Excess deaths and life-years lost due to the Covid-19 pandemic in Denmark – what did we learn?

Knowledge overview

February 2024


Externally reviewed

In a project funded by the ROCKWOOL Foundation, researchers from the Interdisciplinary Centre on Population Dynamics (CPop) at the University of Southern Denmark (SDU) investigated the burden of the COVID-19 pandemic on mortality, both globally and in the Danish context, starting from its spread in early 2020 throughout the end of 2021.

The project answered four main research questions:


a. How to best measure the burden of the COVID-19 pandemic on mortality?

b. How different was the impact of COVID-19 on mortality levels across countries?

c. Which subpopulations have been most affected?

d. What was the association between policy interventions and mortality outcomes?

Main learnings

Was the pandemic effect on life-lost serious?
Yes, it was exceptional. Most European countries saw in the pandemic years the worst life expectancy losses since the end of the Second World War.

What made the difference in saving lives during the COVID-19 pandemic?
In the first pandemic year 2020, the countries with measured, timely and well-enforced lockdowns had the lowest excess death. In 2021, vaccines were available and countries that applied vaccines fast and wide saw lower losses.

Who was mostly affected?
In general, the excess death was highest for older persons, for males, inhabitants of large urban agglomer-ations, and in particular persons from already disadvan-taged segments of society.

And what about Denmark?
Denmark with its timely and well-enforced lockdowns, wide vaccination, and overall high level of population compliance experienced the lowest levels of excess death during the two pandemic years. Also, especially in 2020, Denmark successfully protected institutionalized populations in nursing homes.

Excess death and life expectancy as the preferred measures of the impact of the pandemic

Measuring the burden of the COVID-19 pandemic on mortality proved to be challenging. COVID-19 reported deaths revealed only a partial picture. This was due to the insufficiency of testing capacity, especially at the beginning of the pandemic, and the misclassification and inconsistencies in reporting COVID-19 deaths across time and countries. Researchers from CPop at SDU envisioned to assess the impact of the pandemic more comprehensively by means of two metrics: Excess death and life expectancy.

Excess death represents the difference between the observed number of deaths during the pandemic and the estimated number of deaths that would have had occurred in the absence of the pandemic. This meas-ure of mortality thus reflects a plethora of impacts caused both directly and indirectly by COVID-19 (e.g. changes in behaviour). Thus, it is a summary measure of the ‘total effect’ on the number of deaths. Excess mortality can be standardized for age or population size to aid comparability between countries.

Life expectancy at birth, as a widely used metric of population health and longevity, was used as a snap-shot of current mortality conditions. Life expectancy refers to the average age to which a newborn would have lived if current death rates continued for his whole life. It does not predict an actual lifespan of that newborn. It allows for a comparison of the size of the mortality impacts of the pandemic between different countries and populations.

Low number of losses during the COVID-19 pandemic in Denmark, but high elsewhere

Researchers from CPop analyzed the excess death during the first COVID-19 wave in England and Wales (Aburto et al., 2019 JECH) and Denmark and Sweden (Rizzi and Vaupel, 2019 PNAS). Sweden reported the highest excess death risk with a 20% increase in deaths compared to the expected levels; in England and Wales, elevated mortality rates resulted in 15% increase in deaths compared with the expected level. In comparison, negligible excess death risk was reported for Denmark. The urge to provide systematic evidence of the impacts of the pandemic on population health in a cross-national perspective, led CPop researchers to analyzing a high-quality data set of harmonized all-cause mortality records for 29 countries, representing most of Europe, Chile, and the USA (Aburto et al., 2022 IJE).

They looked at life expectancy for men and women and compared its pre-pandemic level in 2019 with the level in the first pandemic year 2020. They found large life expectancy losses in most of those 29 countries, but not in Denmark. For western European countries such as Spain, England and Wales, Italy, or Belgium, the last time such large magnitudes of life expectancy declines were observed was during the Second World War. 22 countries included in the study experienced losses of life expectancy larger than half a year. Males saw larger life expectancy declines than females: females in 8 countries and males in 11 countries experienced losses larger than a year. Putting these losses in perspective: On average it takes almost 6 years to achieve a one-year increase in life expectancy in these countries. See progress wiped out over the course of 2020 by COVID-19 in figure 1.


