectancy and lifespan inequality in England and Wales: a population-level analysis > Results > Sensitivity analysis
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Rests on an assumption: 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.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Similarly, male life expectancy increased from 77.1 (77.1, 77.2) to 79.9 (79.8, 79.9) years in the same period.”
§ Estimating the burden of the COVID-19 pandemic on mortality, life expectancy and lifespan inequality in England and Wales: a population-level analysis > Results > Estimates of life expectancy and lifespan inequality
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Using data from the first 47 weeks of 2020 yields an estimated life expectancy at birth of 82.6 (82.5, 82.6) and 78.7 (78.6, 78.7) for women and men, respectively, a reduction of 0.9 years for women and 1.2 years for men.”
§ Estimating the burden of the COVID-19 pandemic on mortality, life expectancy and lifespan inequality in England and Wales: a population-level analysis > Results > Estimates of life expectancy and lifespan inequality
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“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.”
- Also stated in: § Estimates of excess deaths · hedged
“From that week until the end of week 47 on 20 November 2020, there were 436 102 registered deaths, from which an estimated 57 419 (54 197, 60 752) are excess mortality above the expected baseline (see figure 1).”
- Also stated in: § Discussion · hedged
“We estimated 57 419 (54 197, 60 752) premature deaths due to the pandemic.”
§ Estimating the burden of the COVID-19 pandemic on mortality, life expectancy and lifespan inequality in England and Wales: a population-level analysis > Abstract > Results
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Rests on an assumption: 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.
- Also stated in: § Estimates of excess deaths · hedged
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Using data from the first 47 weeks of 2020 yields an estimated life expectancy at birth of 82.6 (82.5, 82.6) and 78.7 (78.6, 78.7) for women and men, respectively, a reduction of 0.9 years for women and 1.2 years for men.”
§ Estimating the burden of the COVID-19 pandemic on mortality, life expectancy and lifespan inequality in England and Wales: a population-level analysis > Results > Estimates of life expectancy and lifespan inequality
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Cumulative excess deaths at the end of the first wave (week 26 ending in June 29) were 53 937 (95% prediction interval: 53 092, 54 746) followed by no excess mortality over the summer months, before an uptick that started in October 2020 when a second wave emerged and excess deaths began to rise again.”
§ Estimating the burden of the COVID-19 pandemic on mortality, life expectancy and lifespan inequality in England and Wales: a population-level analysis > Results > Estimates of excess deaths
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- Rests on an assumption: 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.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Over the first 47 weeks of 2020, we estimate that lifespan inequality fell sharply to 13.1 (13.0, 13.1) and 14.2 (14.2, 14.3) years for women and men, respectively, corresponding to a reduction of nearly 5 months for both sexes.”
§ Estimating the burden of the COVID-19 pandemic on mortality, life expectancy and lifespan inequality in England and Wales: a population-level analysis > Results > Estimates of life expectancy and lifespan inequality
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“The first death attributable to COVID-19 in England and Wales was registered in the week starting on 2 March 2020 (week 10).”
§ Estimating the burden of the COVID-19 pandemic on mortality, life expectancy and lifespan inequality in England and Wales: a population-level analysis > Results > Estimates of excess deaths
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
- It may state two separate claims as one. 11
- The quote only partly states this claim. 9
- Probably not a substantial claim. 12
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The toll of the pandemic resulted in 7859 (7065, 8645) and 9835 (8814, 10 833) excess deaths among people between 45–64 and 64–74 years of age, respectively. These numbers are 17.6% (15.6, 19.7) and 16.0% (14.1, 17.9) above the baseline.”
§ Estimating the burden of the COVID-19 pandemic on mortality, life expectancy and lifespan inequality in England and Wales: a population-level analysis > Results > Estimates of excess deaths
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one. The quote only partly states this claim.
- Rests on an assumption: 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.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Our four models produce central estimates of the number of excess deaths between 49 056 and 57 419 depending on the choice of the model and its assumptions, but do not substantively affect the pattern of our results.”
§ Estimating the burden of the COVID-19 pandemic on mortality, life expectancy and lifespan inequality in England and Wales: a population-level analysis > Results > Sensitivity analysis
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
The quote only partly states this claim.
- Rests on an assumption: 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.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The largest numbers of lives lost were estimated among the groups 75–85 and 85 and older, with 17.2% (15.3, 19.2) and 13.7% (11.9, 15.4) more deaths than expected. Among the former, 18 591 (16 845, 20 435), excess deaths were estimated, while among the oldest age group, there were 20 641 (18 271, 22 916) deaths above the baseline.”
§ Estimating the burden of the COVID-19 pandemic on mortality, life expectancy and lifespan inequality in England and Wales: a population-level analysis > Results > Estimates of excess deaths
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
- Rests on an assumption: 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.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“We note that excess deaths derived from the baselines estimated from both the generalised additive models and generalised linear models indicated a higher magnitude of excess deaths than those using average mortality rates from the preceding 5 years as the baseline.”
§ Estimating the burden of the COVID-19 pandemic on mortality, life expectancy and lifespan inequality in England and Wales: a population-level analysis > Results > Sensitivity analysis
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
- Rests on an assumption: 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.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Excess deaths increased sharply with age and men experienced elevated risks of death in all age groups.”
- Also stated in: § Estimates of excess deaths · plain
“For older age groups, excess deaths rose sharply (see figure 2).”
§ Estimating the burden of the COVID-19 pandemic on mortality, life expectancy and lifespan inequality in England and Wales: a population-level analysis > Abstract > Results
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
The quote only partly states this claim.
- Rests on an assumption: 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.
- Also stated in: § Estimates of excess deaths · plain
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The toll of the pandemic resulted in 7859 (7065, 8645) and 9835 (8814, 10 833) excess deaths among people between 45–64 and 64–74 years of age, respectively. These numbers are 17.6% (15.6, 19.7) and 16.0% (14.1, 17.9) above the baseline.”
§ Estimating the burden of the COVID-19 pandemic on mortality, life expectancy and lifespan inequality in England and Wales: a population-level analysis > Results > Estimates of excess deaths
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
The quote only partly states this claim.
