Vaccination rates among one-year-olds have risen drastically in the past four decades, with global coverage for some of the most important vaccines increasing from below twenty percent in 1980 to above eighty percent in 2021. Several vaccines introduced on a larger scale in the 1990s, such as the Hepatitis B vaccine, have increased from just one percent coverage to well over two thirds coverage today. As many infants receive multiple vaccines at one time, or as barriers to healthcare access are lifted, this has meant that global coverage trends have been fairly similar for the most common vaccines, and that coverage for newly developed vaccines has grown relatively quickly (such as the Hepatitis B and Inactivated Polio vaccines). Recent backsliding The COVID-19 pandemic marked the first time in recent history where coverage among one year olds dropped for multiple vaccines. In some cases, global coverage fell by as much as five or six percent for vaccines including diptheria/pertussus/tetanus, hepatitus B, measles, and polio. This backslide has been attributed to a variety of factors, such as weakened healthcare systems in less developed regions, the spread of misinformation surrounding vaccines, disruptions due to containment measures, supply chain issues, and the diversion of medical resources. It had been hoped that 2020 would be an anomaly, and that figures would return to their previous trajectory in 2021, but rising malnutrition and and weaker food supply to the poorest regions has exacerbated this further.

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 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 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.

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...

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.

Note: In these datasets, a person is defined as up to date if they have received at least one dose of an updated COVID-19 vaccine. The Centers for Disease Control and Prevention (CDC) recommends that certain groups, including adults ages 65 years and older, receive additional doses.

On 6/16/2023 CDPH replaced the booster measures with a new “Up to Date” measure based on CDC’s new recommendations, replacing the primary series, boosted, and bivalent booster metrics The definition of “primary series complete” has not changed and is based on previous recommendations that CDC has since simplified. A person cannot complete their primary series with a single dose of an updated vaccine. Whereas the booster measures were calculated using the eligible population as the denominator, the new up to date measure uses the total estimated population. Please note that the rates for some groups may change since the up to date measure is calculated differently than the previous booster and bivalent measures.

This data is from the same source as the Vaccine Progress Dashboard at https://covid19.ca.gov/vaccination-progress-data/ which summarizes vaccination data at the county level by county of residence. Where county of residence was not reported in a vaccination record, the county of provider that vaccinated the resident is included. This applies to less than 1% of vaccination records. The sum of county-level vaccinations does not equal statewide total vaccinations due to out-of-state residents vaccinated in California.

These data do not include doses administered by the following federal agencies who received vaccine allocated directly from CDC: Indian Health Service, Veterans Health Administration, Department of Defense, and the Federal Bureau of Prisons.

Totals for the Vaccine Progress Dashboard and this dataset may not match, as the Dashboard totals doses by Report Date and this dataset totals doses by Administration Date. Dose numbers may also change for a particular Administration Date as data is updated.

Previous updates:

• On March 3, 2023, with the release of HPI 3.0 in 2022, the previous equity scores have been updated to reflect more recent community survey information. This change represents an improvement to the way CDPH monitors health equity by using the latest and most accurate community data available. The HPI uses a collection of data sources and indicators to calculate a measure of community conditions ranging from the most to the least healthy based on economic, housing, and environmental measures.

• Starting on July 13, 2022, the denominator for calculating vaccine coverage has been changed from age 5+ to all ages to reflect new vaccine eligibility criteria. Previously the denominator was changed from age 16+ to age 12+ on May 18, 2021, then changed from age 12+ to age 5+ on November 10, 2021, to reflect previous changes in vaccine eligibility criteria. The previous datasets based on age 16+ and age 5+ denominators have been uploaded as archived tables.

• Starting on May 29, 2021 the methodology for calculating on-hand inventory in the shipped/delivered/on-hand dataset has changed. Please see the accompanying data dictionary for details. In addition, this dataset is now down to the ZIP code level.

View daily updates and historical trends for World Coronavirus Vaccination Rate: Any Dosage. Source: Our World in Data. Track economic data with YCharts a…

The number of COVID-19 vaccination doses administered per 100 people in the World rose to 168 as of Oct 27 2023. This dataset includes a chart with historical data for World Coronavirus Vaccination Rate.

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...

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

France FR: Immunization: Measles: % of Children Aged 12-23 Months data was reported at 90.000 % in 2017. This stayed constant from the previous number of 90.000 % for 2016. France FR: Immunization: Measles: % of Children Aged 12-23 Months data is updated yearly, averaging 84.000 % from Dec 1983 (Median) to 2017, with 35 observations. The data reached an all-time high of 91.000 % in 2015 and a record low of 15.000 % in 1983. France FR: Immunization: Measles: % of Children Aged 12-23 Months data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s France – Table FR.World Bank.WDI: Health Statistics. Child immunization, measles, measures the percentage of children ages 12-23 months who received the measles vaccination before 12 months or at any time before the survey. A child is considered adequately immunized against measles after receiving one dose of vaccine.; ; WHO and UNICEF (http://www.who.int/immunization/monitoring_surveillance/en/).; Weighted average;

As of July 4, 2022, Africa had administered around 41 doses of coronavirus (COVID-19) vaccines per 100 people. The vaccination rate in the continent was far slower than the world average, measured at 154 vaccines per 100 individuals on the same date. The vaccination in Africa has also been marked by a striking divide between countries. Africa started receiving vaccine supplies under the WHO-backed Covax facility in February 2021. Some African countries purchased additional doses, while others benefited from bilateral donations.

