As of January 18, 2023, Portugal had the highest COVID-19 vaccination rate in Europe having administered 272.78 doses per 100 people in the country, while Malta had administered 258.49 doses per 100. The UK was the first country in Europe to approve the Pfizer/BioNTech vaccine for widespread use and began inoculations on December 8, 2020, and so far have administered 224.04 doses per 100. At the latest data, Belgium had carried out 253.89 doses of vaccines per 100 population. Russia became the first country in the world to authorize a vaccine - named Sputnik V - for use in the fight against COVID-19 in August 2020. As of August 4, 2022, Russia had administered 127.3 doses per 100 people in the country.

The seven-day rate of cases across Europe shows an ongoing perspective of which countries are worst affected by the virus relative to their population. For further information about the coronavirus pandemic, please visit our dedicated Facts and Figures page.

The average for 2022 based on 187 countries was 84 percent. The highest value was in Antigua and Barbuda: 99 percent and the lowest value was in North Korea: 0 percent. The indicator is available from 1980 to 2022. Below is a chart for all countries where data are available.

As of March 20, 2023, around 391 doses of COVID-19 vaccines per 100 people in Cuba had been administered, one of the highest COVID-19 vaccine dose rates of any country worldwide. This statistic shows the rate of COVID-19 vaccine doses administered worldwide as of March 20, 2023, by country or territory.

This dataset provides values for CORONAVIRUS VACCINATION RATE reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

Worldwide Measles Vaccination Rates

Measles Vaccination Rates by Country and Year

By Throwback Thursday [source]

About this dataset

The WHO Region Name column represents the name of the World Health Organization (WHO) region to which each country belongs. The ISO Code column contains the standardized ISO code for each country. The Country Name column specifies the name of each individual country included in this dataset.

The Percentage of Surviving Infants receiving Dose column indicates the percentage of infants who received a specific dose of the measles vaccine and survived. This serves as an important indicator for tracking vaccination rates and overall healthcare effectiveness in relation to preventing measles deaths among infants.

Overall, this dataset provides valuable insights into global measles vaccination rates over a span of several decades. By analyzing this information, researchers and policymakers can assess trends in immunization coverage, identify areas where vaccine uptake is low or improving over time, and guide targeted interventions to increase vaccination rates and reduce infant mortality due to measles infection

How to use the dataset

Introduction:

• Understanding the Columns: a. WHO Region Name: It represents the name of the World Health Organization (WHO) region to which a country belongs. b. ISO Code: It provides the ISO code of each country, which is a standardized three-letter code assigned to represent countries. c. Country Name: This column contains the name of each country involved in the dataset. d. Vaccine: It indicates the type of vaccine administered for measles. e. Year: The year when data was recorded, ranging from 1980 to 2017 (numeric). f. Percentage of Surviving Infants receiving Dose: This represents the percentage value denoting infants who received a specified dose of measles vaccine and survived.

• Navigating through Data:

• To explore data for specific countries or regions, filter by using either 'Country Name' or 'WHO Region Name'.

• Utilize filtering according to specific vaccines if you are interested in studying particular types.

• Selection Tools:

• Use pandas library in Python or similar tools/software platforms like Excel or Google Sheets that support filtering capabilities based on columns mentioned above.

• Employ functions such as dataframe.loc[] in Python's pandas library for extracting desired subsets based on specific filters.

• Data Analysis Ideas: Here are some potential analysis ideas using this dataset:

a) Analyzing Trends Over Time: - Generate line plots/graphs comparing vaccination rates across multiple countries/regions over different years to identify trends and patterns. - Categorize countries/regions by their WHO regions utilizing bar plots/graphs, and analyze how vaccination rates vary within each region over time.

b) Regional Comparisons: - Compare the measles vaccination rates between countries within and across different WHO regions. - Identify the top-performing countries in terms of measles vaccination rates for specific years, regions, or vaccine types.

c) Impact of Vaccine Types: - Assess the impact of different measles vaccines by comparing their adoption rates and effectiveness. - Analyze how the percentage of surviving infants receiving a particular vaccine dose varies over time for individual countries or regions.