- Rests on an assumption: 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.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Disaggregating by age, we estimate no excess deaths among those younger than 15 years.”
§ Estimating the burden of the COVID-19 pandemic on mortality, life expectancy and lifespan inequality in England and Wales: a population-level analysis > Results > Estimates of excess deaths
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
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The quote only partly states this claim.
- Rests on an assumption: 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.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The 15–44-year-old age group accounted for 652 (395, 903) excess deaths (6.2% (3.6, 8.7) above the expected level).”
§ Estimating the burden of the COVID-19 pandemic on mortality, life expectancy and lifespan inequality in England and Wales: a population-level analysis > Results > Estimates of excess deaths
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
The quote only partly states this claim.
- Rests on an assumption: 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.
In the paper
“Moreover, our estimates for life expectancy fall 0.7 and 1.1 years below the official projected life expectancy in 2020 for women and men,36 respectively.”
§ Estimating the burden of the COVID-19 pandemic on mortality, life expectancy and lifespan inequality in England and Wales: a population-level analysis > Discussion
What the sources say
- Not checked yetcites [36] ONS . Life tables, principal projection, England and Wales - Office for National Statistics. Available: https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/lifeexpectancies/datasets/lifetablesprincipalprojectionenglandandwales [Accessed 14 Jul 2020].
plain- Asserted: passes — The authors put it forward as true.
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It may state two separate claims as one.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“The largest numbers of lives lost were estimated among the groups 75–85 and 85 and older, with 17.2% (15.3, 19.2) and 13.7% (11.9, 15.4) more deaths than expected. Among the former, 18 591 (16 845, 20 435), excess deaths were estimated, while among the oldest age group, there were 20 641 (18 271, 22 916) deaths above the baseline.”
§ Estimating the burden of the COVID-19 pandemic on mortality, life expectancy and lifespan inequality in England and Wales: a population-level analysis > Results > Estimates of excess deaths
hedged- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one. The quote only partly states this claim.
- Rests on an assumption: 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.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“In addition, we also estimated life expectancy using a piecewise constant hazard model and the results did not change.”
§ Estimating the burden of the COVID-19 pandemic on mortality, life expectancy and lifespan inequality in England and Wales: a population-level analysis > Results > Sensitivity analysis
plain- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
A result the paper reports from its own data — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Death rates during the pandemic were consistently higher among men in all groups compared with women (see online supplemental figure 3).”
§ Estimating the burden of the COVID-19 pandemic on mortality, life expectancy and lifespan inequality in England and Wales: a population-level analysis > Results > Estimates of excess deaths
plaincorrelational- Asserted: passes — The authors put it forward as true.
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The quote only partly states this claim.
- Rests on an assumption: 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.
The paper states this without a source or data behind it here, so there is nothing to check it against. The quote shows it is in the paper.
In the paper
“Excess deaths increased sharply over age and male deaths were estimated to exceed women in all age groups, with the exception of those above age 85.”
§ Estimating the burden of the COVID-19 pandemic on mortality, life expectancy and lifespan inequality in England and Wales: a population-level analysis > Discussion
hedged- Asserted: passes — The authors put it forward as true.
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- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
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The quote only partly states this claim.
- Rests on an assumption: 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.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Note the larger number of female excess deaths in the 85+ age group is due to there being 1.6 times more women in this age group compared with men.”
§ Estimating the burden of the COVID-19 pandemic on mortality, life expectancy and lifespan inequality in England and Wales: a population-level analysis > Results > Estimates of excess deaths
plaindirect- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
What the paper did — it cites no source for this, so there is none to check. The quote shows it is in the paper.
In the paper
“We performed several sensitivity analyses.”
§ Estimating the burden of the COVID-19 pandemic on mortality, life expectancy and lifespan inequality in England and Wales: a population-level analysis > Results > Sensitivity analysis
plain- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
A conclusion the paper draws from its own results — it cites no other source for it, so there is none to check. The quote shows it is in the paper.
In the paper
“Our estimates also do not account for excess mortality that occurred during weeks 48-52 of 2020, which are likely to further reduce life expectancy estimates for the full year.”
§ Estimating the burden of the COVID-19 pandemic on mortality, life expectancy and lifespan inequality in England and Wales: a population-level analysis > Discussion
hedgedconditional- Asserted: passes — The authors put it forward as true.
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It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“Life expectancy in England and Wales had been steadily improving for 50 years before stagnating in the past decade.34 35”
§ Estimating the burden of the COVID-19 pandemic on mortality, life expectancy and lifespan inequality in England and Wales: a population-level analysis > Discussion
What the sources say
- Not checked yetcites [34] source
- Not checked yetcites [35] JY H , Hendi AS . Recent trends in life expectancy across high income countries: retrospective observational study. BMJ 2018;362.
plain- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
In the paper
“Trends over the 20th century from high-income countries, including England and Wales, show that as life expectancy and the modal age at death have increased, lifespan inequality has tended to decrease.16”
§ Estimating the burden of the COVID-19 pandemic on mortality, life expectancy and lifespan inequality in England and Wales: a population-level analysis > Introduction
What the sources say
- Not checked yetcites [16] source
hedgedcorrelational- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“Based on preliminary cause of death analysis of other (non-COVID) causes by the ONS, deaths occurring from Alzheimer disease and dementia, ischaemic heart disease, cerebrovascular diseases, influenza and pneumonia and ‘symptoms signs and ill-defined conditions’ category were all higher between March and May 2020.22”
§ Estimating the burden of the COVID-19 pandemic on mortality, life expectancy and lifespan inequality in England and Wales: a population-level analysis > Discussion
What the sources say
- Not checked yetcites [22] ONS . Analysis of death registrations not involving coronavirus (COVID-19), England and Wales - Office for National Statistics. Available: https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/deaths/articles/analysisofdeathregistrationsnotinvolvingcoronaviruscovid19englandandwales28december2019to1may2020/technicalannex [Accessed 14 Jul 2020].
