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 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.

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.

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.

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...

Context

The COVID-19 outbreak has brought the whole planet to its knees.More over 4.5 million people have died since the writing of this notebook, and the only acceptable way out of the disaster is to vaccinate all parts of society. Despite the fact that the benefits of vaccination have been proved to the world many times, anti-vaccine groups are springing up all over the world. This data set was generated to investigate the impact of coronavirus vaccinations on coronavirus mortality.

Content

country	iso_code	date	total_vaccinations	people_vaccinated	people_fully_vaccinated	New_deaths	population	ratio
country name	iso code for each country	date that this data belong	number of all doses of COVID vaccine usage in that country	number of people who got at least one shot of COVID vaccine	number of people who got full vaccine shots	number of daily new deaths	2021 country population	% of vaccinations in that country at that date = people_vaccinated/population * 100

Data Collection

This dataset is a combination of the following three datasets:

1.https://www.kaggle.com/gpreda/covid-world-vaccination-progress

2.https://covid19.who.int/WHO-COVID-19-global-data.csv

3.https://www.kaggle.com/rsrishav/world-population

you can find more detail about this dataset by reading this notebook:

https://www.kaggle.com/sinakaraji/simple-linear-regression-covid-vaccination

Countries in this dataset:

Afghanistan	Albania	Algeria	Andorra	Angola
Anguilla	Antigua and Barbuda	Argentina	Armenia	Aruba
Australia	Austria	Azerbaijan	Bahamas	Bahrain
Bangladesh	Barbados	Belarus	Belgium	Belize
Benin	Bermuda	Bhutan	Bolivia (Plurinational State of)	Brazil
Bosnia and Herzegovina	Botswana	Brunei Darussalam	Bulgaria	Burkina Faso
Cambodia	Cameroon	Canada	Cabo Verde	Cayman Islands
Central African Republic	Chad	Chile	China	Colombia
Comoros	Cook Islands	Costa Rica	Croatia	Cuba
Curaçao	Cyprus	Denmark	Djibouti	Dominica
Dominican Republic	Ecuador	Egypt	El Salvador	Equatorial Guinea
Estonia	Ethiopia	Falkland Islands (Malvinas)	Fiji	Finland
France	French Polynesia	Gabon	Gambia	Georgia
Germany	Ghana	Gibraltar	Greece	Greenland
Grenada	Guatemala	Guinea	Guinea-Bissau	Guyana
Haiti	Honduras	Hungary	Iceland	India
Indonesia	Iran (Islamic Republic of)	Iraq	Ireland	Isle of Man
Israel	Italy	Jamaica	Japan	Jordan
Kazakhstan	Kenya	Kiribati	Kuwait	Kyrgyzstan
Lao People's Democratic Republic	Latvia	Lebanon	Lesotho	Liberia
Libya	Liechtenstein	Lithuania	Luxembourg	Madagascar
Malawi	Malaysia	Maldives	Mali	Malta
Mauritania	Mauritius	Mexico	Republic of Moldova	Monaco
Mongolia	Montenegro	Montserrat	Morocco	Mozambique
Myanmar	Namibia	Nauru	Nepal	Netherlands
New Caledonia	New Zealand	Nicaragua	Niger	Nigeria
Niue	North Macedonia	Norway	Oman	Pakistan
occupied Palestinian territory, including east Jerusalem
Panama	Papua New Guinea	Paraguay	Peru	Philippines
Poland	Portugal	Qatar	Romania	Russian Federation
Rwanda	Saint Kitts and Nevis	Saint Lucia
Saint Vincent and the Grenadines	Samoa	San Marino	Sao Tome and Principe	Saudi Arabia
Senegal	Serbia	Seychelles	Sierra Leone	Singapore
Slovakia	Slovenia	Solomon Islands	Somalia	South Africa
Republic of Korea	South Sudan	Spain	Sri Lanka	Sudan
Suriname	Sweden	Switzerland	Syrian Arab Republic	Tajikistan
United Republic of Tanzania	Thailand	Togo	Tonga	Trinidad and Tobago
Tunisia	Turkey	Turkmenistan	Turks and Caicos Islands	Tuvalu
Uganda	Ukraine	United Arab Emirates	The United Kingdom	United States of America
Uruguay	Uzbekistan	Vanuatu	Venezuela (Bolivarian Republic of)	Viet Nam
Wallis and Futuna	Yemen	Zambia	Zimbabwe

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.

How many people have received a coronavirus vaccine?

Tracking COVID-19 vaccination rates is crucial to understand the scale of protection against the virus, and how this is distributed across the global population.