d) Outlier Detection: - Explore if there are any significant variations or outliers in measles vaccination rates among different countries or regions. Investigate possible

Research Ideas

• Evaluating the effectiveness of measles vaccination programs: This dataset can be used to analyze the percentage of infants who received the measles vaccine and survived in different countries and regions over time. By comparing this data with information on measles cases and mortality rates, researchers can assess the effectiveness of vaccination programs in preventing measles outbreaks and reducing infant mortality.
• Identifying disparities in vaccine coverage: The dataset can also be used to identify disparities in measles vaccine coverage between countries and regions. By examining the percentage of infants receiving the vaccine across different geographical areas, researchers can identify areas with low coverage rates and target interventions to improve vaccination rates in those regions.
• Assessing trends over time: Since this dataset includes data from 1980 to 2017, it allows for analysis of trends in measles vaccination rates over several decades. Researchers can examine whether there have been improvement...

As of December 23, 2022, around 80 percent of the population of the United States had been given at least one dose of a COVID-19 vaccination. This statistic shows the percentage of population in select countries and territories worldwide that had received a COVID-19 vaccination as of December 23, 2022.

As of June 30, 2023, Japan has administered around 310 doses of COVID-19 vaccine per 100 people, the highest in the Asia-Pacific region. In comparison, Papua New Guinea has administered only approximately 7.27 COVID-19 vaccine doses per 100 people.

By August 2024, Cuba had administered the largest number of vaccines against COVID-19 per 100 inhabitants in the Latin American region, followed by Chile and Peru. According to recent estimates, the Caribbean country applied around 410 doses per 100 population, accounting for one of the largest vaccination rates observed not only in the Latin American region, but worldwide. In comparison, Haiti registered the lowest vaccination rate within the region, with only 5.87 doses administered per 100 inhabitants. Booster shots started To reinforce the immune protection against the fast spread of the SARS-CoV-2, governments began to introduce booster shots in their immunization programs aiming at strengthening people’s immune response against new contagious COVID-19 variants. In Latin America, Cuba was leading on booster shots relative to its population among a selection of countries, with around 88 percent of the population receiving the extra dose. In comparison, these numbers are higher than those for the European Union and the United States. Pharmaceutical research continues As Omicron becomes more prominent worldwide, and recombinant variants emerge, research efforts to prevent and control the disease continue to progress. As of June 2022, there were around 2,700 clinical trials to treat COVID-19 and 1,752 COVID-19 vaccines trials in clinical development. Other studies were focused on mild, moderate and severe COVID-19, complication support, and post-COVID symptoms, among others.For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

As of March 15, 2023, Seychelles was the African country with the highest coronavirus (COVID-19) vaccination rate, with around 205 doses administered per 100 individuals. Mauritius and Rwanda followed with 201 and 190 doses per 100 people, respectively. Ranking fourth, Morocco had a vaccination rate of approximately 148 doses per 100 people, registering the third-highest number of inoculations after Egypt and Nigeria. In South Africa, the most affected country on the continent, the vaccination rate instead reached around 64 per 100 population.

How did Africa obtain the vaccines?

Vaccines in Africa were obtained in different ways. African nations both purchased new doses and received them from other countries. At the beginning of the vaccination campaigns, donations came from all over the world, such as China, the United Arab Emirates, India, and Russia. The United Nations-led COVAX initiative provided Oxford/AstraZeneca and Pfizer/BioNTech doses to several African countries. Within this program, the continent received nearly 270 million doses as of January 2022. Moreover, the vaccination campaign has also been an occasion for intra-African solidarity. Senegal has, for instance, donated vaccines to the Gambia, while in January 2021, Algeria announced that it would have shared its supply with Tunisia.

COVID-19 impact on the African economy

The spread of COVID-19 negatively affected socio-economic growth in Africa, with the continent’s Gross Domestic Product (GDP) contracting significantly in 2020. Specifically, Southern Africa experienced the sharpest decline, at minus six percent, followed by North Africa at minus 1.7 percent. Most of Africa’s key economic sectors were hit by the pandemic. The drop in global oil prices led to a crisis in the oil and gas sector. Nigeria, the continent’s leading oil-exporting country, witnessed a considerable decrease in crude oil trade in 2020. Moreover, the shrinking number of international tourist arrivals determined a loss of over 12 million jobs in Africa’s travel and tourism sector. Society has also been substantially affected by COVID-19 on the poorest continent in the world, and the number of people living in extreme poverty was estimated to increase by around 30 million in 2020.