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
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It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“Insufficient testing capacity for SARS-CoV-2, the causative pathogen of coronavirus disease, especially during the early phases of the pandemic, misclassification of causes of death and definitional inconsistencies in counting COVID-19 deaths across different sources make the true toll of COVID-19 infections hard to estimate.2 3”
§ Estimating the burden of the COVID-19 pandemic on mortality, life expectancy and lifespan inequality in England and Wales: a population-level analysis > Introduction
What the sources say
- Not checked yetcites [2] source
- Not checked yetcites [3] ONS . The different uses of figures on deaths related to COVID-19 published by DHSC and the ONS - Office for National Statistics. Available: https://www.ons.gov.uk/news/statementsandletters/thedifferentusesoffiguresondeathsfromcovid19publishedbydhscandtheons [Accessed 3 Dec 2020].
plaindirect- Asserted: passes — The authors put it forward as true.
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- Load-bearing: unclear — It is unclear whether the paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“The toll of the pandemic had unequal impacts by age and sex in Europe and other regions.31–33”
§ Estimating the burden of the COVID-19 pandemic on mortality, life expectancy and lifespan inequality in England and Wales: a population-level analysis > Discussion
What the sources say
plaincorrelational- Asserted: passes — The authors put it forward as true.
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Probably not a substantial claim. The paper’s conclusions may not depend on it.
In the paper
“Between March and May 2020, 81.1% of all deaths and 86.5% of deaths involving COVID-19 were registered within 1 week of occurrence.21”
§ Estimating the burden of the COVID-19 pandemic on mortality, life expectancy and lifespan inequality in England and Wales: a population-level analysis > Methods > Data
What the sources say
- Not checked yetcites [21] ONS . Deaths involving COVID-19, England and Wales - Office for National Statistics. Available: https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/deaths/bulletins/deathsinvolvingcovid19englandandwales/deathsoccurringinmay2020#time-taken-for-the-deaths-in-march-april-and-may-to-be-registered [Accessed 14 Jul 2020].
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
In the paper
“According to the ONS, between 1 March and 30 June 2020, there were 50 335 deaths involving COVID-19, 46 736 (93%) of which assigned COVID-19 as the underlying cause of death based on information noted on the death certificate.21”
§ Estimating the burden of the COVID-19 pandemic on mortality, life expectancy and lifespan inequality in England and Wales: a population-level analysis > Discussion
What the sources say
- Not checked yetcites [21] ONS . Deaths involving COVID-19, England and Wales - Office for National Statistics. Available: https://www.ons.gov.uk/peoplepopulationandcommunity/birthsdeathsandmarriages/deaths/bulletins/deathsinvolvingcovid19englandandwales/deathsoccurringinmay2020#time-taken-for-the-deaths-in-march-april-and-may-to-be-registered [Accessed 14 Jul 2020].
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it. It may state two separate claims as one.
None of the sources cited for this claim have been checked yet.
In the paper
“This approach for estimating excess all-cause mortality has been widely used to quantify the mortality toll of previous epidemics such as influenza6 or HIV7 and has also begun to be applied for COVID-19.1 8”
§ Estimating the burden of the COVID-19 pandemic on mortality, life expectancy and lifespan inequality in England and Wales: a population-level analysis > Introduction
boosted- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
None of the sources cited for this claim have been checked yet.
In the paper
“While this metric provides an important measure of the burden of the pandemic on a society, simply counting total excess deaths does not provide an understanding of the substantial variation by age and sex over time in elevated mortality risks.10 11 nor does it allow for a comparison of current mortality conditions with past conditions due to changes in population age structure over the period.”
§ Estimating the burden of the COVID-19 pandemic on mortality, life expectancy and lifespan inequality in England and Wales: a population-level analysis > Introduction
plain- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
It may state two separate claims as one.
In the paper
“Historically, life expectancy increases have been accompanied by reductions in lifespan inequality due to mortality improvements at younger ages, although more recent studies have found that life expectancy improvements can occur even without accompanying reductions in lifespan inequality.13”
§ Estimating the burden of the COVID-19 pandemic on mortality, life expectancy and lifespan inequality in England and Wales: a population-level analysis > Discussion
What the sources say
- Not checked yetcites [13] source
plaindirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: passes — The paper’s conclusions depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim.
In the paper
“Recent evidence suggests that reversals and stagnation in life expectancy among developed countries are usually a result of mid-life mortality crises.35”
§ Estimating the burden of the COVID-19 pandemic on mortality, life expectancy and lifespan inequality in England and Wales: a population-level analysis > Discussion
What the sources say
- Not checked yetcites [35] JY H , Hendi AS . Recent trends in life expectancy across high income countries: retrospective observational study. BMJ 2018;362.
hedgeddirect- Asserted: passes — The authors put it forward as true.
- Checkable: passes — It can be checked against evidence.
- Load-bearing: fails — The paper’s conclusions may not depend on it.
- Based: passes — The paper gives a reason why it holds.
Probably not a substantial claim. The paper’s conclusions may not depend on it.
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.”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“A decrease in the number of cancer-attributed deaths can be explained by mortality displacement (19, 20)”
From Socioeconomic status determines COVID-19 incidence and related mortality in Santiago, Chile (2021) · cites this paper as [20]
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
Each contradiction between two passages listed here was confirmed by an independent check.
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
§ Estimating the burden of the COVID-19 pandemic on mortality, life expectancy and lifespan inequality in England and Wales: a population-level analysis > Abstract > Background
“week 47 ending 20 November 2020”
§ Estimating the burden of the COVID-19 pandemic on mortality, life expectancy and lifespan inequality in England and Wales: a population-level analysis > Introduction
“week 10 (March 2–8)”
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
§ Estimating the burden of the COVID-19 pandemic on mortality, life expectancy and lifespan inequality in England and Wales: a population-level analysis > Results > Estimates of excess deaths
“between 45–64 and 64–74 years of age, respectively”
§ Estimating the burden of the COVID-19 pandemic on mortality, life expectancy and lifespan inequality in England and Wales: a population-level analysis > Methods > Data
“six age-groups (0–14, 15–44, 45–64, 65–74, 75–84 and 85-older years of age)”
Rated minor: it would not touch a result — a value no result rests on, a p-value that stays on the same side of the significance level, or a conflict that is clerical, resolved elsewhere in the paper, or outside its own findings.
