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

BackgroundDeaths 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.MethodsWe 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.ResultsThere 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.ConclusionQuantifying 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.

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

10.1101/2020.07.16.20155077 ◽

2020 ◽

Cited By ~ 1

Author(s):

José Manuel Aburto ◽

Ridhi Kashyap ◽

Jonas Schöley ◽

Colin Angus ◽

John Ermisch ◽

...

Keyword(s):

Life Expectancy ◽

Population Health ◽

Mortality Risk ◽

Excess Mortality ◽

England And Wales ◽

National Statistics ◽

Life Expectancy At Birth ◽

The Impact ◽

Age And Sex ◽

Excess Deaths

AbstractBackgroundDeaths 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, when the first COVID-19 death was registered, to week 47 ending November 20, 2020 in England and Wales through an analysis of excess mortality.MethodsWe 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 standard deviation in age at death.ResultsThere 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 females and males relative to the 2019 levels, respectively. Lifespan inequality also fell over the same period by five months for both sexes.ConclusionQuantifying excess deaths and their impact on life expectancy at birth provides 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.Summary boxesWhat is already known on this topicCOVID-19 related deaths may be misclassified thereby inaccurately estimating the full impact of the pandemic on mortality. The pandemic may also have indirect effects on other causes due to changed behaviours, as well as the social and economic consequences resulting from its management. Excess mortality, the difference between observed deaths and what would have been expected in the absence of the pandemic, is a useful metric to quantify the overall impact of the pandemic on mortality and population health. Life expectancy at birth and lifespan inequality assess the cumulative impact of the pandemic on population health.What this study addsWe examine death registration data from the Office for National Statistics from 2010 to week 47 (ending on November 20) in 2020 to quantify the impact of the COVID-19 pandemic on mortality in England and Wales thus far. We estimate excess mortality risk by age and sex, and quantify the impact of excess mortality risk on excess deaths, life expectancy and lifespan inequality. During weeks 10 through 47 of 2020, elevated mortality rates resulted in 57,419 additional deaths compared with baseline mortality. Life expectancy at birth for females and males over the 47 weeks of 2020 was 82.6 and 78.7 years, with 0.9 and 1.2 years of life lost relative to the year 2019. Lifespan inequality, a measure of the spread or variation in ages at death, declined due to the increase of mortality at older ages.

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Impact of the COVID-19 pandemic on life expectancy in Madrid (Spain)

10.31219/osf.io/s53jx ◽

2020 ◽

Author(s):

Sergi Trias-Llimós ◽

Usama Bilal

Keyword(s):

Life Expectancy ◽

Surveillance System ◽

Excess Mortality ◽

Daily Mortality ◽

Life Expectancy At Birth ◽

The World ◽

Using Data ◽

The Impact ◽

Mortality Surveillance ◽

Annual Mortality

The COVID-19 pandemic is causing substantial increases in mortality across populations, potentially causing stagnation or decline in life expectancy. We explored this idea by examining the impact of excess mortality linked to the COVID-19 crisis on life expectancy in the region of Madrid (Spain). Using data from the Daily Mortality Surveillance System (MoMo), we calculated excess mortality (death counts) for the weeks 10th to 14th in 2020 using data on expected and observed mortality, assuming no further excess mortality during the rest of the year. The expected annual mortality variation was +6%, +21% and +25% among men aged under 65, between 65 and 74 and over 75, respectively, and +5%, +13%, and 18% for women, respectively. This excess mortality during weeks 10th to 14th resulted in a life expectancy at birth decline of 1.6 years among men and 1.1 years among women. These estimates confirm that Madrid and other severely hit regions in the world may face substantial life expectancy declines.

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Impact of the COVID-19 pandemic on life expectancy in Madrid (Spain)

10.31235/osf.io/4w9bx ◽

2020 ◽

Cited By ~ 1

Author(s):

Sergi Trias-Llimós ◽

Usama Bilal

Keyword(s):

Life Expectancy ◽

Surveillance System ◽

Excess Mortality ◽

Daily Mortality ◽

Life Expectancy At Birth ◽

The World ◽

Using Data ◽

The Impact ◽

Mortality Surveillance ◽

Annual Mortality

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Human costs of the first wave of the COVID-19 pandemic in the major epicentres in Italy

10.1553/populationyearbook2022.res2.1 ◽

2021 ◽

Author(s):