Worldwide Measles Vaccinations

Tracking measles vaccination rates worldwide

By Throwback Thursday [source]

About this dataset

The dataset contains several columns that help analyze and compare the vaccination rates across different regions. These columns include: - Country: The name of the country where the data was collected. - ISO Code: The three-letter code assigned to each country by the International Organization for Standardization (ISO). - WHO Region: The region to which a particular country belongs as defined by the World Health Organization (WHO). - Data Source: The source from where the data was obtained, ensuring transparency in reporting. - Year: The year in which the measles vaccine coverage was recorded. - Immunization Coverage (%): This column represents the percentage of individuals vaccinated against measles within a given year for each respective country.

By analyzing this dataset, researchers and policymakers can gain useful insights into global immunization efforts, identify geographical disparities in vaccine coverage rates, assess the impact of vaccination campaigns over time, measure progress towards eliminating measles as per international goals, and inform evidence-based decision-making for improving public health outcomes worldwide.

Please note that this dataset does not contain any dates specific to individual records

How to use the dataset

• Understanding the Columns Let's begin by understanding the columns present in this dataset:

  • Country - Represents the name of a specific country or region.
  • Year - Indicates the year for which vaccination data is available.
  • Vaccination Rate- Represents the percentage of individuals vaccinated against measles in a particular country or region during a given year.

• Exploratory Data Analysis The first step when working with any new dataset is conducting exploratory data analysis (EDA) to gain insights into its contents and structure. Here are some key EDA steps you can take:

  • Identify unique countries/regions present in the Country column.
  • Determine which years have data available in this dataset.
  • Calculate summary statistics such as mean, median, minimum, maximum vaccination rates.

• Comparative Analysis One interesting aspect of this dataset is its ability to compare measles vaccination rates across different countries and regions over time. Here's how you can perform comparative analysis:

  i) Select specific countries/regions from the Country column that you want to analyze.

  ii) Filter out these selected countries/regions from your dataframe for further analysis.

  iii) Plot line charts or bar graphs to compare their vaccination rates over years.

• Analyzing Trends and Patterns By analyzing trends and patterns within this dataset, one can gain valuable insights into global measles vaccination behavior and effectiveness of immunization programs. Here are a few ideas to get started:

  i) Plot line and bar graphs to visualize overall trends in measles vaccination rates worldwide.

  ii) Identify countries where vaccination rates have significantly increased or decreased over time.

  iii) Identify any patterns or relationships between vaccination rates and other factors such as GDP, population, etc.

• Identifying Outliers While analyzing this dataset, pay attention to possible outliers that may skew your analysis or predictions. By identifying and handling these outliers appropriately, you can ensure robust conclusions from your analysis.

• Data Visualization Utilize data visualization techniques such as

Research Ideas

• Identifying countries with low measles vaccination rates: By analyzing the dataset, one can identify countries or regions with low measles vaccination rates over time. This information can be used to target and prioritize interventions, education campaigns, and resources to increase vaccination coverage in these areas.
• Understanding the relationship between vaccination rates and measles outbreaks: The dataset can help analyze the correlation between measles vaccination rates and outbreaks of this infectious disease worldwide. Researchers can investigate how higher vaccine coverage is associated with lower incidence of measles cases, highlighting the importance of immunization for disease prevention.
• Evaluating the impact of immunization programs: This dataset can be used to assess the effectiveness of different immunization programs implemented by various countries or...