Note: Explanatory note to the graph: The biggest declines in life expectancy were among males in the US, with a decline of 2.2 years relative to 2019 levels, followed by Lithuanian males with 1.7 years loss.
Source: Schöley, J., Aburto, J.M., Kashnitsky, I. et al., 2022.

Denmark and Norway were the only two countries out the 29 under study, that recorded increase in life expectancy for both males and females in 2020 (Figure 2). This does not mean that lives were not lost due to COVID-19 there. But the losses were relatively low and the increase in mortality due to COVID-19 was offset by mortality reductions among other causes (e.g., because of lower infection rates from other diseases). Danes were gaining a little more than two months of life expectancy yearly before the pandemic. In the first pandemic year 2020 the gain stayed positive although at somewhat lower level, 1.1 months.

The above-mentioned studies bring evidence that the countries with measured, timely and well-enforced lock-downs had the lowest excess death and life expectancy losses in the first pandemic year 2020. Denmark was one of them.


Note: Countries are sorted from largest to smallest losses. The sum of both components adds to the total change from 2019 to 2020 in each country.
Source: Aburto et al. (2021).

A follow-up study covering the impact of the pandemic on life expectancy in 2021 saw more diverse impacts across countries (Schöley, et.al. 2022 Nat Hum Behav). Denmark again fared well in this comparison (Figure 3). In 2021, vaccines were available and countries that applied a vaccine fast and wide saw lower life-losses.Some countries experienced life expectancy bounce-backs from previous losses (among them most significantly Switzerland, Sweden, Spain, and Belgium). In more countries however, the life expectancy storm continued and even intensified. This was the case of Central and Eastern European countries. Also, USA with the worst life expectancy decline in the first year of pandemic did not rebound in 2021.

How to read the figure: On the example of the USA: Table part on the right hand side: Average increase in life expectan-cy for the years 2016-2019 in USA was +2.0 months (grey dot and the number in last column). Change in life expectancy between 2019 and 2021 (column 19/21) was -28.2 months. Graph part: The arm of the arrow represents the total life expectancy change between 2019 and 2021. The total change (19/21) is -28.2 months.

Source: Schöley, J., Aburto, J.M., Kashnitsky, I. et al. , 2022.

COVID-19 unequally affected different population groups

CPop researchers did not only analyze excess death and life expectancy at the national level. They zoomed in and stratified the population by regions and demographic characteristics to understand which subpopulations had been mostly affected, focusing on regional level, urban vs rural areas, age, sex, race, living arrangements, frailty, and socioeconomic status.

Estimation of excess death and life expectancy at the regional level showed that geographical spatial disparities in mortality occurred during the pandemic. An unequal impact of the first wave was found across French and Spanish regions (Ainhoa and Rizzi, 2020 Popul) with high density areas suffering the most. Comunidad de Madrid in Spain and Île-de-France in France, regions including the capital cities, recorded the highest excess death risk above age 70 (around 50% and 20% respectively). In a later paper, Kashnitsky et al. (Kashnitsky et al. 2023 study report) explored the differences in the mortality dynamics between urban and rural areas of 20 European countries during the two pandemic years 2020 and 2021. Authors found pronounced and significant differences, with urban areas being harder hit by COVID-19 mortality in most countries. Evidence pointed to the necessity of protecting densely populated areas during the spread of highly communicable diseases.

Regarding demographic characteristics, while the highest excess mortality was generally found at older ages across countries, gender differences in excess death risk existed, but with a nuanced and non-consistent picture. In an analysis of the first COVID-19 wave in Italy, for ex-ample, authors found excess death risk to be 25.0% both for men and women, mostly over age 70. Men generally had more excess deaths compared to women, but the only statistically significant difference between the two sexes occurred for the age categories 60–69 and 70–79 (Rizzi et al, Genus).