In the paper
§ Estimating the burden of the COVID-19 pandemic on mortality, life expectancy and lifespan inequality in England and Wales: a population-level analysis > Results > Estimates of excess deaths
“week 26 ending in June 29”
§ Estimating the burden of the COVID-19 pandemic on mortality, life expectancy and lifespan inequality in England and Wales: a population-level analysis > Introduction
“week 10 (March 2–8)”
Citations
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Sorted by citations
Socioeconomic status determines COVID-19 incidence and related mortality in Santiago, Chile
Mena, G. E., Martinez, P. P., Mahmud, A. S., Marquet, P. A., Buckee, C. O., & Santillana, M. (2021) · Science · doi:10.1126/science.abg5298 · Cited by 431
Aburto, J. M., Schöley, J., Kashnitsky, I., Zhang, L., Rahal, C., Missov, T. I., Mills, M. C., Dowd, J. B., & Kashyap, R. (2022) · International Journal of Epidemiology · doi:10.1093/ije/dyab207 · Cited by 531
“A widely-used approach to quantify the burden of the pandemic using all-cause mortality is through the analysis of excess mortality, defined as the number of deaths observed during the pandemic above a baseline of recent trends (Pifarr´e i Arolas et al., 2021; Aburto et al., 2021).”
Self-citationIslam, N., Jdanov, D. A., Школьников, В. М., Khunti, K., Kawachi, I. I., White, M. J., Lewington, S., & Lacey, B. (2021) · BMJ · doi:10.1136/bmj-2021-066768 · Cited by 268
“Country specific estimates of life expectancy, largely based on partial data in 2020, have been reported for the US, 27 28 England and Wales, 29 and Spain.”
InfluentialModig, K., Ahlbom, A., & Ebeling, M. (2020) · European Journal of Public Health · doi:10.1093/eurpub/ckaa218 · Cited by 127
Sensitivity Analysis of Excess Mortality due to the COVID‐19 Pandemic
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Significant impacts of the COVID-19 pandemic on race/ethnic differences in US mortality
Aburto, J. M., Tilstra, A. M., Floridi, G., & Dowd, J. B. (2022) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2205813119 · Cited by 99
Self-citationde Lima, E. E. C., Vilela, E., Peralta, A., Rocha, M. G., Queiroz, B. L., Gonzaga, M. R., Díaz, M. E. P., Martínez-Folgar, K., García-Guerrero, V. M., & Freire, F. H. M. D. A. (2021) · Genus · doi:10.1186/s41118-021-00139-1 · Cited by 94
“Under normal conditions, changes in mortality tend to be steady, making its interpretation more direct; under a temporary shock (the pandemic), its interpretation might be misleading (Aburto et al., 2021b; Heuveline, 2021).”
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Risk factors for developing COVID-19: a population-based longitudinal study (COVIDENCE UK)
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Informal Caregiving and Alzheimer’s Disease: The Psychological Effect
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Linking excess mortality to mobility data during the first wave of COVID-19 in England and Wales
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“We estimate that about 62,200 excess deaths occurred in England and Wales during weeks 13–33 of 2020 with respect to what was expected from previous years, in line with other findings (Aburto et al., 2021; Office for National Statistics, 2020b).”
Cuéllar, L., Torres, I., Romero-Severson, E. O., Mahesh, R., Ortega, N., Pungitore, S. A., Hengartner, N., & Ke, R. (2021) · International Journal of Epidemiology · doi:10.1093/ije/dyab163 · Cited by 54
Trends in health expectancies: a systematic review of international evidence
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Estimates of pandemic excess mortality in India based on civil registration data
Banaji, M., & Gupta, A. (2022) · PLOS Global Public Health · doi:10.1371/journal.pgph.0000803 · Cited by 45
“All-cause mortality data, where available, has been used to understand the overall mortality impact of the pandemic [11, 12].”
MethodThe Impact of the Covid-19 Pandemic on Global Population Ageing
Harper, S. E. (2021) · Journal of Population Ageing · doi:10.1007/s12062-021-09330-w · Cited by 47
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Robustness and bias of European excess death estimates in 2020 under varying model specifications
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MethodSelf-citationGobiņa, I., Avotiņš, A., Kojalo, U., Strēle, I., Pildava, S., Villeruša, A., & Briģis, Ģ. (2022) · BMC Public Health · doi:10.1186/s12889-022-13491-4 · Cited by 34
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“Most studies to date on life expectancy during the COVID-19 pandemic have focused on 2020 and 2021 (Aburto, Kashyap, et al., 2021; Aburto, Sch ¨ oley, et al., 2021; Aburto, Sch ¨ oley, Kashnitsky, & Kashyap, 2022; Andrasfay & Goldman, 2021a, 2021b; Canudas-Romo, Houle, & Adair, 2022; Eurostat,…”
BackgroundInfluentialBonnet, F., Grigoriev, P., Sauerberg, M., Alliger, I., Mühlichen, M., & Camarda, C. G. (2024) · Nature Communications · doi:10.1038/s41467-024-48689-0 · Cited by 37
Impact of COVID-19 on life expectancy at birth in India: a decomposition analysis
Yadav, S., Yadav, P. K., & Yadav, N. (2021) · BMC Public Health · doi:10.1186/s12889-021-11690-z · Cited by 31
“The study explores the repercussions of the mortality pattern of COVID-19 disease as one of the causes of death [38] on the life expectancy at birth (e 0 ) and inequality in age at death (G 0 ) [74, 76] for India in the entire period of 2010 – 2020.”
BackgroundInfluentialMcCartney, G., Leyland, A. H., Walsh, D., & Dundas, R. (2020) · Journal of Epidemiology & Community Health · doi:10.1136/jech-2020-214373 · Cited by 28
A first analysis of excess mortality in Switzerland in 2020
Locatelli, I., & Rousson, V. (2021) · PLoS ONE · doi:10.1371/journal.pone.0253505 · Cited by 27
“[3] (the latter based on the first 47 weeks of 2020 only).”