Simone Ghislandi ◽

Raya Muttarak ◽

Markus Sauerberg ◽

Benedetta Scotti

Keyword(s):

Life Expectancy ◽

Excess Mortality ◽

National Level ◽

Death Registration ◽

Substantial Impact ◽

Registration Data ◽

Life Expectancy At Birth ◽

Human Costs ◽

The Impact ◽

Excess Deaths

Deaths from COVID-19 can be miscounted due to under-reporting and inaccurate death registration. Mortality is often reported at the national level, which can result in the underestimation of the true scale of the impact of the pandemic since outbreaks tend to be localised. This study exploits all-cause daily death registration data provided by the Italian Statistical Office (ISTAT) from 1 January to 31 October to estimate the excess mortality and the corresponding changes in life expectancy during the first wave of the COVID-19 pandemic. Focusing on the five most severely hit provinces in Italy (Bergamo, Brescia, Cremona, Lodi and Piacenza), we calculate the excess mortality in 2020 compared to the average mortality of the years 2015 to 2019. Moreover, we estimate the excess mortality in the first quadrimester of 2020, and the annual life expectancy at birth. The estimated excess deaths show that during this period, mortality was significantly higher than the official mortality statistics for COVID-19. According to our estimates for the first quadrimester, life expectancy in the five provinces declined by 5.4 to 8.1 for men and by 4.1 to 5.8 years for women. In addition, we find that annual life expectancy decreased by 2.4 to 4.1 years for men and by 1.9 to 2.8 years for women compared to the 2015–2019 average. Thus, we conclude that the first wave of the COVID-19 pandemic had a substantial impact on population health in the hardest hit areas in Italy.

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The decomposition of life expectancy for age and cause of death in Tuscany, Italy

European Journal of Public Health ◽

10.1093/eurpub/ckz185.638 ◽

2019 ◽

Vol 29 (Supplement_4) ◽

Author(s):

N Nante ◽

L Kundisova ◽

F Gori ◽

A Martini ◽

F Battisti ◽

...

Keyword(s):

Life Expectancy ◽

Causes Of Death ◽

National Level ◽

Age Groups ◽

Resistant Bacteria ◽

Mortality Data ◽

Life Expectancy At Birth ◽

Icd 10 ◽

Reduction Of Mortality ◽

The Impact

Abstract Introduction Changing of life expectancy at birth (LE) over time reflects variations of mortality rates of a certain population. Italy is amongst the countries with the highest LE, Tuscany ranks fifth at the national level. The aim of the present work was to evaluate the impact of various causes of death in different age groups on the change in LE in the Tuscany region (Italy) during period 1987-2015. Material and methods Mortality data relative to residents that died during the period between 1987/1989 and 2013/2015 were provided by the Tuscan Regional Mortality Registry. The causes of death taken into consideration were cardiovascular (CVS), respiratory (RESP) and infective (INF) diseases and cancer (TUM). The decomposition of LE gain was realized with software Epidat, using the Pollard’s method. Results The overall LE gain during the period between two three-years periods was 6.7 years for males, with a major gain between 65-89, and 4.5 years for females, mainly improved between 75-89, <1 year for both sexes. The major gain (2.6 years) was attributable to the reduction of mortality for CVS, followed by TUM (1.76 in males and 0.83 in females) and RESP (0.4 in males; 0.1 in females). The major loss of years of LE was attributable to INF (-0.15 in females; -0.07 in males) and lung cancer in females (-0.13), for which the opposite result was observed for males (gain of 0.62 years of LE). Conclusions During the study period (1987-2015) the gain in LE was major for males. To the reduction of mortality for CVS have contributed to the tempestuous treatment of acute CVS events and secondary CVS prevention. For TUM the result is attributable to the adherence of population to oncologic screening programmes. The excess of mortality for INF that lead to the loss of LE can be attributed to the passage from ICD-9 to ICD-10 in 2003 (higher sensibility of ICD-10) and to the diffusion of multi-drug resistant bacteria, which lead to elevated mortality in these years. Key messages The gain in LE during the period the 1987-2015 was higher in males. The major contribution to gain in LE was due to a reduction of mortality for CVS diseases.