Losses varied greatly also by race/ethnicity. In a study Aburto et al. (Aburto et al. 2022 PNAS) found that in the United States in 2020, Hispanic and Black Americans suffered a much larger decline in life expectancy compared to White population, highlighting the importance of social determinants in health during mortality crises. In particular, life expectancy dropped for Hispanic and Black males 4.5 and 3.6 years, respectively, compared to a 1.5 years drop in White males. These drops nearly eliminated the previous life-expectancy advantage for the Hispanic compared to the White population and dramatically increased the already large gap in life expectancy between Black and White Americans. Analyzing the specific causes of death that contributed to the losses in life expectancy, authors found that life expectancy losses for the Hispanic population were largely attributable to official COVID-19 deaths, while Black Americans saw increases in cardiovascular diseases and “deaths of despair”.

Even in an egalitarian country like Denmark, that did not experience mortality declines in 2020 and only a slight decline in 2021, researchers observed a mortality gradi-ent across socioeconomic status (SES) groups (Strozza et al., 2024 Popul. Health Metr.). In 2020, both women and men with higher SES recorded a larger increase in life expectancy compared to those of lower SES. In 2021, men with higher SES did not experience any life expectancy drop, while those with lower SES registered a decrease in life expectancy. In the same year, women with higher SES experienced negligible losses in life expectancy compared to women with lower SES. The pandemic years, disproportionally affected people of lower SES, exacerbating social inequalities in health also in Denmark.


Source: Strozza et al., 2024.

In Denmark, life expectancy losses differed also by living arrangements. Authors showed that small non-traditional households were hit the hardest (Vigezzi et al. 2023 study report) and could prove that, especially in 2020, Denmark successfully protected institutionalized populations in nursing homes.

Timely policy interventions matter on mortality outcomes

Given the demographic analysis of the impact of the COVID-19 pandemic on mortality, researchers contributed further to the unresolved debate on the effectiveness of non-pharmaceutical interventions (NPIs) in fighting the pandemic. They analyzed two interesting cases to estimate the lockdown policy effectiveness.

First, Ege et al. (2023 Sci Rep) used the rare case of Sweden to estimate the causal impact of not implementing a lockdown on excess death outcomes from the end of February 2020 throughout the end of September 2020. Using state-of-the-art synthetic cohort methods, researchers constructed a counterfactual version of Sweden, a synthetic control, to estimate what would have happened to actual Sweden, the treated unit, had it imposed a mandatory lockdown (Figure 5). Authors found that by the end of September 2020 approximately 10% of all deaths in Sweden could have been avoided, had Sweden implemented a mandatory lockdown.

Source: Ege et al., 2023.

Second, Ege et al. (2023 study report) studied the short, yet stringent, lockdown implemented in 7 Danish municipalities in late 2020, when a mutated SARS-CoV-2 virus variant showed spillover infections between the mink population and humans. This case represents a unique opportunity to estimate the causal effect of a timely lock-down policy on infection rates. Infections, rather than excess deaths, were used here as outcome of interest given the small population size (hence, too small number of deaths). High testing rates consistent across all Danish municipalities lend credibility to the outcome measure. While the rest of Denmark remained with few restrictions in late 2020, 7 municipalities in Northern Jutland were targeted, not because of high infection numbers, but as a part of the overall response to the widespread circulation of mink-derived variants of SARS-CoV-2 in the human population in Northern Jutland. Applying a state-of-the-art synthetic cohort approach, it became evident that timely, short-lived, stringent measures were able to abruptly halt additional infections, indicating a substantial and significant reduction in daily infections when compared to the respective synthetic counterfactual municipality (Figure 6 reports the case of Hjørring).

Finding showed consistent reductions of daily infection numbers ranging between 19% to 43% in the target municipalities. Researchers could conclude that a strict and short lockdown policy controlled the spread of the virus.

Source: Ege et al., 2023 (study report).

Publications behind the study:

1. Quantifying life expectancy losses globally

1. Aburto, JM, et al. 2022. “Significant Impacts of the COVID-19 Pandemic on Race/Ethnic Differences in USA Mortality.” Proceedings of the National Academy of Sciences (PNAS). Access here.

2. Aburto, José Manuel. 2021a. “The Need for All-Cause Mortality Data to Aid Our Understanding of the COVID-19 Pandemic in Latin America.” American Journal of Public Health. Access here.