Even though they are important determinants for increasing vaccination rates in advanced and developing nations alike, maternal capacity and decisional authority have not been fully elucidated in diverse countries and cultural spheres. This study examined the effects of South Korean, Chinese, and Japanese mothers’ health literacy, self-efficacy, mass media use, and decisional authority on their children’s vaccination after adjustment for their socioeconomic statuses. Computer-assisted web interviews were conducted with married women in their 20s-40s of South Korean, Chinese, or Japanese nationality (n = 1,571). Dependent variables were generated for the following four vaccinations: BCG, diphtheria+pertussis+tetanus (DPT), poliomyelitis (polio), and measles. For statistical processing, cases where all four types of vaccines had been recorded were scored as 1 and other cases were processed as 0. According to the results of the pooled model, we found that for East Asian mothers, decisional authority, self-efficacy, and health literacy all increased the likelihood that they would vaccinate their children. Furthermore, women who searched for health information through media such as the radio were more likely to vaccinate their children. However, when elaborate analyses were conducted by country, there were considerable differences in those characteristics by country. Therefore, this study showed that it is necessary to establish locally tailored strategies in order to raise vaccination rates in the Global Vaccine Action Plan. This study also showed that social contexts must be taken into consideration in order to raise vaccination rates.

View daily updates and historical trends for Brazil Coronavirus Full Vaccination Rate. Source: Our World in Data. Track economic data with YCharts analyti…

Objectives: Disease control is important to limit the social, economic and health effects of COVID-19 and reduce the risk of novel variants emerging. Evidence suggests vaccines are less effective against the Omicron variant, but their impact on disease control is unclear.Methods: We used a longitudinal fixed effects Poisson regression model to assess the impact of vaccination on COVID-19 case rates across 32 countries in Europe from 13th October to 01st January 2022. We controlled for country and time fixed effects and the severity of public health restrictions.Results: Full vaccination coverage increased by 4.2%, leading to a 54% reduction in case rates across Europe (p < 0.001). This protection decreased over time but remained significant at 5 weeks after the detection of Omicron. Mean booster vaccination rates increased from 2.71% to 24.5% but provided no significant additional benefit. For every one-unit increase in the severity of public health restrictions, case rates fell by a further 2% (p = 0.019).Conclusion: Full vaccination significantly limited the spread of COVID-19 and blunted the impact of the Omicron variant, despite becoming less useful over time.

This dataset merges three distinct data sources to explore the relationship between COVID-19 death rates, vaccination efforts, and public sentiment on Twitter from December 25, 2020 to March 29, 2022. It includes 2,000 cleaned rows with 16 variables, created by combining global health statistics and social media sentiment data.

Sources & Variables:

1. COVID-19 Deaths Data (scraped from Worldometer - COVID-19 Deaths via BeautifulSoup):

   • Date: Date of record
   • daily_increase_percent: % change in deaths from previous day
   • Season: Derived from date (Winter, Spring, Summer, Fall)

2. Tweet Sentiment Data : COVID Vaccine Tweets Dataset

   • Date: Tweet timestamp
   • text_sentiment: Sentiment label (positive, neutral, negative) from NLTK’s SentimentIntensityAnalyzer
   • user_verified: Whether the user is verified
   • user_since_days: Age of the Twitter account (in days)
   • country: Cleaned user location

3. Vaccination Data : Vaccination Dataset

   • Date: Date of record
   • total_vaccinations_per_hundred: Doses per 100 people
   • daily_vaccinations: Daily dose count
   • vaccine_group: Grouped vaccine type (e.g., mRNA, Viral Vector)
   • country: Country name

Preprocessing Summary:

• Merged by Date and country
• Cleaned invalid country names (e.g., “moon”, “nowhere”)
• Standardized all datetime formats
• Removed entries with missing or unreliable values
• Created derived variables: Season, user_since_days, vaccine_group

This dataset was used in a final data science project to:

• Classify public sentiment toward vaccines using health indicators
• Predict daily COVID-19 death counts using sentiment and vaccination data

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 statistic displays the percentage of the world population that has been vaccinated with select routine vaccinations as of 2022. According to the data, globally, just ** percent of people have had a last Rota vaccine against the Rotavirus. Rotavirus is responsible for an inflammation of the intestines and stomach and causes severe gastrointestinal and diarrheal disease. Vaccination success worldwide All around the world, vaccinations have been effective in reducing the number of cases and deaths of various communicable diseases since the introduction of global vaccination programs in the 1970’s. For example, between 2000 and 2021, millions of deaths due to measles have been averted all over the globe. The final aim of vaccination is to eradicate the disease entirely, as is the case with smallpox: no cases have been reported since 1978. Under-immunized groups Despite the success of immunization programs, there are still groups lacking the recommended vaccinations; this is often due to a lack of access or resources within a country or region, although under-immunization can also be a result of hesitancy due to personal beliefs. Individual rights involving compulsory vaccinations has also remained a hot topic over the years- for example, support for government-required childhood vaccinations has decreased in the U.S. since 1991. In order to further grow vaccination coverage, targeted strategies are needed for under-immunized and vaccine-hesitant groups using context-specific interventions to increase and monitor immunization rates.