A global, aggregated database on COVID-19 vaccination rates is essential to monitor progress, but it is unfortunately not yet available. This dataset provides the last weekly update of vaccination rates.

Last update

June 2021

Content

Colums description: 1. iso_code: ISO 3166-1 alpha-3 – three-letter country codes 2. continent: Continent of the geographical location 3. location: Geographical location 4. date: Date of observation 5. total_cases: Total confirmed cases of COVID-19 6. new_cases: New confirmed cases of COVID-19 7. new_cases_smoothed: New confirmed cases of COVID-19 (7-day smoothed) 8. total_deaths: Total deaths attributed to COVID-19 9. new_deaths: New deaths attributed to COVID-19 10. new_deaths_smoothed: New deaths attributed to COVID-19 (7-day smoothed) 11. total_cases_per_million: Total confirmed cases of COVID-19 per 1,000,000 people 12. new_cases_per_million: New confirmed cases of COVID-19 per 1,000,000 people 13. new_cases_smoothed_per_million: New confirmed cases of COVID-19 (7-day smoothed) per 1,000,000 people 14. total_deaths_per_million: Total deaths attributed to COVID-19 per 1,000,000 people 15. new_deaths_per_million: New deaths attributed to COVID-19 per 1,000,000 people 16. new_deaths_smoothed_per_million: New deaths attributed to COVID-19 (7-day smoothed) per 1,000,000 people 17. reproduction_rate: Real-time estimate of the effective reproduction rate (R) of COVID-19. See http://trackingr-env.eba-9muars8y.us-east-2.elasticbeanstalk.com/FAQ 18. icu_patients: Number of COVID-19 patients in intensive care units (ICUs) on a given day 19. icu_patients_per_million: Number of COVID-19 patients in intensive care units (ICUs) on a given day per 1,000,000 people 20. hosp_patients: Number of COVID-19 patients in hospital on a given day 21. hosp_patients_per_million: Number of COVID-19 patients in hospital on a given day per 1,000,000 people 22. weekly_icu_admissions: Number of COVID-19 patients newly admitted to intensive care units (ICUs) in a given week 23. weekly_icu_admissions_per_million: Number of COVID-19 patients newly admitted to intensive care units (ICUs) in a given week per 1,000,000 people 24. weekly_hosp_admissions: Number of COVID-19 patients newly admitted to hospitals in a given week 25. weekly_hosp_admissions_per_million: Number of COVID-19 patients newly admitted to hospitals in a given week per 1,000,000 people 26. total_tests: Total tests for COVID-19 27. new_tests: New tests for COVID-19 28. new_tests_smoothed: New tests for COVID-19 (7-day smoothed). For countries that don't report testing data on a daily basis, we assume that testing 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 29. total_tests_per_thousand: Total tests for COVID-19 per 1,000 people 30. new_tests_per_thousand: New tests for COVID-19 per 1,000 people 31. new_tests_smoothed_per_thousand: New tests for COVID-19 (7-day smoothed) per 1,000 people 32. tests_per_case: Tests conducted per new confirmed case of COVID-19, given as a rolling 7-day average (this is the inverse of positive_rate) 33. positive_rate: The share of COVID-19 tests that are positive, given as a rolling 7-day average (this is the inverse of tests_per_case) 34. tests_units: Units used by the location to report its testing data 35. total_vaccinations: Number of COVID-19 vaccination doses administered 36. total_vaccinations_per_hundred: Number of COVID-19 vaccination doses administered per 100 people 37. stringency_index: Government Response Stringency Index: composite measure based on 9 response indicators including school closures, workplace closures, and travel bans, rescaled to a value from 0 to 100 (100 = strictest response) 38. population: Population in 2020 39. population_density: Number of people divided by land area, measured in square kilometers, most recent year available 40. median_age: Median age of the population, UN projection for 2020 41. aged_65_older: Share of the population that is 65 years and older, most recent year available 42. aged_70_older: Share of the population that is 70 years and older in 2015 43. gdp_per_capita: Gross domestic product at purchasing power parity (constant 2011 international dollars), most recent year available 44. extreme_poverty: Share of the population living in extreme poverty, most recent year available since 2010 45. cardiovasc_death_rate: Death rate from cardiovascular disease in 2017 (annual number of deaths per 100,000 people) 46. diabetes_prevalence: Diabetes prevalence (% of population aged 20 to 79) in 2017 47. female...

