This study adopts a retrospective, observational design that leverages secondary data to analyze age-specific COVID-19 vaccine distribution patterns across multiple European nations. The aim is to explore how vaccines were distributed across various age groups, and countries, over the study period of September 2021 to September 2023.

Given that this study uses pre-existing aggregated data, no direct interventions or modifications are made to the data. The analysis will focus on observing trends and drawing conclusions from the distribution patterns. A cross-sectional approach will be used at multiple time points to capture shifts in distribution patterns as the pandemic progressed and vaccine supply increased.

This design is appropriate for assessing vaccine distribution policies retrospectively, allowing for a detailed examination of trends without the need for primary data collection. The key advantage of using secondary data is its ability to capture wide-ranging and large-scale data points across different time periods and geographic regions, which provides a robust framework for analyzing population-level patterns.

The study will utilize publicly available data obtained from the European Centre for Disease Prevention and Control (ECDC). The ECDC compiles and shares data on COVID-19 vaccination coverage across European countries. This data will serve as the backbone of the cross-country comparison.

Data collection for this study was submitted to the European Union/European Economic Area through the European Surveillance System (TESSy) and covered the period from September 2021 to September 2023. To ensure uniformity across countries, the study will limit its scope to countries with complete, reliable data on vaccine doses administered by age group. The study will include variables such as age, number of doses administered, and the time period of administration.

The study population is composed of aggregated, age-specific vaccine data representing individuals from multiple European countries. This population-level data includes individuals who received one or more doses of a COVID-19 vaccine during the study period. Since the study utilizes secondary data, no personal identifiers will be involved, and the analysis will focus on aggregate outcomes at the national level. These age categories allow for a detailed examination of vaccine distribution across various demographic segments, facilitating comparisons between younger and older populations. The choice of countries will be based on the availability of comprehensive data for these age groups.

The analysis will focus on several key variables, both dependent and independent, to ensure a thorough examination of vaccine distribution patterns:

The analysis was conducted using both descriptive and inferential statistical methods. The following steps outline the process for analyzing the dataset.

The initial analysis will involve calculating summary statistics for some variable frequencies, to provide a clear overview of vaccine distribution across age groups and countries. These results will help identify overarching patterns in the data, including which age groups received higher priority in the vaccine distribution process.

To determine whether there are significant differences in vaccine distribution between age groups and countries, the following inferential statistical tests will be applied:

1) Analysis of Variance (ANOVA) will be used to compare mean vaccination rates, between different age groups across the countries. This will help assess whether certain age groups received disproportionately more vaccines across different countries.

2) The Z-tests will be employed to compare the proportion of vaccinated individuals in high priority age groups (>70 years) across selected countries.

To explore cross-country differences in vaccine distribution strategies, cross-tabulation and chi-square tests were used. This will allow the study to assess whether certain countries prioritized older age groups more than others. Graphical representations such as heat maps and bar charts will visually display the distribution patterns. For example, countries with a high proportion of elderly citizens might have prioritized vaccines for the 60+ age groups, while others may have opted for a more even distribution across all age groups.

The data will be processed and analyzed using R programming Language. This language is well-equipped to handle large datasets and conduct the variety of statistical tests outlined above. The graphical outputs, including plots, heat maps, and comparative bar charts, will be generated using these tools to provide a clear and comprehensive visual representation of the findings.

Since this study uses secondary data that is publicly available and anonymized at the aggregate level, there are minimal ethical concerns regarding individual privacy. However, all data will be handled in accordance with ethical guidelines for the use of secondary data, ensuring that no attempts are made to de-anonymize or link the data to specific individuals. Additionally, the study will comply with all legal and institutional policies regarding the use of publicly available data.

The study uses pre-existing aggregated data that were submitted by European Union/European Economic Area (EU/EEA) countries to ECDC through The European Surveillance System (TESSy) on scheduled dates. EU/EEA countries report aggregated data on the number of individuals receiving one vaccine dose during the reporting period starting from 01 September 2023. Doses are also reported by vaccine product. The variables in the dataset are summarized in the Appendix 1 titled data dictionary.

In this study, we focused primarily on the non-overlapping age groups 0 - 4, 5 - 9, 10 - 17, 18 - 24, 25 - 49, 50 - 69 and >70 (Prioritized Group) as shown in Figure 1 . Health Care Workers (HCW), Pregnant Women and other individuals aged 18 - 59 with underlying chronic medical conditions were excluded in the study.

We test for association between age groups and countries. The goal is to verify if the countries in the study jointly prioritized certain age groups against others in their vaccination campaign. Using the Chi-Square test of association, we present the test below:

Null hypothesis (H₀): There is no association between age groups and countries in the vaccination campaign.