BackgroundMasters, R. K., Woolf, S. H., & Aron, L. Y. (2022) · The Journals of Gerontology Series B · doi:10.1093/geronb/gbac028 · Cited by 26
Life expectancy drop in 2020. Estimates based on Human Mortality Database
Mazzuco, S., & Campostrini, S. (2022) · PLoS ONE · doi:10.1371/journal.pone.0262846 · Cited by 25
Divergent trends in lifespan variation during mortality crises
Vigezzi, S., Aburto, J. M., Permanyer, I., & Zarulli, V. (2022) · Demographic Research · doi:10.4054/demres.2022.46.11 · Cited by 25
Self-citationHiam, L. C., Minton, J., & McKee, M. (2021) · Journal of the Royal Society of Medicine · doi:10.1177/01410768211011742 · Cited by 24
“Conversely, analysis of the burden of COVID-19 on mortality in the UK found lifespan inequality decreased during the first year of the pandemic, while e0 also decreased.(3) In both examples, the utility of life disparity is as complementary to e0 – a rising life disparity in the context of stagnating or falling e0 may…”
BackgroundAssessing COVID-19 pandemic excess deaths in Brazil: Years 2020 and 2021
Colonia, S. R. R., Cardeal, L. M., de Oliveira, R. A., & Trinca, L. A. (2023) · PLoS ONE · doi:10.1371/journal.pone.0272752 · Cited by 25
“398 Studies around the world [4, 5, 14,40, 41] reported COVID-19 mortality affects more 399 males than females, although some authors did not find relevant differences once 400 baseline is considered [42].”
A particle swarm optimization approach for predicting the number of COVID-19 deaths
Haouari, M., & Mhiri, M. (2021) · Scientific Reports · doi:10.1038/s41598-021-96057-5 · Cited by 23
The effect of the COVID-19 pandemic on life expectancy in 27 countries
Huang, G., Guo, F., Zimmermann, K. F., Liu, L., Taksa, L., Cheng, Z., Tani, M., & Franklin, M. (2023) · Scientific Reports · doi:10.1038/s41598-023-35592-9 · Cited by 23
León-Gómez, I., Mazagatos, C., Delgado‐Sanz, C., Frías, L., Vega‐Piris, L., Rojas‐Benedicto, A., & Larrauri, A. (2021) · Viruses · doi:10.3390/v13122423 · Cited by 24
“On the other hand, the Institute of Health Carlos III’s MoMo estimates in the first wave may also capture mortality “indirectly” related to COVID-19—that is, deaths from other non-COVID-19 causes but related to the pandemic situation—with more impact in the first wave compared to second and third waves: strict lockdow…”
BackgroundProgress Stalled? The Uncertain Future of Mortality in High‐Income Countries
Dowd, J. B., Polizzi, A., & Tilstra, A. M. (2025) · Population and Development Review · doi:10.1111/padr.12687 · Cited by 21
Self-citationTrias‐Llimós, S., & Spijker, J. (2022) · BMJ Open · doi:10.1136/bmjopen-2021-053205 · Cited by 20
Currie, J., Boyce, T., Evans, L., Luker, M., Senior, S. L., Hartt, M. D., Cottrell, S. L., Lester, N., Huws, D., Humphreys, C., et al. (2021) · Public Health · doi:10.1016/j.puhe.2021.01.025 · Cited by 19
The impact of mortality shocks on modelling and insurance valuation as exemplified by COVID-19
Schnürch, S., Kleinow, T., Korn, R., & Wagner, A. (2022) · Annals of Actuarial Science · doi:10.1017/s1748499522000045 · Cited by 23
“…on COVID-19-related deaths because these might give an incomplete account for multiple reasons (such as cause of death misclassifications and collateral effects of the pandemic on other causes of death, see Aburto et al., 2021; Institute for HealthMetrics and Evaluation 2021b for further details).”
Lundberg, C. E., Santosa, A., Björk, J., Brandén, M., Cronie, O., Lindgren, M., Edqvist, J., Åberg, M., Adiels, M., & Rosengren, A. (2023) · European Journal of Public Health · doi:10.1093/eurpub/ckad086 · Cited by 15
Cao, G., Liu, J., Liu, M., & Liang, W. (2023) · Journal of Global Health · doi:10.7189/jogh.13.06042 · Cited by 19
Polizzi, A., Zhang, L., Timonin, S., Gupta, A., Dowd, J. B., Leon, D. A., & Aburto, J. M. (2024) · PNAS Nexus · doi:10.1093/pnasnexus/pgae508 · Cited by 15
Self-citationBonnet, F., Grigoriev, P., Sauerberg, M., Alliger, I., Mühlichen, M., & Camarda, C. G. (2024) · Journal of Epidemiology and Global Health · doi:10.1007/s44197-024-00200-0 · Cited by 17
“Excess mortality is considered by scholars to be the gold standard for estimating the global impact of SARS-CoV-2 [6-7], which is why numerous studies have estimated excess mortality for a large number of countries [8-16].”
Post-Pandemic Urbanism: Criteria for a New Normal
Neuman, M., Chelleri, L., & Schuetze, T. (2021) · Sustainability · doi:10.3390/su131910600 · Cited by 17
“The pandemic has accelerated this decline [19].”
Social Determinants of Remaining Life Expectancy at Age 60: A District-Level Analysis in Germany
Siegel, A., Schug, J. F., & Rieger, M. A. (2022) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph19031530 · Cited by 17
Adult death registration in Matlab, rural Bangladesh: completeness, correlates, and obstacles
Haider, M. M., Alam, N., Bashar, M. I., et al. (2021) · Genus · doi:10.1186/s41118-021-00125-7 · Cited by 16
“Such data are thus extensively used in high-income and some uppermiddle-income countries to measure monthly or weekly levels of excess mortality during the COVID-19 pandemic (Aburto et al., 2021; Economic Commission for Latin America and the Caribbean (ECLAC)., 2021).”