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Excess mortality in Guadeloupe and Martinique, islands of the French West Indies, during the chikungunya epidemic of 2014

Epidemiology and Infection ◽

10.1017/s0950268818002315 ◽

2018 ◽

Vol 146 (16) ◽

pp. 2059-2065 ◽

Cited By ~ 10

Author(s):

A. R. R. Freitas ◽

P. M. Alarcón-Elbal ◽

M. R. Donalisio

Keyword(s):

Strong Correlation ◽

Excess Mortality ◽

Pearson Correlation ◽

Age Groups ◽

Epidemiological Data ◽

Mortality Data ◽

Surveillance Systems ◽

Mortality And Morbidity ◽

The Impact ◽

Excess Deaths

AbstractIn some chikungunya epidemics, deaths are not completely captured by traditional surveillance systems, which record case and death reports. We evaluated excess deaths associated with the 2014 chikungunya virus (CHIKV) epidemic in Guadeloupe and Martinique, Antilles. Population (784 097 inhabitants) and mortality data, estimated by sex and age, were accessed from the Institut National de la Statistique et des Études Économiques in France. Epidemiological data, cases, hospitalisations and deaths on CHIKV were obtained from the official epidemiological reports of the Cellule de Institut de Veille Sanitaire in France. Excess deaths were calculated as the difference between the expected and observed deaths for all age groups for each month in 2014 and 2015, considering the upper limit of 99% confidence interval. The Pearson correlation coefficient showed a strong correlation between monthly excess deaths and reported cases of chikungunya (R= 0.81,p< 0.005) and with a 1-month lag (R= 0.87,p< 0.001); and a strong correlation was also observed between monthly rates of hospitalisation for CHIKV and excess deaths with a delay of 1 month (R= 0.87,p< 0.0005). The peak of the epidemic occurred in the month with the highest mortality, returning to normal soon after the end of the CHIKV epidemic. There were excess deaths in almost all age groups, and excess mortality rate was higher among the elderly but was similar between male and female individuals. The overall mortality estimated in the current study (639 deaths) was about four times greater than that obtained through death declarations (160 deaths). Although the aetiological diagnosis of all deaths associated with CHIKV infection is not always possible, already well-known statistical tools can contribute to the evaluation of the impact of CHIKV on mortality and morbidity in the different age groups.

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Excess Mortality Associated With COVID-19 by Demographic Group: Evidence From Florida and Ohio

Public Health Reports ◽

10.1177/00333549211041550 ◽

2021 ◽

pp. 003335492110415

Author(s):

Troy Quast ◽

Ross Andel

Keyword(s):

Excess Mortality ◽

Prediction Interval ◽

National Level ◽

Age Groups ◽

Black Population ◽

Infection Rates ◽

Black Adults ◽

Demographic Groups ◽

Younger Age ◽

Excess Deaths

Objective COVID-19 mortality varies across demographic groups at the national level, but little is known about potential differences in COVID-19 mortality across states. The objective of this study was to estimate the number of all-cause excess deaths associated with COVID-19 in Florida and Ohio overall and by sex, age, and race. Methods We calculated the number of weekly and cumulative excess deaths among adults aged ≥20 from March 15 through December 5, 2020, in Florida and Ohio as the observed number of deaths less the expected number of deaths, adjusted for population, secular trends, and seasonality. We based our estimates on death certificate data from the previous 10 years. Results The results were based on ratios of observed-to-expected deaths. The ratios were 1.17 (95% prediction interval, 1.14-1.21) in Florida and 1.15 (95% prediction interval, 1.11-1.19) in Ohio. Although the largest number of excess deaths occurred in the oldest age groups, in both states the ratios of observed-to-expected deaths were highest among adults aged 20-49 (1.21; 95% prediction interval, 1.11-1.32). The ratio of observed-to-expected deaths for the Black population was especially elevated in Florida. Conclusions Although excess deaths were largely concentrated among older cohorts, the high ratios of observed-to-expected deaths among younger age groups indicate widespread effects of COVID-19. The high levels of observed-to-expected deaths among Black adults may reflect in part disparities in infection rates, preexisting conditions, and access to care. The finding of high excess deaths among Black adults deserves further attention.