Alternative hypothesis (H₁): There is an association between age groups and countries in the vaccination campaign.

Level of significance = 5%

Test Statistic: ${\chi }^2$ = ${\text{Σ}}_{ij}\frac{{\left(O_{ij-}{E}_{ij}\right)}^2}{E_{ij}}$ follows ${\chi }_{\left(r-1\right)\left(c-1\right)}$

where

O_ij = Observed values;

E_ij = Expected Values;

(r − 1) (c − 1) = Degree of freedom.

Decision Rule:

Reject the null hypothesis if the p-value is less than 0.05. Do not reject if otherwise.

It is important to note that, vaccine frequency distribution by itself does not tell the whole story because, it only captures frequency and not rates. Therefore, a contingency table of age groups and countries to investigate association between the two categorical variables namely age groups and country using Chi-Square test was used as presented in Table 1 . The result shows a p-value (2.2e−16) < 0.05, we therefore, conclude that vaccination in different countries in Europe is associated with the age intervals.

Table 2 shows, vaccination rates increase with age, peaking at the 25 - 49 age group (1.34 × 10⁻⁴), after which, there was a decline in vaccination rate. The youngest age group (0 - 4 years) has the lowest rate (3.04 × 10⁻⁸), while older adults, especially those over 50, show moderate rates. There is a notable rise from childhood (0 - 17 years) to young adulthood (18 - 24 years). The rates remain relatively stable between 50 and 69 years, with a slight drop in those over 70. This pattern suggests higher vaccination uptake among working-age adults, followed by a decline in older age groups.

In Table 3 , we performed an analysis of variance (ANOVA) to investigate the equality of mean vaccination rates across the 29 countries in Europe. Since our p-values for both sources of variations (age groups interval and countries) are <0.05, We conclude that there are significant differences in age-specific vaccination rates. Secondly, the results show a significant difference in vaccination rates across the countries as displayed in Figure 2 . Also, the very low p-values coming from the variables indicate that the effects of the age and country are highly significant statistically. We utilized the Tukey Honest Significant Difference (HSD) to identify the pairs that are statistically significant at 5% level. The results in ( Table 4 ) showed that most of the pairwise comparisons were statistically significant with p-value < 0.05. Hence to reduce ambiguity, we identified the age groups that actually did not lead to the variation.

We performed a series of Z-tests, presented in the table below, Table 5 , which compares vaccination proportions in the high-priority age group-in people over 70-years-old across different countries. There was a significant difference between vaccination proportion in Austria-20% and Belgium-33%: χ² = 298.82, p < 2.2e−16; and between Denmark-20% and Iceland-33%: χ² = 6.23, p < 0.013. A repeated comparison between Denmark and Iceland (p < 0.0125) reaffirmed the significant disparity. Additionally, Romania (33%) and Sweden (29%) showed a statistically significant difference in vaccination coverage (χ² = 17.95, p < 2.27e−05). The insignificant difference in vaccination proportion between Finland and Poland suggests a similarity in proportions, probably because of similar policy regimes addressing this group. The summary of the vaccination coverage for the > 70 years age group is presented in Table 6 . Belgium, Bulgaria, Italy, Estonia, Romania, France, and Malta generally have the highest vaccination proportion (33.3%). Conversely, Austria reports the lowest proportion at 10.6%, while several countries, including Greece, Spain, Finland, Croatia, Lithuania, the Netherlands, and Poland, have around 20% vaccination coverage for the priority group.