IntroductionIn relatively wealthy countries, substantial between-country variability in COVID-19 vaccination coverage occurred. We aimed to identify influential national-level determinants of COVID-19 vaccine uptake at different COVID-19 pandemic stages in such countries.MethodsWe considered over 50 macro-level demographic, healthcare resource, disease burden, political, socio-economic, labor, cultural, life-style indicators as explanatory factors and coverage with at least one dose by June 2021, completed initial vaccination protocols by December 2021, and booster doses by June 2022 as outcomes. Overall, we included 61 European or Organisation for Economic Co-operation and Development (OECD) countries. We performed 100 multiple imputations correcting for missing data and partial least squares regression for each imputed dataset. Regression estimates for the original covariates were pooled over the 100 results obtained for each outcome. Specific analyses focusing only on European Union (EU) or OECD countries were also conducted.ResultsHigher stringency of countermeasures, and proportionately more older adults, female and urban area residents, were each strongly and consistently associated with higher vaccination rates. Surprisingly, socio-economic indicators such as gross domestic product (GDP), democracy, and education had limited explanatory power. Overall and in the OECD, greater perceived corruption related strongly to lower vaccine uptake. In the OECD, social media played a noticeable positive role. In the EU, right-wing government ideology exhibited a consistently negative association, while cultural differences had strong overall influence.ConclusionRelationships between country-level factors and COVID-19 vaccination uptake depended on immunization stage and country reference group. Important determinants include stringency, population age, gender and urbanization, corruption, government ideology and cultural context.

This study provides a macro-level societal and health system focused analysis of child vaccination rates in 30 European countries, exploring the effect of context on coverage. The importance of demography and health system attributes on health care delivery are recognized in other fields, but generally overlooked in vaccination. The analysis is based on correlating systematic data built up by the Models of Child Health Appraised (MOCHA) Project with data from international sources, so as to exploit a one-off opportunity to set the analysis within an overall integrated study of primary care services for children, and the learning opportunities of the ‘natural European laboratory’. The descriptive analysis shows an overall persistent variation of coverage across vaccines with no specific vaccination having a low rate in all the EU and EEA countries. However, contrasting with this, variation between total uptake per vaccine across Europe suggests that the challenge of low rates is related to country contexts of either policy, delivery, or public perceptions. Econometric analysis aiming to explore whether some population, policy and/or health system characteristics may influence vaccination uptake provides important results - GDP per capita and the level of the population’s higher education engagement are positively linked with higher vaccination coverage, whereas mandatory vaccination policy is related to lower uptake rates. The health system characteristics that have a significant positive effect are a cohesive management structure; a high nurse/doctor ratio; and use of practical care delivery reinforcements such as the home-based record and the presence of child components of e‑health strategies.

This dataset provides values for CORONAVIRUS VACCINATION RATE reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

BackgroundCountries deliver vaccines either through routine health services or supplementary immunization activities (SIAs), usually community-based or door-to-door immunization campaigns. While SIAs have been successful at increasing coverage of vaccines in low- and middle-income countries, they may disrupt the delivery of routine health services. We examine the impact of SIAs on routine vaccine coverage in five low-income countries.MethodsData on the number and timing of SIAs conducted in various countries was compiled by WHO and obtained through UNICEF. Information on the coverage of vaccines not targeted by SIAs (e.g., DPT) was extracted from the Demographic and Health Surveys. We focus on SIAs that took place between 1996 and 2013 in Bangladesh, Senegal, Togo, Gambia, and Cote d’Ivoire, and examine outcomes for children aged 12–59 months. To avoid biases resulting from non-random placement and timing of SIAs, we use age of a child at her first SIA as an instrumental variable for total exposure to SIAs.ResultsWe find that SIA exposure reduced the likelihood of receiving routine vaccines in all the countries included in the study; the coefficients of interest are however statistically insignificant for Gambia and Cote d’Ivoire. In countries that witnessed statistically significant SIA-induced declines in the likelihood of obtaining DPT 3, measles as well as BCG, reductions ranged from 1.3 percentage points (Senegal) to 5.5 percentage points (Bangladesh).ConclusionSIA exposure reduced routine vaccination rates in study countries. Efforts should be made to limit the detrimental impact of SIAs on the services provided by routine health systems.

