As of April 25, 2022, Mauritius was the African country with the highest number of coronavirus (COVID-19) doses secured per capita. The country had received **** COVID-19 vaccine doses per capita through bilateral agreements, donations, and the COVAX initiative. Seychelles and Rwanda followed with **** and **** doses per capita, respectively.

Context

All about an attempt to end the pandemic across the globe with the help of vaccinations for COVID-19. It is important to track and understand the effort that is in progress across the globe to administer doses of vaccinations. There could be many sources of information. This is one of the sources from Bloomberg that is captured and presented here. Additionally, I have tried to include the GDP per capita per country from Wiki so that we can see how that is influencing the vaccination progress.

Content

There are two files. a) Latest Global Covid-19 Vaccine tracker of all the countries and regions in the World as of September 11, 2021 b) GDP information per capita per country

Attribute Information (COVID19 vaccination Tracker file)

• Countries and regions - Name of countries
• Doses administered - Number of vaccine doses administered
• Enough for % of people - Number of vaccine doses administered as a % of population
• Percentage of population with 1+ dose - Percentage of the population vaccinated with at least 1+ dose
• Percentage of the population fully vaccinated - Percentage of the population fully vaccinated
• Daily rate of doses administered - Daily rate of doses administered

Attribute Information (for GDP file per country per capita)

• Country
• Subregion (Western Europe, Northern Europe etc.)
• Region (Europe, Asia etc.)
• GDP estimate $ as per IMF
• Year for IMF
• GDP estimate $ as per UN
• Year for UN
• GDP estimate $ as per World Bank
• Year for World Bank

Source

URL1: https://www.bloomberg.com/graphics/covid-vaccine-tracker-global-distribution/ URL2: https://en.wikipedia.org/wiki/List_of_countries_by_GDP_(nominal)_per_capita

Inspiration

The path to immunity and hope to get back to normalcy by tracking and analyzing the latest updates on vaccinations across the globe. As we gear up to end the pandemic, the vaccination tracker can help us answer the following questions.

• What are the Top N countries/regions where vaccinations are administered?
• What are the Top N countries/regions with fully vaccinated people?
• What are the Top N countries/regions with at least 1+ doses administered?
• What is the access to vaccines - by least wealthy and most wealthy countries? (based on GDP per capita per country data)
• What is the average daily rate of the dose administered? Which countries are Top N and Bottom N? Which countries are above and below the World average? and many more...

Thank you for reading.

Please give your feedback/upvote/comments if you find this useful and download.

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

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.

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.

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.

As of January 17, 2023, 96.3 percent of adults in Ireland had been fully vaccinated against COVID-19. According to the manufacturers of the majority of COVID-19 vaccines currently in use in Europe, being fully vaccinated is when a person receives two doses of the vaccine. In Portugal, 94.2 percent of adults had received a full course of the COVID-19 vaccination, as well as 93.9 percent of those in Malta had been fully vaccinated. On the other hand, only 35.8 percent of adults in Bulgaria had been fully vaccinated.

Furthermore, the seven-day rate of cases across Europe shows which countries are currently worst affected by the situation. For further information about the coronavirus pandemic, please visit our dedicated Facts and Figures page.

Global Covid-19 Data

Global Covid-19 data on cases, deaths, vaccinations, and more

By Valtteri Kurkela [source]

About this dataset

The dataset is constantly updated and synced hourly to ensure up-to-date information. With over several columns available for analysis and exploration purposes, users can extract valuable insights from this extensive dataset.

Some of the key metrics covered in the dataset include:

1. Vaccinations: The dataset covers total vaccinations administered worldwide as well as breakdowns of people vaccinated per hundred people and fully vaccinated individuals per hundred people.

2. Testing & Positivity: Information on total tests conducted along with new tests conducted per thousand people is provided. Additionally, details on positive rate (percentage of positive Covid-19 tests out of all conducted) are included.

3. Hospital & ICU: Data on ICU patients and hospital patients are available along with corresponding figures normalized per million people. Weekly admissions to intensive care units and hospitals are also provided.

4. Confirmed Cases: The number of confirmed Covid-19 cases globally is captured in both absolute numbers as well as normalized values representing cases per million people.

5.Confirmed Deaths: Total confirmed deaths due to Covid-19 worldwide are provided with figures adjusted for population size (total deaths per million).