Despite the improved supply of COVID-19 vaccine in 2021, which was meant to lead to improved and larger coverage for Europeans countries and the vulnerable populations such as the elderly which in our study were the prioritized age group (>70 years), there was a low vaccination coverage of this age group. Our study evaluated age-specific COVID-19 vaccine distribution patterns in (29) European Union (EU) countries to better understand the variation in the distribution patterns across different age groups and to access the level of prioritization given to prioritized vulnerable age groups (Age > 70) in their vaccination programs. Our result shows that vaccination rates in countries in Europe are associated with the age intervals. Two sources of variations in our study were Age and Country. A critical examination of the ANOVA result suggests country is a stronger source of variation than age in vaccination rates and frequencies across the continent. This observation is evident in the F-value of Country (355.3) which is much greater than F-value of Age (232.2). Hence, we can conclude that geographical or other conditions peculiar to the country are more influential in driving the outcome than the age itself. There was a concerning low coverage of vaccination for the >70 years age group across Europe, with seven (7) countries namely Belgium, Bulgaria, Italy, Estonia, Romania, France, and Malta vaccinated just about 1:3 population (33.3%) of their most vulnerable age-group population given the risk of severe outcomes that were associated with this age group. Conversely, Austria reports the lowest rate at 10.6%, while several countries, including Greece, Spain, Finland, Croatia, Lithuania, the Netherlands, and Poland, have around 20% vaccination coverage for the priority group. Given that morbidity and mortality are highest among this age group [7] [21] , based on data, no European country achieved the 70% coverage aimed by WHO by 2022 within the time period [22] . Contrary to the low coverage among European countries, by early April 2021, 79.6% of adults aged 65 - 74 and 78.3% of ≥75 years had received at least ≥1 dose of vaccine in the US [23] . Approximately 99.9% of older persons aged 65 - 74 and 98.1% of those aged ≥ 75 had received at least one dose of a COVID-19 vaccine, by 2022. In the United Kingdom, around 95% of those aged ≥ 65 have been fully vaccinated against COVID-19 [24] [25] . In other studies, even the oldest-old age group (≥80 years) had 72.0% of the population vaccinated with the first dose by the end of summer 2022 [26] .

Our study shows there was a low coverage of COVID-19 vaccination for the prioritized age group (>70) during the study period. Challenges such as vaccines hesitancy, poor public health outreach to the elderly group and logistical constraint may have independently or collectively contributed to the low coverage. This supports the findings of Zhang et al., that living alone, being older, having chronic conditions, and having a lower self-rated health status were all associated with vaccine resistance and hesitation, and they concluded that poor health or vaccine side effects were the main causes [27] . Additionally, the elderly may not have internet access, are inexperienced with online scheduling, or lack transportation means. These factors pose a challenge to easy access to vaccines [28] .

Continuous efforts must be made to ensure larger coverage of COVID-19 vaccination among this vulnerable population in other to protect them from additional severe outcomes of COVID-19 among the European countries. Primary healthcare centers should integrate Covid-19 vaccination into regular immunization services to ensure wider coverage of vaccination for all age groups and most importantly, the vulnerable age population.

Our study highlights a significant gap in COVID-19 vaccine coverage for the prioritized elderly population (age > 70) across 29 European Union countries, despite improved vaccine supply in 2021. The findings indicate that variations in vaccination rates are influenced more by country-specific factors than by age, as evidenced by the higher F-value for the country in the ANOVA analysis. The low vaccination coverage in several countries, particularly among the most vulnerable age groups, underscores the need for targeted interventions. Factors such as vaccine hesitancy, inadequate public health outreach to elderly populations, and logistical challenges may have contributed to this shortfall. In contrast, countries like the United States and the United Kingdom demonstrated significantly higher coverage among older adults. To protect this high-risk population from severe outcomes of COVID-19, continuous efforts are necessary to improve vaccine distribution and uptake. Integrating COVID-19 vaccination into routine immunization services at primary healthcare centers could help ensure broader coverage, particularly for vulnerable populations. Addressing the gaps identified in this study is crucial to achieving equitable vaccine access and reducing the impact of COVID-19 among older adults in Europe.

To improve COVID-19 vaccination coverage among the elderly, potential measures that can be taken to improve vaccine distribution includes:

1) Strengthening public health communication strategies is crucial to addressing vaccine hesitancy and misinformation in this vulnerable group.

2) Expanding access through mobile units, home-based services, and simplifying administrative processes could overcome logistical barriers, especially in rural areas.

3) Integrating COVID-19 vaccination into routine healthcare services at primary care centers would ensure sustained coverage for older adults.

4) Given the significant variation in vaccination rates between countries, national strategies should be adapted to address country-specific challenges such as supply chain issues, public health infrastructure, and cultural factors.

5) Enhancing international collaboration, knowledge exchange, and continuous monitoring of vaccine supplies are also critical to ensuring equitable access.

Future research should focus on understanding the specific determinants of vaccine hesitancy among older adults, particularly in the context of socio-cultural and psychological barriers. Further investigation is needed into the effectiveness of logistical interventions like mobile vaccination units in reaching rural and underserved populations. Additionally, studies could explore how country-specific factors such as healthcare systems and political environments influence vaccine distribution success. Longitudinal research examining the integration of COVID-19 vaccines into routine immunization programs and its impact on coverage rates would offer valuable insights for future pandemic preparedness. Lastly, examining the public health consequences of low vaccine coverage among the elderly in terms of morbidity and mortality could inform better strategies for prioritizing high-risk populations in future health crises.

Source: European Centre for Disease Control (ECDC).