3. Aburto, JM, et al. 2021. “Estimating the Burden of the COVID-19 Pandemic on Mortality, Life Expectancy and Lifespan Inequality
in England and Wales: A Population-Level Analysis.” Journal of Epidemiology and Community Health. Access here.

4. Aburto, JM, et al. 2022. “Life Expectancy Declines in Russia during the COVID-19 Pandemic in 2020.” International Journal of Epidemiology. Access here.

5. Aburto, JM., et al. 2021. “Quantifying Impacts of the COVID-19 Pandemic through Life-Expectancy Losses: A Population-Level Study of 29 Countries.” International Journal of Epidemiology. Access here.

6. Levin, A. et al. 2022. “Assessing the Burden of COVID-19 in Developing Countries: Systematic Review, Meta-Analysis, and Public Policy Implications.” BMJ Global Health. Access here.

7. Mena, G. and Aburto, JM. 2022. “Unequal Impact of the COVID-19 Pandemic in 2020 on Life Expectancy across Urban Areas in Chile: A Cross-Sectional Demographic Study.” BMJ Open. Access here.

8. Schöley, et.al. 2022. “Life Expectancy Changes since COVID-19.” Nature Human Behaviour. Access here.


2. Estimation of seasonal mortality

9. Leger, A. and S. Rizzi. 2022. “Estimating Excess Mortality in French and Spanish Regions during the First COVID-19 Wave with the Later/Earlier Method” Population. Access here.

10. Rizzi, S. et al. 2022. “High Excess Deaths in Sweden during the First Wave of COVID-19: Policy Deficiencies or ‘Dry Tinder’?” Scandinavian Journal of Public Health. Access here.

11. Rizzi, S, and J W. Vaupel. 2021. “Short-Term Forecasts of Expected Deaths.” Proceedings of the National Academy of Sciences. Access here.

12. Schöley, J. 2021. “MOCY Database on ‘Timeseries of Weekly Death Counts and Co-Variates by Country, Sex and Age. Database available at GitHub here.

13. Léger, A, and Rizzi S. 2023. “Month-to-Month All-Cause Mortality Forecasting: A Method to Rapidly Detect Changes in Seasonal Patterns.” Accepted American Journal of Epidemiology.

14. Missov, T. I. n.d. “Estimates of Life Years Lost and Harvesting.” – DRAFT

3. Individual and spatial characteristics

15. Rizzi, S. et al. 2022. “Sex-Differences in Excess Death Risk during the COVID-19 Pandemic: An Analysis of the First Wave across Italian Regions. What Have We Learned?” Genus. Access here.

16. Kashnitsky, I., Trias-Llimós, S., & Villavicencio, F. (n.d.). “Life expectancy changes in urban and rural areas of European countries in the two pandemic years 2020-21 ” – DRAFT

17. Strozza, C., Vigezzi, S., Callaway, J., Aburto, J.M. n.d. “ The impact of COVID-19 on life expectancy across socioeconomic groups in Denmark” Population Health Metrics. Access here

18. Vigezzi, S., Strozza C., & Zarulli, V. n.d. “Changes in life expectancy by household type: the case of Denmark between 2019 and 2021” Under review in European Journal of Public Health

19. Kashnitsky, I., & Aburto, J. M. (2020). COVID-19 in unequally ageing European regions. World Development, 136, 105170. Access here.


4. Policy interventions and their relation to COVID19 mortality

20. Ege, F. n.d. “Effectiveness of the 2020 Mink-Lockdown of Selected Municipalities in Northern Jutland, Denmark.” – DRAFT

21. Ege, F., Giovanni M., and Seetha M. 2023. “The Unseen Toll: Excess Mortality during Covid-19 Lockdowns.” Scientific Reports 13 (1): 18745. Access here.

22. Ege, F. n.d. “Excess Mortality during the COVID-19 Pandemic: A Tragic Tale of a Concepts Rise to Fame.” – DRAFT


Not peer reviewed

23. Balbo, N., Kashnitsky, I., Melegaro, A., Meslé, F., Mills, M., De Valk, H., & Vono de Vilhena, D. (2020). Demography and the Coronavirus Pandemic (Population & Policy Compact 25). Max Planck Society/Population Europe. Policy Brief, not subjected to academic peer review. Access here.

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