6.Reproduction Rate: The estimated reproduction rate (R) indicates the contagiousness of the virus within a particular country or region.

7.Policy Responses: Besides healthcare-related metrics, this comprehensive dataset includes policy responses implemented by countries or regions such as lockdown measures or travel restrictions.

8.Other Variables of InterestThe data encompasses various socioeconomic factors that may influence Covid-19 outcomes including population density,membership in a continent,gross domestic product(GDP)per capita;

For demographic factors: -Age Structure : percentage populations aged 65 and older,aged (70)older,median age -Gender-specific factors: Percentage of female smokers -Lifestyle-related factors: Diabetes prevalence rate and extreme poverty rate

1. Excess Mortality: The dataset further provides insights into excess mortality rates, indicating the percentage increase in deaths above the expected number based on historical data.

The dataset consists of numerous columns providing specific information for analysis, such as ISO code for countries/regions, location names,and units of measurement for different parameters.

Overall,this dataset serves as a valuable resource for researchers, analysts, and policymakers seeking to explore various aspects related to Covid-19

How to use the dataset

Introduction:

• Understanding the Basic Structure:

  • The dataset consists of various columns containing different data related to vaccinations, testing, hospitalization, cases, deaths, policy responses, and other key variables.
  • Each row represents data for a specific country or region at a certain point in time.

• Selecting Desired Columns:

  • Identify the specific columns that are relevant to your analysis or research needs.
  • Some important columns include population, total cases, total deaths, new cases per million people, and vaccination-related metrics.

• Filtering Data:

  • Use filters based on specific conditions such as date ranges or continents to focus on relevant subsets of data.
  • This can help you analyze trends over time or compare data between different regions.

• Analyzing Vaccination Metrics:

  • Explore variables like total_vaccinations, people_vaccinated, and people_fully_vaccinated to assess vaccination coverage in different countries.
  • Calculate metrics such as people_vaccinated_per_hundred or total_boosters_per_hundred for standardized comparisons across populations.

• Investigating Testing Information:

  • Examine columns such as total_tests, new_tests, and tests_per_case to understand testing efforts in various countries.
  • Calculate rates like tests_per_case to assess testing efficiency or identify changes in testing strategies over time.

• Exploring Hospitalization and ICU Data:

  • Analyze variables like hosp_patients, icu_patients, and hospital_beds_per_thousand to understand healthcare systems' strain.
  • Calculate rates like icu_patients_per_million or hosp_patients_per_million for cross-country comparisons.

• Assessing Covid-19 Cases and Deaths:

  • Analyze variables like total_cases, new_ca...

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.

Summary statistics for outcome and explanatory variables.

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.

Since 2001, an aid consortium known as Gavi has accounted for over half of vaccination expenditure in the 75 eligible countries with an initial per capita GNI below $1,000. Regression discontinuity (RD) estimates show aid significantly displaced other immunization efforts and failed to increase vaccination rates for diseases covered by cheap, existing vaccines. For some newer and more expensive vaccines, i.e., Hib and rotavirus, we found large effects on vaccination and limited fungibility, though statistical significance is not robust. These RD estimates apply to middle-income countries near Gavi's eligibility threshold, and cannot rule out differential effects for the poorest countries.

COVID-19 Stats & Trends

Context

This dataset seeks to provide insights into what has changed due to policies aimed at combating COVID-19 and evaluate the changes in community activities and its relation to reduced confirmed cases of COVID-19. The reports chart movement trends, compared to an expected baseline, over time (from 2020/02/15 to 2020/02/05) by geography (across 133 countries), as well as some other stats about the country that might help explain the evolution of the disease.