CDC COVID-19 Vaccine Tracker

Cumulative and Daily Counts of COVID-19 Vaccine Doses in the United States

By Nicky Forster [source]

About this dataset

The dataset contains data points such as the cumulative count of people who have received at least one dose of the vaccine, new doses administered on a specific date, cumulative count of doses distributed in the country, percentage of population that has completed the full vaccine series, cumulative count of Pfizer and Moderna vaccine doses administered in each state, seven-day rolling averages for new doses administered and distributed, among others.

It also provides insights into the vaccination status at both national and state levels. The dataset includes information on the percentage of population that has received at least one dose of the vaccine, percentage of population that has completed the full vaccine series, cumulative counts per 100k population for both distributed and administered doses.

Additionally, it presents data specific to each state, including their abbreviation and name. It outlines details such as cumulative counts per 100k population for both distributed and administered doses in each state. Furthermore, it indicates if there were instances where corrections resulted in single-day negative counts.

The dataset is compiled from daily snapshots obtained from CDC's COVID Data Tracker. Please note that there may be reporting delays by healthcare providers up to 72 hours after administering a dose.

This comprehensive dataset serves various purposes including tracking vaccination progress over time across different locations within the United States. It can be used by researchers, policymakers or anyone interested in analyzing trends related to COVID-19 vaccination efforts at both national and state levels

How to use the dataset

• Familiarize Yourself with the Columns: Take a look at the available columns in this dataset to understand what information is included. These columns provide details such as state abbreviations, state names, dates of data snapshots, cumulative counts of doses distributed and administered, people who have received at least one dose or completed the vaccine series, percentages of population coverage, manufacturer-specific data, and seven-day rolling averages.

• Explore Cumulative Counts: The dataset includes cumulative counts that show the total number of doses distributed or administered over time. You can analyze these numbers to track trends in vaccination progress in different states or regions.

• Analyze Daily Counts: The dataset also provides daily counts of new vaccine doses distributed and administered on specific dates. By examining these numbers, you can gain insights into vaccination rates on a day-to-day basis.

• Study Population Coverage Metrics: Metrics such as pct_population_received_at_least_one_dose and pct_population_series_complete give you an understanding of how much of each state's population has received at least one dose or completed their vaccine series respectively.

• Utilize Manufacturer Data: The columns related to Pfizer and Moderna provide information about the number of doses administered for each manufacturer separately. By analyzing this data, you can compare vaccination rates between different vaccines.

• Consider Rolling Averages: The seven-day rolling average columns allow you to smooth out fluctuations in daily counts by calculating an average over a week's time window. This can help identify long-term trends more accurately.

• Compare States: You can compare vaccination progress between different states by filtering the dataset based on state names or abbreviations. This way, you can observe variations in distribution and administration rates among different regions.

• Visualize the Data: Creating charts and graphs will help you visualize the data more effectively. Plotting trends over time or comparing different metrics for various states can provide powerful visual representations of vaccination progress.

• Stay Informed: Keep in mind that this dataset is continuously updated as new data becomes available. Make sure to check for any updates or refreshed datasets to obtain the most recent information on COVID-19 vaccine distributions and administrations

Research Ideas

• Vaccination Analysis: This dataset can be used to analyze the progress of COVID-19 vaccinations in the United States. By examining the cumulative counts of doses distributed and administered, as well as the number of people who have received at least one dose or completed the vaccine series, researchers and policymakers can assess how effectively vaccines are being rolled out and monitor...

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.

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.

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.

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.

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.

About this Dataset

The data contains the following information:

Country- this is the country for which the vaccination information is provided; Country ISO Code - ISO code for the country; Date - date for the data entry; for some of the dates we have only the daily vaccinations, for others, only the (cumulative) total; Total number of vaccinations - this is the absolute number of total immunizations in the country; Total number of people vaccinated - a person, depending on the immunization scheme, will receive one or more (typically 2) vaccines; at a certain moment, the number of vaccination might be larger than the number of people; Total number of people fully vaccinated - this is the number of people that received the entire set of immunization according to the immunization scheme (typically 2); at a certain moment in time, there might be a certain number of people that received one vaccine and another number (smaller) of people that received all vaccines in the scheme; Daily vaccinations (raw) - for a certain data entry, the number of vaccination for that date/country; Daily vaccinations - for a certain data entry, the number of vaccination for that date/country; Total vaccinations per hundred - ratio (in percent) between vaccination number and total population up to the date in the country; Total number of people vaccinated per hundred - ratio (in percent) between population immunized and total population up to the date in the country; Total number of people fully vaccinated per hundred - ratio (in percent) between population fully immunized and total population up to the date in the country; Number of vaccinations per day - number of daily vaccination for that day and country; Daily vaccinations per million - ratio (in ppm) between vaccination number and total population for the current date in the country; Vaccines used in the country - total number of vaccines used in the country (up to date); Source name - source of the information (national authority, international organization, local organization etc.); Source website - website of the source of information;

Tasks: Track the progress of COVID-19 vaccination What vaccines are used and in which countries? What country is vaccinated more people? What country is vaccinated a larger percent from its population?