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Increasing Longevity and the New Demography of Death

International Journal of Population Research ◽

10.1155/2014/521523 ◽

2014 ◽

Vol 2014 ◽

pp. 1-7 ◽

Cited By ~ 11

Author(s):

George W. Leeson

Keyword(s):

20Th Century ◽

21St Century ◽

Population Level ◽

Sub Saharan Africa ◽

Global Level ◽

England And Wales ◽

Individual Level ◽

Life Expectancy At Birth ◽

Sub Saharan ◽

Using Data

The world is ageing at both an individual and population levels and population ageing is truly a global phenomenon, the only notable region of exception being sub-Saharan Africa, which remains relatively young in demographic terms. At an individual level, life expectancies at birth have increased at the global level from 47 years in the mid-20th century to around 70 years today and are expected to rise to 76 years by the mid-21st century. At the population level, the proportion of the world’s population aged 60 years and over has increased from 8 percent in the mid-20th century to 12 percent, and by 2050, it is expected to reach 21 percent. In Europe, ageing has continued at a slower rate, but with the emergence of increasing numbers of centenarians. This paper outlines the transition using data from England and Wales from a demography of young death in the mid-19th century to a demography of survival in the 20th century and on to the new demography of old death in the 21st century. The paper provides evidence that it is likely that ages at death will continue to increase, with more and more people reaching extreme old age. At the same time, it is likely that life expectancies at birth will continue to rise, taking life expectancy at birth in England and Wales to 100 years or more by the end of the 21st century. The new 21st century demography of death will lead to annual numbers of deaths far in excess of previous maxima.

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Impact of COVID-19 infection on life expectancy, premature mortality, and DALY in Maharashtra, India

BMC Infectious Diseases ◽

10.1186/s12879-021-06026-6 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Guru Vasishtha ◽

Sanjay K. Mohanty ◽

Udaya S. Mishra ◽

Manisha Dubey ◽

Umakanta Sahoo

Keyword(s):

Life Expectancy ◽

Premature Mortality ◽

The State ◽

Multiple Sources ◽

Life Expectancy At Birth ◽

Disability Adjusted Life ◽

Life Years ◽

Working Age ◽

Using Data ◽

The Impact

Abstract Background The COVID-19 infections and deaths have largely been uneven within and between countries. With 17% of the world’s population, India has so far had 13% of global COVID-19 infections and 8.5% of deaths. Maharashtra accounting for 9% of India’s population, is the worst affected state, with 19% of infections and 33% of total deaths in the country until 23rd December 2020. Though a number of studies have examined the vulnerability to and spread of COVID-19 and its effect on mortality, no attempt has been made to understand its impact on mortality in the states of India. Method Using data from multiple sources and under the assumption that COVID-19 deaths are additional deaths in the population, this paper examined the impact of the disease on premature mortality, loss of life expectancy, years of potential life lost (YPLL), and disability-adjusted life years (DALY) in Maharashtra. Descriptive statistics, a set of abridged life tables, YPLL, and DALY were used in the analysis. Estimates of mortality indices were compared pre- and during COVID-19. Result COVID-19 attributable deaths account for 5.3% of total deaths in the state and have reduced the life expectancy at birth by 0.8 years, from 73.2 years in the pre-COVID-19 period to 72.4 years by the end of 2020. If COVID-19 attributable deaths increase to 10% of total deaths, life expectancy at birth will likely reduce by 1.4 years. The probability of death in 20–64 years of age (the prime working-age group) has increased from 0.15 to 0.16 due to COVID-19. There has been 1.06 million additional loss of years (YPLL) in the state, and DALY due to COVID-19 has been estimated to be 6 per thousand. Conclusion COVID-19 has increased premature mortality, YPLL, and DALY and has reduced life expectancy at every age in Maharashtra.

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Inaction on climate change projected to reduce European life expectancy

10.31235/osf.io/ngtxr ◽

2017 ◽

Author(s):

Mathew Hauer ◽

Alexis R Santos-Lozada

Keyword(s):

Climate Change ◽

Life Expectancy ◽

Excess Mortality ◽

Climate Extremes ◽

European Countries ◽

Life Expectancy At Birth ◽

Project Climate Change ◽

The Cost ◽

The Impact ◽

Mortality Estimates

Climate change-related excess mortality estimates clearly demonstrate a dramatic impact on public health and human mortality. However, life expectancy at birth is more easily communicated and understood by the public. By properly situating climate change mortality within the contexts of life expectancy, we better represent the cost of climate change on longevity. In this paper, we convert excess mortality estimates due to increases in extreme weather from climate change into potential reductions in life expectancy at birth in thirty-one European countries. We project climate change extremes to reduce life expectancy at birth by 0.24 years for the average European country with differences in excess of 1.0 years in some countries by the end of the century. We only estimate the impact of mortality directly related to climate extremes, making our estimates conservative. Thus, the cost of inaction on climate change could approach, and likely to exceed, one year of life in some European countries.

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