Content

1. Grocery & Pharmacy: Mobility trends for places like grocery markets, food warehouses, farmers' markets, specialty food shops, drug stores, and pharmacies.
2. Parks: Mobility trends for places like national parks, public beaches, marinas, dog parks, plazas, and public gardens.
3. Residential: Mobility trends for places of residence.
4. Retail & Recreation: Mobility trends for places like restaurants, cafes, shopping centers, theme parks, museums, libraries, and movie theaters.
5. Transit stations: Mobility trends for places like public transport hubs such as subway, bus, and train stations.
6. Workplaces: Mobility trends for places of work.
7. Total Cases: Total number of people infected with the SARS-CoV-2.
8. Fatalities: Total number of deaths caused by CoV-19.
9. Government Response Stringency Index: Additive score of nine indicators of government response to CoV-19: School closures, workplace closures, cancellation of public events, public information campaigns, stay at home policies, restrictions on internal movement, international travel controls, testing policy, and contact tracing.
10. COVID-19 Testing: Total number of tests performed.
11. Total Vaccinations: Total number of shots given.
12. Total People Vaccinated: Total number of people given a shot.
13. Total People Fully Vaccinated: Total number of people fully vaccinated (might require two shots of some vaccines).
14. Population: Total number of inhabitants.
15. Population Density per km2: Number of human inhabitants per square kilometer.
16. Health System Index: Overall performance of the health system.
17. Human Development Index (HDI): Summary index based on life expectancy at birth, expected years of schooling for children and mean years of schooling for adults, and GNI per capita.
18. GDP (PPP) per capita: Gross Domestic Product (GDP) per capita based on Purchasing Power Parity (PPP), taking into account the relative cost of local goods, services and inflation rates of the country, rather than using international market exchange rates, which may distort the real differences in per capita income.
19. Elderly Population (percentage): Percentage of the population above the age of 65 years old.

References & Acknowledgements

Bing COVID-19 data. Available at: https://github.com/microsoft/Bing-COVID-19-Data COVID-19 Community Mobility Report. Available at: https://www.google.com/covid19/mobility/ COVID-19: Government Response Stringency Index. Available at: https://ourworldindata.org/grapher/covid-stringency-index Coronavirus (COVID-19) Testing. Available at: https://github.com/owid/covid-19-data/blob/master/public/data/testing/covid-testing-all-observations.csv Coronavirus (COVID-19) Vaccination. Available at: https://raw.githubusercontent.com/owid/covid-19-data/master/public/data/vaccinations/vaccinations.csv List of countries and dependencies by population. Available at: https://www.kaggle.com/tanuprabhu/population-by-country-2020 List of countries and dependencies by population density. Available at: https://www.kaggle.com/tanuprabhu/population-by-country-2020 List of countries by Human Development Index. Available at: http://hdr.undp.org/en/data Measuring Overall Health System Performance. Available at: https://www.who.int/healthinfo/paper30.pdf?ua=1 List of countries by GDP (PPP) per capita. Available at: https://data.worldbank.org/indicator/NY.GDP.PCAP.PP.CD List of countries by age structure (65+). Available at: https://data.worldbank.org/indicator/SP.POP.65UP.TO.ZS

Authors

• Diogo Silva, up201706892@fe.up.pt

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.

State-by-state data on United States COVID-19 vaccinations data

Acknowledgement and License

All data are produced by Our World in Data are completely open access under the Creative Commons BY license. You have the permission to use, distribute, and reproduce these in any medium, provided the source and authors are credited. In the case of our vaccination dataset, please give the following citation:

Mathieu, E., Ritchie, H., Ortiz-Ospina, E. et al. A global database of COVID-19 vaccinations. Nat Hum Behav (2021). https://doi.org/10.1038/s41562-021-01122-8

Data Set Column Details

location : name of the state or federal entity. date: date of the observation. total vaccinations: total number of doses administered. This is counted as a single dose, and may not equal the total number of people vaccinated, depending on the specific dose regime (e.g. people receive multiple doses). If a person receives one dose of the vaccine, this metric goes up by 1. If they receive a second dose, it goes up by 1 again. total vaccinations per hundred: total vaccinations per 100 people in the total population of the state. daily vaccinations raw: daily change in the total number of doses administered. It is only calculated for consecutive days. This is a raw measure provided for data checks and transparency, but we strongly recommend that any analysis on daily vaccination rates be conducted using daily vaccinations instead. daily vaccinations: new doses administered per day (7-day smoothed). For countries that don't report data on a daily basis, we assume that doses changed equally on a daily basis over any periods in which no data was reported. This produces a complete series of daily figures, which is then averaged over a rolling 7-day window. An example of how we perform this calculation can be found here. daily vaccinations per million: daily vaccinations per 1,000,000 people in the total population of the state. people vaccinated: total number of people who received at least one vaccine dose. If a person receives the first dose of a 2-dose vaccine, this metric goes up by 1. If they receive the second dose, the metric stays the same. people vaccinated per hundred: people vaccinated per 100 people in the total population of the state. people fully vaccinated: total number of people who received all doses prescribed by the initial vaccination protocol. If a person receives the first dose of a 2-dose vaccine, this metric stays the same. If they receive the second dose, the metric goes up by 1. people fully vaccinated per hundred: people fully vaccinated per 100 people in the total population of the state. total distributed: cumulative counts of COVID-19 vaccine doses recorded as shipped in CDC's Vaccine Tracking System. total distributed per hundred: cumulative counts of COVID-19 vaccine doses recorded as shipped in CDC's Vaccine Tracking System per 100 people in the total population of the state. share doses used: share of vaccination doses administered among those recorded as shipped in CDC's Vaccine Tracking System. total boosters: total number of COVID-19 vaccination booster doses administered (doses administered beyond the number prescribed by the initial vaccination protocol) total boosters per hundred: total boosters per 100 people in the total population.