This dataset provides values for CORONAVIRUS VACCINATION RATE reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

This dataset provides values for CORONAVIRUS VACCINATION RATE reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

BackgroundThe global COVID-19 pandemic is still ongoing, and cross-country and cross-period variation in COVID-19 age-adjusted case fatality rates (CFRs) has not been clarified. Here, we aimed to identify the country-specific effects of booster vaccination and other features that may affect heterogeneity in age-adjusted CFRs with a worldwide scope, and to predict the benefit of increasing booster vaccination rate on future CFR.MethodCross-temporal and cross-country variations in CFR were identified in 32 countries using the latest available database, with multi-feature (vaccination coverage, demographic characteristics, disease burden, behavioral risks, environmental risks, health services and trust) using Extreme Gradient Boosting (XGBoost) algorithm and SHapley Additive exPlanations (SHAP). After that, country-specific risk features that affect age-adjusted CFRs were identified. The benefit of booster on age-adjusted CFR was simulated by increasing booster vaccination by 1–30% in each country.ResultsOverall COVID-19 age-adjusted CFRs across 32 countries ranged from 110 deaths per 100,000 cases to 5,112 deaths per 100,000 cases from February 4, 2020 to Jan 31, 2022, which were divided into countries with age-adjusted CFRs higher than the crude CFRs and countries with age-adjusted CFRs lower than the crude CFRs (n = 9 and n = 23) when compared with the crude CFR. The effect of booster vaccination on age-adjusted CFRs becomes more important from Alpha to Omicron period (importance scores: 0.03–0.23). The Omicron period model showed that the key risk factors for countries with higher age-adjusted CFR than crude CFR are low GDP per capita and low booster vaccination rates, while the key risk factors for countries with higher age-adjusted CFR than crude CFR were high dietary risks and low physical activity. Increasing booster vaccination rates by 7% would reduce CFRs in all countries with age-adjusted CFRs higher than the crude CFRs.ConclusionBooster vaccination still plays an important role in reducing age-adjusted CFRs, while there are multidimensional concurrent risk factors and precise joint intervention strategies and preparations based on country-specific risks are also essential.

Estimated regression models of percentage of population fully vaccinated at 6, 12, 18 and 24 months post global roll-out.

This dataset provides values for CORONAVIRUS VACCINATION RATE reported in several countries. The data includes current values, previous releases, historical highs and record lows, release frequency, reported unit and currency.

BackgroundThe rapid development and rollout of COVID-19 vaccines helped reduce the pandemic’s mortality burden. The vaccine rollout, however, has been uneven; it is well known that vaccination rates tend to be lower in lower income countries. Vaccine uptake, however, ultimately depends on the willingness of individuals to get vaccinated. If vaccine confidence is low, then uptake will be low, regardless of country income level. We investigated the impact on country-level COVID-19 vaccination rates of both national income and vaccine hesitancy.MethodsWe estimated a linear regression model of COVID-19 vaccine uptake across 145 countries; this cross-sectional model was estimated at each of four time points: 6, 12, 18, and 24 months after the onset of global vaccine distribution. Vaccine uptake reflects the percentage of the population that had completed their primary vaccination series at the time point. Covariates include per capita GDP, an estimate of the percentage of country residents who strongly disagreed that vaccines are safe, and a variety of control variables. Next, we estimated these models of vaccine uptake by country income (countries below, and above the international median per capita GDP) to examine whether the impact of vaccine hesitancy varies by country income.ResultsWe find that GDP per capita has a pronounced impact on vaccine uptake at 6 months after global rollout. After controlling for other factors, there was a 22 percentage point difference in vaccination rates between the top 20% and the bottom 20% of countries ranked by per capita GDP; this difference grew to 38% by 12 months. The deleterious impact of distrust of vaccine safety on vaccine uptake became apparent by 12 months and then increased over time. At 24 months, there was a 17% difference in vaccination rates between the top 20% and the bottom 20% of countries ranked by distrust. The income stratified models reveal that the deleterious impact of vaccine distrust on vaccine uptake at 12 and 24 months is particularly evident in lower income countries.ConclusionsOur study highlights the important role of both national income and vaccine hesitancy in determining COVID-19 vaccine uptake globally. There is a need to increase the supply and distribution of pandemic vaccines to lower-income countries, and to take measures to improve vaccine confidence in these countries.