The Mean Unfulfilled Lifespan (MUL): A new indicator of the impact of mortality shocks on the individual lifespan, with application to mortality reversals induced by COVID-19

Spatial Variation in Excess Mortality Across Europe: A Cross-Sectional Study of 561 Regions in 21 Countries

OBJECTIVE

To measure the burden of the COVID-19 pandemic in 2020 at the subnational level by estimating excess mortality, defined as the increase in all-cause mortality relative to an expected baseline mortality level.

METHODS

Statistical and demographic analyses of regional all-cause mortality data provided by the vital statistics systems of 21 European countries for 561 regions in Central and Western Europe. Life expectancy losses at ages 0 and 60 for males and females were estimated.

RESULTS

We found evidence of a loss in life expectancy in 391 regions, whilst only three regions exhibit notable gains in life expectancy in 2020. For 12 regions, losses of life expectancy amounted to more than 2 years and three regions showed losses greater than 3 years. We highlight geographical clusters of high mortality in Northern Italy, Spain and Poland, whilst clusters of low mortality were found in Western France, Germany/Denmark and Norway/Sweden.

CONCLUSIONS

Regional differences of loss of life expectancy are impressive, ranging from a loss of more than 4 years to a gain of 8 months. These findings provide a strong rationale for regional analysis, as national estimates hide significant regional disparities.

Evaluating Spatial, Cause-Specific and Seasonal Effects of Excess Mortality Associated with the COVID-19 Pandemic: The Case of Germany, 2020

BACKGROUND

Evaluating mortality effects of the COVID-19 pandemic using all-cause mortality data for national populations is inevitably associated with the risk of masking important subnational differentials and hampering targeted health policies. This study aims at assessing simultaneously cause-specific, spatial and seasonal mortality effects attributable to the pandemic in Germany in 2020.

METHODS

Our analyses rely on official cause-of-death statistics consisting of 5.65 million individual death records reported for the German population during 2015-2020. We conduct differential mortality analyses by age, sex, cause, month and district (N = 400), using decomposition and standardisation methods, comparing each strata of the mortality level observed in 2020 with its expected value, as well as spatial regression to explore the association of excess mortality with pre-pandemic indicators.

RESULTS

The spatial analyses of excess mortality reveal a very heterogenous pattern, even within federal states. The coastal areas in the north were least affected, while the south of eastern Germany experienced the highest levels. Excess mortality in the most affected districts, with standardised mortality ratios reaching up to 20%, is driven widely by older ages and deaths reported in December, particularly from COVID-19 but also from cardiovascular and mental/nervous diseases.

CONCLUSIONS

Our results suggest that increased psychosocial stress influenced the outcome of excess mortality in the most affected areas during the second lockdown, thus hinting at possible adverse effects of strict policy measures. It is essential to accelerate the collection of detailed mortality data to provide policymakers earlier with relevant information in times of crisis.

Interpreting changes in life expectancy during temporary mortality shocks

BACKGROUND

Life expectancy is a pure measure of the mortality conditions faced by a population, unaffected by that population's age structure. The numerical value of life expectancy also has an intuitive interpretation, conditional on some assumptions, as the expected age at death of an average newborn. This intuitive interpretation gives life expectancy a broad appeal. Changes in life expectancy are also routinely used to assess mortality trends. Interpreting these changes is not straightforward as the assumptions underpinning the intuitive interpretation of life expectancy are no longer valid. This is particularly problematic during mortality 'shocks,' such as during wars or pandemics, when mortality changes may be sudden, temporary, and contrary to secular trends.

OBJECTIVE

This study aims to provide an alternative perspective on what changes in life expectancy measure that remains applicable during mortality shocks.

CONCLUSIONS

Returning to two different models that the period life table may represent, I show that a difference in life expectancy is typically interpreted from the synthetic cohort model as the difference in mean longevity between different birth cohorts. However, it can also be interpreted from the stationary population model as a measure of premature mortality in a death cohort. The latter, less common interpretation makes more sense for temporary declines in life expectancy induced by mortality shocks. The absolute change in life expectancy is then an age-standardized value of the average lifespan reduction for people dying during the mortality shock.

CONTRIBUTION

To clarify what a decline in life expectancy measures during mortality shocks is important, especially as demographers often assess the mortality impact of those shocks using this metric, which gets widely reported beyond demographers' inner circle.

Global and National Declines in Life Expectancy: An End-of-2021 Assessment

Timely, high-quality mortality data have allowed for assessments of the impact of the novel coronavirus disease 2019 (COVID-19) on life expectancies in upper-middle- and high-income countries. Extant data, though imperfect, suggest that the bulk of the pandemic-induced mortality might have occurred elsewhere. This article reports on changes in life expectancies around the world as far as they can be estimated from the evidence available at the end of 2021. The global life expectancy appears to have declined by 0.92 years between 2019 and 2020 and by another 0.72 years between 2020 and 2021, but the decline seems to have ended during the last quarter of 2021. Uncertainty about its exact size aside, this represents the first decline in global life expectancy since 1950, the first year for which a global estimate is available from the United Nations. Annual declines in life expectancy (from a 12-month period to the next) appear to have exceeded two years at some point before the end of 2021 in at least 50 countries. Since 1950, annual declines of that magnitude had only been observed on rare occasions, such as Cambodia in the 1970s, Rwanda in the 1990s, and possibly some sub-Saharan African nations at the peak of the acquired immunodeficiency syndrome (AIDS) pandemic.

Investigating regional excess mortality during 2020 COVID-19 pandemic in selected Latin American countries

In this paper, we measure the effect of the 2020 COVID-19 pandemic wave at the national and subnational levels in selected Latin American countries that were most affected: Brazil, Chile, Ecuador, Guatemala, Mexico, and Peru. We used publicly available monthly mortality data to measure the impacts of the pandemic using excess mortality for each country and its regions. We compare the mortality, at national and regional levels, in 2020 to the mortality levels of recent trends and provide estimates of the impact of mortality on life expectancy at birth. Our findings indicate that from April 2020 on, mortality exceeded its usual monthly levels in multiple areas of each country. In Mexico and Peru, excess mortality was spreading through many areas by the end of the second half of 2020. To a lesser extent, we observed a similar pattern in Brazil, Chile, and Ecuador. We also found that as the pandemic progressed, excess mortality became more visible in areas with poorer socioeconomic and sanitary conditions. This excess mortality has reduced life expectancy across these countries by 2-10 years. Despite the lack of reliable information on COVID-19 mortality, excess mortality is a useful indicator for measuring the effects of the coronavirus pandemic, especially in the context of Latin American countries, where there is still a lack of good information on causes of death in their vital registration systems.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1186/s41118-021-00139-1.