Time Span

20th Dec 2020 to 28th Dec 2022

Global Veterinary Vaccines Except for Foot and Mouth Market Size Value Per Capita by Country, 2023 Discover more data with ReportLinker!

Sources of the variables that appear in the regression models.

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.

GNI: Gross National Income; DGP: Gross Domesitc Product; USD: United States Dollars.1Total gross national income per-capita, total expenditure on health, percent of deaths among children <5 years caused by pneumonia and ranking of pneumonia as the cause of childhood mortality updated May 2012 and found at: levels for each country found at: http://www.who.int/countries/en/.2World Bank country classification can be found at: http://data.worldbank.org/about/country-classifications/country-and-lending-groups.3Routine childhood vaccinations are tuberculosis (BCG), diptheria, tetanus, pertussis (DTP), oral polio vaccine (OPV), hepatitis B, and measles-containing vaccine (MCV).4Percent of routine vaccinations funded by government and under 5-year mortality rates updated Oct 2012 and found at: http://apps.who.int/immunization_monitoring/en/globalsummary/countryprofileselect.cfm.

Based on a comparison of coronavirus deaths in 210 countries relative to their population, Peru had the most losses to COVID-19 up until July 13, 2022. As of the same date, the virus had infected over 557.8 million people worldwide, and the number of deaths had totaled more than 6.3 million. Note, however, that COVID-19 test rates can vary per country. Additionally, big differences show up between countries when combining the number of deaths against confirmed COVID-19 cases. The source seemingly does not differentiate between "the Wuhan strain" (2019-nCOV) of COVID-19, "the Kent mutation" (B.1.1.7) that appeared in the UK in late 2020, the 2021 Delta variant (B.1.617.2) from India or the Omicron variant (B.1.1.529) from South Africa.

The difficulties of death figures

This table aims to provide a complete picture on the topic, but it very much relies on data that has become more difficult to compare. As the coronavirus pandemic developed across the world, countries already used different methods to count fatalities, and they sometimes changed them during the course of the pandemic. On April 16, for example, the Chinese city of Wuhan added a 50 percent increase in their death figures to account for community deaths. These deaths occurred outside of hospitals and went unaccounted for so far. The state of New York did something similar two days before, revising their figures with 3,700 new deaths as they started to include “assumed” coronavirus victims. The United Kingdom started counting deaths in care homes and private households on April 29, adjusting their number with about 5,000 new deaths (which were corrected lowered again by the same amount on August 18). This makes an already difficult comparison even more difficult. Belgium, for example, counts suspected coronavirus deaths in their figures, whereas other countries have not done that (yet). This means two things. First, it could have a big impact on both current as well as future figures. On April 16 already, UK health experts stated that if their numbers were corrected for community deaths like in Wuhan, the UK number would change from 205 to “above 300”. This is exactly what happened two weeks later. Second, it is difficult to pinpoint exactly which countries already have “revised” numbers (like Belgium, Wuhan or New York) and which ones do not. One work-around could be to look at (freely accessible) timelines that track the reported daily increase of deaths in certain countries. Several of these are available on our platform, such as for Belgium, Italy and Sweden. A sudden large increase might be an indicator that the domestic sources changed their methodology.

Where are these numbers coming from?

The numbers shown here were collected by Johns Hopkins University, a source that manually checks the data with domestic health authorities. For the majority of countries, this is from national authorities. In some cases, like China, the United States, Canada or Australia, city reports or other various state authorities were consulted. In this statistic, these separately reported numbers were put together. For more information or other freely accessible content, please visit our dedicated Facts and Figures page.