BackgroundGeyter, C. D., Masciocchi, M., & Gobrecht-Keller, U. (2022) · Human Reproduction · doi:10.1093/humrep/deac031 · Cited by 16
Bennett, H., Kingston, A., Lourida, I., Robinson, L. A., Corner, L., Brayne, C., Matthews, F. E., & Jagger, C. (2021) · EClinicalMedicine · doi:10.1016/j.eclinm.2021.101041 · Cited by 16
Caída de la esperanza de vida en distritos de Madrid en 2020: relación con determinantes sociales
Olalla, J. M. D., Valero-Oteo, I., Moreno-Vázquez, S., et al. (2021) · Gaceta Sanitaria · doi:10.1016/j.gaceta.2021.07.004 · Cited by 14
The Demographic Drivers of Grief and Memory After Genocide in Guatemala
Alburez‐Gutierrez, D. (2022) · Demography · doi:10.1215/00703370-9975747 · Cited by 13
Impacts of the COVID-19 pandemic on life expectancy at birth in Asia
Mo, Y., Feng, Q., & Gu, D. (2023) · BMC Public Health · doi:10.1186/s12889-023-16426-9 · Cited by 14
Excess Mortality During the COVID-19 Pandemic in Jordan: Secondary Data Analysis
Khader, Y. S., & Nsour, M. A. (2021) · JMIR Public Health and Surveillance · doi:10.2196/32559 · Cited by 13
“…deaths in Jordan [2] does not reflect the true burden of the pandemic because some people with COVID-19 died without All-cause mortality and estimates of excess deaths are commonly used in different countries to estimate the burden of COVID-19 and assess its direct and indirect effects [3,4].”
Schnier, C., McCarthy, A., Morales, D. R., Akbari, A., Sofat, R., Dale, C. E., Takhar, R., Mamas, M. A., Khunti, K. K., Zaccardi, F., et al. (2023) · The Lancet Healthy Longevity · doi:10.1016/s2666-7568(23)00105-8 · Cited by 13
Rotulo, A., Kondilis, E., Thwe, T., Gautam, S., Torcu, Ö., Vera‐Montoya, M., Marjan, S., Gazi, M. I., Putri, A. S., Hasan, R. B., et al. (2023) · PLOS Global Public Health · doi:10.1371/journal.pgph.0001148 · Cited by 16
UNEQUAL CHANCES? INEQUALITIES IN MORTALITY IN IRELAND
Duffy, K., Connolly, S., Nolan, A., & Maître, B. (2022) · doi:10.26504/rs145 · Cited by 15
COVID-19, Inequality and Older People
Lewis, C., Phillipson, C., Yarker, S., et al. (2023) · Policy Press eBooks · doi:10.56687/9781447367468 · Cited by 12
COVID-19, Inequality and Older People: Developing Community-Centred Interventions
Phillipson, C., Yarker, S., Lang, L., Doran, P., Goff, M., & Buffel, T. (2021) · International Journal of Environmental Research and Public Health · doi:10.3390/ijerph18158064 · Cited by 13
“Reflecting on all these, we know that the pandemic has already accelerated the decline in life expectancy which had started to affected poorer areas in England and Wales over the period 2010–2020: Aburto and colleagues [36] estimate a fall of about one year since the start of the pandemic.”
Marinetti, I., Jdanov, D. A., Grigoriev, P., Klüsener, S., & Janssen, F. (2023) · PLoS ONE · doi:10.1371/journal.pone.0295763 · Cited by 10
Zhang, W., Fumey, M. P., Bekun, F. V., Karikari, F. A., Yeboah, S. D., Aboagye, G. T., & Yeboah, E. (2025) · Air Quality Atmosphere & Health · doi:10.1007/s11869-025-01712-9 · Cited by 12
“However, the COVID-19 pandemic has had a detrimental effect on LEO, with projections estimating a loss of 1.2 years in 2020 (Aburto et al. 2021).”
InfluentialBonnet, F., & Camarda, C. G. (2024) · PLoS ONE · doi:10.1371/journal.pone.0293752 · Cited by 11
Normalized lifespan inequality: disentangling the longevity–lifespan variability nexus
Permanyer, I., & Shi, J. (2022) · Genus · doi:10.1186/s41118-021-00150-6 · Cited by 12
Estimation of Excess All-Cause Mortality Due to COVID-19 in Thailand
Wilasang, C., Modchang, C., Lincharoen, T., & Chadsuthi, S. (2022) · Tropical Medicine and Infectious Disease · doi:10.3390/tropicalmed7070116 · Cited by 11
“We employed the standard interpolation approach [18] to estimate the monthly population by gender and age group.”
MethodLeveraging deep neural networks to estimate age-specific mortality from life expectancy at birth
Nigri, A., Levantesi, S., & Aburto, J. M. (2022) · Demographic Research · doi:10.4054/demres.2022.47.8 · Cited by 11
“…in several countries (Nigri, Barbi, and Levantesi 2021), including the United States and the United Kingdom (Mehta, Abrams, and Myrskylä 2020; Aburto et al. 2021; Ho and Hendi 2018) but also around the globe in contexts where timely data is needed and often reported with significant delays,…”
BackgroundMethodInfluentialSelf-citationExcess mortality and COVID-19 in Sweden in 2020: A demographic account
Kolk, M., Drefahl, S., Wallace, M., & Andersson, G. (2022) · Vienna Yearbook of Population Research · doi:10.1553/populationyearbook2022.res2.2 · Cited by 10
COVID-19 Patients' Experiences during the Pandemic: A Phenomenology Study
Thirarattanasunthon, P., Kongnarong, L., Chanachon, N., Adesina, F. P., Ageru, T. A., Pham, T. T., Stanikzai, M. H., & Suwanbamrung, C. (2024) · Journal of Human Earth and Future · doi:10.28991/hef-2024-05-01-04 · Cited by 9
“According to a recent study, many countries have seen a sharp rise in the percentage of elderly fatalities [30].”
BackgroundOf not passing: homelessness, addiction, mental health and care during COVID-19
Lenhard, J., Margetts, M., & Meng, E. (2022) · Medical Humanities · doi:10.1136/medhum-2021-012367 · Cited by 11
“The Health Foundation; Aburto et al .”