This data is valuble in relation to the health, financial, and engineering sectors.

Category

Health & Medicine

Keywords

Health,Medicine,covid-19,dataset,progress

Row Count

5824

Price

$120.00

Dataset contains: Latest worldwide vaccination status of all the countries till 08th Jan 2023.

Features: Country-Name of the country Pct. of population Vaccinated-Percentage of population Vaccinated Pct. of population Fully vaccinated-Percentage of population Fully vaccinated Additional Doses Per 100 people-Number of additional doses per 100 people Additional Doses Total-Number of total additional doses Doses administered Per 100 people-Number of vaccine doses administered per 100 people Total Doses administered-Total number of doses administered

Coronavirus disease 2019 (COVID-19) is a contagious disease caused by a virus, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The first known case was identified in Wuhan, China, in December 2019.The disease quickly spread worldwide, resulting in the COVID-19 pandemic.

Vaccines save millions of lives each year and a COVID-19 vaccine could save yours. The COVID-19 vaccines are safe and effective, providing strong protection against serious illness and death. WHO reports that unvaccinated people have at least 10 times higher risk of death from COVID-19 than someone who has been vaccinated.The COVID-19 vaccines are highly effective, but no vaccine provides 100 per cent protection. Some people will still get ill from COVID-19 after vaccination or pass the virus onto someone else. Therefore, it is important to continue practicing safety precautions to protect yourself and others, including avoiding crowded spaces, physical distancing, hand washing and wearing a mask.

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.

This dataset reports the daily reported number of the 7-day moving average rates of Deaths involving COVID-19 by vaccination status and by age group. Learn how the Government of Ontario is helping to keep Ontarians safe during the 2019 Novel Coronavirus outbreak. Effective November 14, 2024 this page will no longer be updated. Information about COVID-19 and other respiratory viruses is available on Public Health Ontario’s interactive respiratory virus tool: https://www.publichealthontario.ca/en/Data-and-Analysis/Infectious-Disease/Respiratory-Virus-Tool Data includes: * Date on which the death occurred * Age group * 7-day moving average of the last seven days of the death rate per 100,000 for those not fully vaccinated * 7-day moving average of the last seven days of the death rate per 100,000 for those fully vaccinated * 7-day moving average of the last seven days of the death rate per 100,000 for those vaccinated with at least one booster ##Additional notes As of June 16, all COVID-19 datasets will be updated weekly on Thursdays by 2pm. As of January 12, 2024, data from the date of January 1, 2024 onwards reflect updated population estimates. This update specifically impacts data for the 'not fully vaccinated' category. On November 30, 2023 the count of COVID-19 deaths was updated to include missing historical deaths from January 15, 2020 to March 31, 2023. CCM is a dynamic disease reporting system which allows ongoing update to data previously entered. As a result, data extracted from CCM represents a snapshot at the time of extraction and may differ from previous or subsequent results. Public Health Units continually clean up COVID-19 data, correcting for missing or overcounted cases and deaths. These corrections can result in data spikes and current totals being different from previously reported cases and deaths. Observed trends over time should be interpreted with caution for the most recent period due to reporting and/or data entry lags. The data does not include vaccination data for people who did not provide consent for vaccination records to be entered into the provincial COVaxON system. This includes individual records as well as records from some Indigenous communities where those communities have not consented to including vaccination information in COVaxON. “Not fully vaccinated” category includes people with no vaccine and one dose of double-dose vaccine. “People with one dose of double-dose vaccine” category has a small and constantly changing number. The combination will stabilize the results. Spikes, negative numbers and other data anomalies: Due to ongoing data entry and data quality assurance activities in Case and Contact Management system (CCM) file, Public Health Units continually clean up COVID-19, correcting for missing or overcounted cases and deaths. These corrections can result in data spikes, negative numbers and current totals being different from previously reported case and death counts. Public Health Units report cause of death in the CCM based on information available to them at the time of reporting and in accordance with definitions provided by Public Health Ontario. The medical certificate of death is the official record and the cause of death could be different. Deaths are defined per the outcome field in CCM marked as “Fatal”. Deaths in COVID-19 cases identified as unrelated to COVID-19 are not included in the Deaths involving COVID-19 reported. Rates for the most recent days are subject to reporting lags All data reflects totals from 8 p.m. the previous day. This dataset is subject to change.