TOP 10 Countries with Highest Excess Mortality in 2020–2024
Excess mortality measures how many more people died than would have been expected if pre-pandemic mortality trends had continued. It is more informative than official COVID-19 death counts alone because it captures both direct fatalities and indirect losses linked to overwhelmed hospitals, delayed diagnosis, missed treatment, labour-market stress, and other knock-on effects that persisted through the pandemic era.
The most defensible international comparison is a 2020–2023 cumulative ranking. That is the latest period for which broadly comparable public excess-mortality estimates remain available across a wide range of countries. Extending the headline to 2024 would make the comparison look more complete than the public ranking datasets currently support.
What stands out at the top of the ranking
The upper end of the distribution is not random. The heaviest cumulative excess-mortality burden is concentrated in Eastern Europe, the Western Balkans, and the broader post-socialist space, with Peru standing out as the major Latin American outlier. That pattern points to structural vulnerability rather than to a single isolated factor: older age structures, high prevalence of cardiovascular and metabolic disease, weaker baseline health-system capacity, uneven vaccination uptake, and lower institutional resilience during repeated waves of stress.
- Regional concentration: the highest cumulative burden is overwhelmingly European, especially in the Balkans and eastern part of the continent.
- Peru remains exceptional: it still appears among the worst-affected countries per capita because the early pandemic shock was unusually severe and official COVID reporting initially understated the full mortality burden.
- This is a systems metric, not a virus-only metric: excess mortality reflects how well a country absorbed a multi-year public-health shock, not just how many deaths were formally certified as COVID.
Top 10 countries by cumulative excess deaths per 100,000 people
| Rank | Country | Excess deaths per 100,000 | Region |
|---|---|---|---|
| 1 | Serbia | 1,015.9 | Western Balkans |
| 2 | Lithuania | 942.9 | Baltics / Eastern Europe |
| 3 | Bulgaria | 922.2 | Eastern Europe |
| 4 | Russia | 921.0 | Eastern Europe / Eurasia |
| 5 | North Macedonia | 803.2 | Western Balkans |
| 6 | Georgia | 685.2 | South Caucasus |
| 7 | Bosnia and Herzegovina | 683.3 | Western Balkans |
| 8 | Armenia | 671.9 | South Caucasus |
| 9 | Croatia | 597.9 | Southeast Europe |
| 10 | Peru* | 608.4 | Latin America |
* Peru’s public comparable series ends earlier than several European 2023-complete series, but it remains part of the hardest-hit group in cumulative excess deaths per capita. Figures are shown in excess deaths per 100,000 people over the latest comparable pandemic-era period available in the public ranking dataset.
Chart 1. Excess deaths per 100,000 in the top 10
The distribution is highly concentrated. Serbia stands clearly above 1,000 excess deaths per 100,000 people, while Lithuania, Bulgaria, and Russia form a second tightly packed tier just below that threshold. After North Macedonia, the ranking steps down into another still very elevated group that includes Georgia, Bosnia and Herzegovina, Armenia, Croatia, and Peru.
- Serbia — 1,015.9
- Lithuania — 942.9
- Bulgaria — 922.2
- Russia — 921.0
- North Macedonia — 803.2
- Georgia — 685.2
- Bosnia and Herzegovina — 683.3
- Armenia — 671.9
- Croatia — 597.9
- Peru — 608.4
Bars show cumulative excess deaths per 100,000 population. The fallback list remains visible in the markup so the ranking stays readable even without JavaScript.
Methodology
Excess mortality is calculated as observed all-cause deaths minus expected deaths. In the public World Mortality Dataset framework, the expected level is based on a linear extrapolation of the 2015–2019 trend, with separate yearly baselines used for 2020, 2021, 2022, and 2023. That makes the series useful for pandemic-era comparison, while also explaining why cross-country consistency weakens once the comparison is extended beyond the currently maintained ranking horizon.
The ranking is presented here as 2020–2023 because that is the latest period for which broadly comparable public excess-mortality estimates remain available across a wide international sample. Raw death series may continue beyond that point, but the public comparative ranking itself is not maintained in the same way for 2024 onward.
The source base is complementary rather than interchangeable. Karlinsky & Kobak provide the continuously updated public ranking file and leaderboard built from the World Mortality Dataset. Our World in Data explains how HMD and WMD inputs are processed and documents its own country-quality filters. WHO provides a broader modelled country dataset, but its published country release still covers January 2020 to December 2021, so it is most useful here for global context rather than for the latest ranking cutoff.
Several limitations matter. Countries differ in reporting frequency, completeness, revision cycles, age structure, baseline mortality trends, and the strength of death registration systems. Excess mortality also reflects more than COVID itself: heatwaves, healthcare disruption, postponed surgery, influenza rebound, war-related stress, and registration revisions can all affect the final number. For that reason, excess mortality is best read as a summary stress test of population health and system resilience, not as a simple scorecard of one policy choice or one calendar year.