Assessing the impact of human mobility to predict regional excess death in Ecuador
Cuéllar, L., Torres, I., Romero-Severson, E. O., Mahesh, R., Ortega, N., Pungitore, S. A., Ke, R., & Hengartner, N. (2022) · Scientific Reports · doi:10.1038/s41598-021-03926-0 · Cited by 9
Two complementary approaches to estimate an excess of mortality: The case of Switzerland 2022
Locatelli, I., & Rousson, V. (2023) · PLoS ONE · doi:10.1371/journal.pone.0290160 · Cited by 9
“A generalized additive model with a negative binomial distribution was applied by [13] to mortality data in England for the period 2010–19, while a Poisson model was applied by [14] to mortality data of 2016– 19 in 29 high-income countries.”
MethodA ketogenic diet can mitigate SARS-CoV-2 induced systemic reprogramming and inflammation
Palermo, A., Li, S., ten Hoeve, J., Chellappa, A., Morris, A., Dillon, B. J., Ma, F., Wang, Y., Cao, E. Z., Shabane, B., et al. (2023) · Communications Biology · doi:10.1038/s42003-023-05478-7 · Cited by 9
“evere acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the cause of coronavirus disease 2019 (COVID-19), has irreversibly impacted human health and life 1 .”
Modifying impact of environmental factors on the course of an epidemic process
Зайцева, Н. В., Popova, A. Y., Kleyn, S. V., Kiryanov, D. A., Chigvintsev, V. М., & Glukhikh, M. V. (2022) · Hygiene and Sanitation · doi:10.47470/0016-9900-2022-101-11-1274-1282 · Cited by 7
Impact of the COVID-19 pandemic on the age-sex pattern of COVID-19 deaths in India
Samir, K. C., & Moradhvaj (2023) · Asian Population Studies · doi:10.1080/17441730.2023.2193077 · Cited by 8
“…Analysis (IIASA), Laxenburg, Austria; Wittgenstein Centre for Demography and Global Human Capital (IIASA, VID/OAW, WU), Vienna, Austria pandemic differs by country and demographic characteristics such as age and sex (Aburto et al., 2021, 2022; Dowd et al., 2020; United Nations, 2022; WHO, 2022).”
BackgroundA Workflow for Estimating and Visualising Excess Mortality During the COVID-19 Pandemic
Konstantinoudis, G., Gómez‐Rubio, V., Cameletti, M., Pirani, M., Baio, G., & Blangiardo, M. (2023) · The R Journal · doi:10.32614/rj-2023-055 · Cited by 7
Ahmadi‐Abhari, S., Bandosz, P., Shipley, M. J., Lindbohm, J. V., Dehghan, A., Elliott, P., & Mika Kivimaki, B. (2025) · PLoS Medicine · doi:10.1371/journal.pmed.1004541 · Cited by 7
Decrease in Life Expectancy in Germany in 2020: Men from Eastern Germany Most Affected
Luy, M., Sauerberg, M., Muszyńska, M. M., & di Lego, V. (2021) · Comparative Population Studies · doi:10.12765/cpos-2021-20 · Cited by 7
Socioeconomic Disparities Do Not Explain the U.S. International Disadvantage in Mortality
Barbiéri, M. (2022) · The Journals of Gerontology Series B · doi:10.1093/geronb/gbac030 · Cited by 8
Abdallah, W., Kanzari, D., Sallami, D., et al. (2022) · Computational Intelligence · doi:10.1111/coin.12516 · Cited by 7
Mortality in Switzerland in 2021
Locatelli, I., & Rousson, V. (2022) · PLoS ONE · doi:10.1371/journal.pone.0274295 · Cited by 8
“The latter has been evaluated for a large number of countries both from the point of view of the excess mortality (or excess deaths) [1-4] and from the perspective of the loss of life expectancy [5-8].”
BackgroundCurrie, J., Schilling, H. T., Evans, L., Boyce, T., Lester, N., Greene, G., Little, K. E., Humphreys, C., Huws, D., Yeoman, A. D., et al. (2022) · Journal of Public Health · doi:10.1093/pubmed/fdac133 · Cited by 10
A Statistical Analysis of Excess Mortality Mean at Covid-19 in 2020-2021
Raihen, M. N., Akter, S., Tabassum, F., Jahan, F., & Begum, S. (2023) · Computational Journal of Mathematical and statistical Sciences · doi:10.21608/cjmss.2023.229207.1014 · Cited by 8
“Researchers Aburto, Basellini, Németh and Stokes [17, 18, 19, 20] have used a wide variety of death rates, including crude death rates (CDRs) and age-specific death rates; See Németh et al.”
BackgroundCheshmehzangi, A. (2022) · Urban sustainability · doi:10.1007/978-981-19-3167-3_4 · Cited by 6
On the feasibility of reverse mortgages in Colombia
Franco, J. B., Cifuentes, J. C. A., Mosquera, J. A. C., et al. (2021) · International Journal of Housing Markets and Analysis · doi:10.1108/ijhma-05-2021-0063 · Cited by 6
Höhn, A., Lomax, N., Rice, H. P., et al. (2024) · BMJ Open · doi:10.1136/bmjopen-2023-076704 · Cited by 6
“39 On another note, recent period effects such as the consequences of austerity measures, 40 the COVID-19 pandemic, 41 and the subsequent cost- of-living crisis 42 highlight that deteriorations in population health can occur throughout the life course of individuals.”
