March 2024
The raw data is based upon weekly deaths data from Eurostat spanning from 2010 to 2023. For some countries (such as Germany) the data is limited to selected age groups so it will not be used in the correlation analysis.
The computed excess mortality is based upon our excess mortality analysis using method 2C as described in the methodology reports. The yearly excess mortality for each country and age group can be found in the yearly excess mortality analysis page.
Countries: AT, BE, BG, CZ, DK, EL (Greece), ES, FR, IT, HU, NL, PL, PT, RO, FI, SE, NO.
Source for Weekly Deaths (Eurostat): Eurostat table: Deaths by week, sex and 5-year age group.
Source for Vaccination data: European Centre for Disease Prevention and Control.
Source for Population Estimates (Eurostat and UN): Eurostat table: Population on 1st January by age, sex and type of projection.
This page shows the correlation analysis of yearly excess mortality as a function of total vaccination doses received for different European countries, for different population age groups. The excess mortality computations follow the methodology described in our reports (method 2C).
It allows individuals, researchers and institutions to visualise the data, and make their own conclusions based upon what they view. Each of the charts attempts to capture different aspects of the observed excess mortality during the Covid-19 pandemic years and in this particular case, relate it to the total number of vaccine doses received (as a percentage of the population).
All the data is downloadable and the original data sources, as well as methodologies to analyse the data, are provided. We will endeavour to update our servers as new data becomes available.
The following charts show the analysis of the relationship between annualised excess mortality for 2022 and 2023 and the total vaccine doses, for different age groups in the selected sample of European countries. The Covid-19 vaccinations data (x-axis) refers to the total accumulated doses until the last available datapoint, as a percentage of the respective age group population, for each country.
Definite conclusions regarding the results shown below need to be taken with caution, as there are several variables that might have contributed to excess deaths during this period of time. One such factor is the dynamics of the Covid-19 pandemic over time, which appears to have been different in countries from Western Europe (Italy, France, Spain) relative to Eastern European countries (Bulgaria, Romania, Poland, Czechia), with other countries falling in between (such as Hungary and Greece).
Eastern European countries appear to have suffered the brunt of the Covid-19 pandemic deaths in 2021, while the Western European countries seem to have been most affected in 2020 and early 2021. From our observations, it appears that for the Western European countries, from Q2-2021 the virus had become endemic and was possibly not responsible for significant excess mortality since then.
Another confounder is that Western European countries have very high vaccination levels for almost all age groups, while Eastern European countries have lower vaccination levels, particularly in younger populations.
It is therefore difficult to devise a single metric that could show a clear relationship between the vaccine penetration level in the population and excess mortality, when comparing different countries. We believe that the best measures are those that somehow avoid the brunt of the Covid-19 pandemic. For this we suggest:
1 - Monitoring the relationship between excess mortality and vaccine penetration for different countries, from 2022 onwards. Note that in the first quarter of 2022, Covid-19 was still impacting significantly the Eastern European countries.
2 - Comparing quarters that seasonally are less prone to have Covid-19 outbreaks (such as Q2 and Q3 in the Northern Hemisphere).
As previously mentioned, this page is dedicated to showing the correlation between excess mortality and vaccine rollout levels in 2022 and 2023. For viewing the correlation in different quarters, go to quarterly correlation analysis.
As previously mentioned, there are several confounding factors that could influence excess mortality in the different European countries. Additionally, natural noise in data sample of yearly deaths (due for instance to different patterns in seasonal flu) can lead to noise in the calculation of the baseline from which excess deaths were computed. Therefore, caution needs to be applied when making definite conclusions regarding the correlations shown in the charts above.
When analysing the charts above, we can observe that for ages groups 15-24, 25-49 and 50-59, the regression has a positive slope coefficient even though with weak statistical significance (tstat < 2.0). The positive slope of the regression line means that higher excess deaths are associated with countries with higher vaccination levels.
For individuals aged 60-69, the slope coefficient is close to zero, showing no relationship between excess deaths levels and total vaccination doses.
For individuals aged 70-79 and 80+, the slope coefficient is negative even though with no statistical significance.
These results on their own suggest that the cost-benefit relationship, in 2022, of having taken the vaccines is not favourable for individuals younger than 70. For 2023, the cost-benefit relationship appears unfavourable for all age groups.
PHINANCE TECHNOLOGIES