What the ranking shows
The main lesson is that the largest cumulative losses were concentrated in countries that entered the pandemic with high underlying cardiovascular risk, aging populations, and less spare health-system capacity. That does not mean these countries faced one identical policy failure. It means that repeated infection waves, delayed care, and institutional strain interacted over several years and produced exceptionally heavy cumulative damage.
Serbia, Bulgaria, Lithuania, Russia, and North Macedonia sit so high not because of one catastrophic month, but because the mortality shock was repeated, broad-based, and difficult to absorb. In practical terms, that usually reflects some combination of fragile hospital capacity under stress, uneven vaccination, chronic-disease burden, weaker primary-care continuity, and lower ability to shield vulnerable groups over time.
Peru matters because it shows that the pattern was not exclusively European. The early pandemic shock there was so severe that even with an earlier series cutoff, the country still remains among the worst-hit cases per capita. That is a reminder that oxygen shortages, limited ICU access, informal labour exposure, and uneven state capacity can produce mortality outcomes just as severe as the structural vulnerabilities seen in Eastern Europe.
Excess mortality and official COVID deaths are not the same thing. In some countries the excess burden far exceeded formally certified COVID fatalities, which points to undercounting, indirect mortality, or both. That is why excess mortality remains one of the most useful cross-country metrics when certification rules, testing intensity, and reporting practices differ sharply.
What this means for readers
This ranking says something deeper than how severe COVID was in a given place. It also reveals how resilient a country’s health system, care pathways, and population health profile were under prolonged stress. That has real relevance for public policy, insurance risk, labour-market resilience, long-term demography, and migration analysis.
For readers comparing countries, excess mortality should not be treated as a personal safety score on its own. It works better as a structural context indicator. A very high cumulative burden can point to chronic-disease vulnerability, delayed-care problems, weaker continuity of treatment, and sharper health inequalities than official headline statistics alone might suggest.
For policy watchers and investors, the implications also extend beyond the emergency phase. Countries that suffered heavier cumulative losses may face weaker labour supply, higher disability and care burdens, stronger pension and hospital pressure, and more persistent trust damage in institutions. In that sense, excess mortality is partly a public-health measure and partly a capacity indicator.
FAQ
Why is excess mortality more useful than official COVID-19 deaths?
Because it captures the total mortality impact above the expected baseline, not just deaths formally certified as COVID. That includes undercounted direct deaths and indirect losses caused by overwhelmed hospitals, delayed treatment, missed screening, reduced access to care, and wider systemic disruption.
Why is the ranking presented as 2020–2023 rather than 2020–2024?
Because the latest broadly comparable public excess-mortality ranking is anchored to the end of 2023. Some raw mortality series continue beyond that point, but the public cross-country excess-mortality estimates used for ranking are not maintained in the same way for 2024 onward.
Does a high excess-mortality score mean a country had the worst policy?
Not automatically. Excess mortality is an outcome measure, not a full policy audit. It reflects pre-existing disease burden, age structure, hospital capacity, timing of infection waves, vaccination, social behaviour, death-registration quality, and indirect effects such as delayed care. Policy matters, but it is only one part of the story.
Why are so many Balkan and Eastern European countries near the top?
Several structural risk factors overlapped there: older populations, higher cardiovascular mortality, lower baseline health resilience, uneven vaccination uptake, and repeated system stress over multiple years. The result was a cumulative burden that stayed exceptionally high even after the first pandemic shocks had passed.
Why is Peru still in the top group even with an earlier data cutoff?
Peru’s early pandemic mortality shock was exceptionally severe. Even without a later 2023-complete endpoint in the public comparable ranking, its cumulative excess deaths per capita remained high enough to keep it among the hardest-hit countries.
Why do WHO, OWID, and the World Mortality Dataset sometimes show different numbers?
Because they rely on different combinations of raw inputs, baseline assumptions, imputation rules, and modelling choices. WHO also publishes a country model dataset that currently covers only 2020–2021, while WMD-based public rankings extend through 2023. The broad pattern is often similar even when exact values differ.
Can excess mortality be negative?
Yes. A country can record fewer deaths than expected if other mortality risks temporarily fall, for example during periods of reduced mobility or lower circulation of other infectious diseases. That happened in some places, although the countries at the top of this ranking experienced the opposite over the full pandemic-era window.
Sources
-
Our World in Data — cumulative excess deaths per million
Processed HMD and WMD-based series with methodological notes, quality caveats, and metadata for the public comparative indicator. -
World Mortality Dataset
Maintainer notes on scope, updates, and the decision not to publish excess-mortality estimates for 2024 onward. -
Karlinsky & Kobak — excess mortality repository
Public leaderboard image and companion country table used to verify the latest country ordering and per-capita values in the ranking. -
Human Mortality Database — STMF
Weekly all-cause mortality source used in many high-quality international excess-mortality comparisons. -
WHO — global excess deaths associated with COVID-19
Modelled country estimates for January 2020 to December 2021, useful for global context and methodological comparison.
Last updated: April 8, 2026. The ranking is presented as a 2020–2023 cumulative comparison because that is the latest broadly comparable public endpoint for this metric.