BackgroundSelf-citationBirhanu, A., Ayana, G. M., Bayu, M., et al. (2021) · SAGE Open Medicine · doi:10.1177/20503121211062793 · Cited by 6
Tamasiga, P., Guta, A. T., Onyeaka, H. N., & Kalane, M. S. (2022) · Journal of Social and Economic Development · doi:10.1007/s40847-022-00184-2 · Cited by 6
“In the same vein, Aburto et al. (2021) asserted that the study of life expectancy in the context of the COVID-19 pandemic matters because it enables us to compare the cumulative impacts of the pandemic against past mortality shocks and recent trends across different countries. Berkman et al. (2014) and Swift (2011) do…”
BackgroundInfluentialKajdanek, K., & Radzimski, A. (2025) · Cities · doi:10.1016/j.cities.2025.106060 · Cited by 5
Zhao, J. V., Yao, M., & Liu, Z. (2024) · Aging · doi:10.18632/aging.205711 · Cited by 5
Quantifying the hidden impact of COVID ‐19 pandemic: The cytology perspective
Yousefi, E., Cibas, E. S., & Mito, J. K. (2022) · Cancer Cytopathology · doi:10.1002/cncy.22613 · Cited by 5
Mikolai, J., Dorey, P., Keenan, K. L., et al. (2023) · Social Science & Medicine · doi:10.1016/j.socscimed.2023.116330 · Cited by 5
Benczes, R., Benczés, I., Ságvári, B., & Szabó, L. P. (2024) · Cognitive Linguistics · doi:10.1515/cog-2023-0050 · Cited by 5
Human costs of the first wave of the COVID-19 pandemic in the major epicentres in Italy
Ghislandi, S., Muttarak, R., Sauerberg, M., & Scotti, B. (2021) · Vienna Yearbook of Population Research · doi:10.1553/populationyearbook2022.res2.1 · Cited by 5
Pou, S. A., Dı́az, M. D. P., & González, L. M. (2022) · Revista Brasileira de Epidemiologia · doi:10.1590/1980-549720220018 · Cited by 4
Vanthomme, K., Gadeyne, S., Devleesschauwer, B., & den Borre, L. V. (2023) · Journal of Public Health · doi:10.1007/s10389-023-02180-0 · Cited by 4
“However, most of the existing mortality studies by migrant group or ethnic minority group are based on data from the first wave of the epidemic (Vanthomme et al. 2021; Indseth et al. 2021; Aburto et al. 2021; Rostila et al. 2021; Kjøllesdal et al. 2022; Khlat et al. 2022).”
Impact of the COVID-19 Pandemic on Life Expectancy in South Korea, 2019–2022
Song, S. J., & Lim, D. (2025) · Healthcare · doi:10.3390/healthcare13030258 · Cited by 4
“Numerous studies have documented changes in life expectancy due to the COVID-19 pandemic [12–23], demonstrating its significant impact worldwide.”
An Overlapping Cohorts Perspective of Lifespan Inequality
Arolas, H. P. I., Andrade, J., & Myrskylä, M. (2025) · Demography · doi:10.1215/00703370-11876384 · Cited by 3
Assessing excess mortality in Vienna and Austria after the first year of the COVID-19 pandemic
Bauer, R., Speringer, M., Frühwirt, P., Seidl, R., & Trautinger, F. (2022) · Vienna Yearbook of Population Research · doi:10.1553/populationyearbook2022.dat.1 · Cited by 4
“For assessing the direct and indirect impacts of COVID-19 on overall mortality, excess mortality for all causes of deaths is a well-established indicator (Aburto et al., 2021; Aron et al., 2020; Ghislandi et al., 2021; Schöley, 2021).”
BackgroundDivergent Trends of Lifespan Variation During Mortality CrisesPreprint
Vigezzi, S., Aburto, J. M., Permanyer, I., & Zarulli, V. (2021) · doi:10.31235/osf.io/ze57r · Cited by 4
“The greater mortality of older individuals compared to children (Bhopal et al. 2021) suggests that our results could hold during the current pandemic, as shown by Aburto et al. (2021) for England and Wales in 2020.”
BackgroundResultSelf-citationEvolution of Life Expectancy and Lifespan Variation in Sub-Saharan AfricaPreprint
Mejía‐Guevara, I., Gazeley, U., Nabukalu, D., & Aburto, J. M. (2025) · medRxiv · doi:10.1101/2025.05.20.25328051 · Cited by 3
“…as those following the dissolution of the Soviet Union (Aburto and van Raalte 2018), increased violence in Latin America (Aburto and Beltrán-Sánchez 2019; García and Aburto 2019), historical epidemics and famines (Vigezzi et al. 2022), and more recently, the COVID-19 pandemic (Aburto et al. 2021).”
InfluentialSelf-citationAño y medio de pandemia: años de vida perdidos debido al COVID-19 en México
Novak, B., & Castillo, P. V. (2022) · Notas de población · doi:10.18356/16810333-48-113-8 · Cited by 3
A Statistical Analysis of Positive Excess Mortality at Covid-19 in 2020-2021
Raihen, M. N., Akter, S., Tabassum, F., Jahan, F., & Sardar, M. N. (2023) · Journal of Mathematics and Statistics Studies · doi:10.32996/jmss.2023.4.3.2 · Cited by 3
“Researchers have used a wide variety of death rates, including crude death rates (CDRs) (Aburto et al., 2021; Basellini et al., 2021; Németh et al., 2021; Stokes et al., 2021) and age-specific death rates (Németh et al., 2021) and age-standardized death dates (SDRs) (Islam et al., 2021; Krieger et…”
Sustainability: a multifaceted important aspect of cancer care
O’Reilly, S., Weadick, C., & Keogh, R. J. (2024) · BJC Reports · doi:10.1038/s44276-023-00025-7 · Cited by 3
Same storm, different boats: can the UK recapture improving life expectancy trends?
Hiam, L., & Patel, P. (2021) · Journal of the Royal Society of Medicine · doi:10.1177/01410768211033895 · Cited by 3
“2 years for women and men, respectively, when compared to 2019.(2) These falls are, however, part of a longer-term trend that began long before the COVID-19 pandemic.”
ResultCiências Socialmente Aplicáveis: Integrando Saberes e Abrindo Caminhos VII
Rodrigues, J., & Marques, M. A. (2022) · Editora Artemis eBooks · doi:10.37572/edart_171222729 · Cited by 4
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
- ORCID
- 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
- PMC
- PMC7818788
- OpenAlex
- W3125353637
- Semantic Scholar
- d98ee91f8f166d87e8bdf8e20b864f13b4b11d74
- 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
- hybrid
- doi.org
- 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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