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.

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.

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.

Summary statistics for outcome and explanatory variables.

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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.

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 3.12 COVID-19 vaccine doses per capita through bilateral agreements, donations, and the COVAX initiative. Seychelles and Rwanda followed with 2.33 and 2.24 doses per capita, respectively.

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.

Indonesia Average Monthly Expenditure per Capita: Goods and Services: Health Preventive Cost: Children Under-Fives Immunization Cost data was reported at 1,158.000 IDR in 2018. This records an increase from the previous number of 330.000 IDR for 2017. Indonesia Average Monthly Expenditure per Capita: Goods and Services: Health Preventive Cost: Children Under-Fives Immunization Cost data is updated yearly, averaging 92.500 IDR from Dec 2003 (Median) to 2018, with 16 observations. The data reached an all-time high of 1,158.000 IDR in 2018 and a record low of 18.000 IDR in 2003. Indonesia Average Monthly Expenditure per Capita: Goods and Services: Health Preventive Cost: Children Under-Fives Immunization Cost data remains active status in CEIC and is reported by Central Bureau of Statistics. The data is categorized under Indonesia Premium Database’s Domestic Trade and Household Survey – Table ID.HC001: Average Monthly Expenditure per Capita.

Context

This dataset provides State-by-state data on United States COVID-19 vaccinations between 20 December of 2020 and 12 January of 2022. Data is taken daily by the United States Centers for Disease Control and Prevention

Columns

us_vaccinations File

- location: State name.

- date: date of the case.

- 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 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.

Data as of: May 18, 2021

As of April 26, 2023, around 81.3 percent of the U.S. population had received at least one dose of a COVID-19 vaccination. This statistic shows the percentage of the population in the United States who had been given a COVID-19 vaccination as of April 26, 2023, by state or territory.

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.

The global pneumococcal vaccines market is projected to have an average-paced CAGR of 4.1% during the forecast period. The current valuation of the market is US$ 8.9 Billion in 2023. The market value of the pneumococcal vaccines market is anticipated to surpass a market valuation of US$ 13.3 Billion by 2033. A historical market valuation of US$ 8.5 Billion has been recorded by the analysts of Future Market Insights for the concerned market during the base year.

Report Attribute	Details
Pneumococcal Vaccines Market Value (2023)	US$ 8.9 Billion
Pneumococcal Vaccines Market Anticipated Value (2033)	US$ 13.3 Billion
Pneumococcal Vaccines Projected Growth Rate (2023 to 2033)	4.1%

PCV in Infant Routine Immunization in 2023 Excel Against the Historical Market Scenario

Historical CAGR (2018 to 2022)	3.2%
Market Value in 2022	US$ 8.5 Billion

Forecast CAGR (2023 to 2033)	4.1%
Market Value in 2023	US$ 8.9 Million

Country-wise Insights

Region	North America
Country	United States of America
CAGR (2023 to 2033)	1.8%

Region	Europe
Country	United Kingdom
CAGR (2023 to 2033)	2.5%

Region	Europe
Country	Germany
CAGR (2023 to 2033)	2.9%

Region	Asia Pacific
Country	China
CAGR (2023 to 2033)	9.0%

Region	Asia Pacific
Country	India
CAGR (2023 to 2033)	9.2%

Indonesia Average Monthly Expenditure per Capita: Urban: Goods and Services: Health Preventive Cost: Children Under-Fives Immunization Cost data was reported at 1,339.000 IDR in 2018. This records an increase from the previous number of 411.000 IDR for 2017. Indonesia Average Monthly Expenditure per Capita: Urban: Goods and Services: Health Preventive Cost: Children Under-Fives Immunization Cost data is updated yearly, averaging 146.500 IDR from Dec 2003 (Median) to 2018, with 16 observations. The data reached an all-time high of 1,339.000 IDR in 2018 and a record low of 30.000 IDR in 2003. Indonesia Average Monthly Expenditure per Capita: Urban: Goods and Services: Health Preventive Cost: Children Under-Fives Immunization Cost data remains active status in CEIC and is reported by Central Bureau of Statistics. The data is categorized under Indonesia Premium Database’s Domestic Trade and Household Survey – Table ID.HC002: Average Monthly Expenditure per Capita: Urban.

Vaccination is considered as the main tool for the Global Control and Eradication Strategy for peste des petits ruminants (PPR), and the efficacity of the PPR-vaccine in conferring long-life immunity has been established. Despite this, previous studies asserted that vaccination can be expensive and consequently, the effectiveness of disease control may not necessarily translate to overall profit for farmers. Also, the consequences of PPR control on socioeconomic indicators like food and nutrition security at a macro-national level have not been explored thoroughly. Therefore, this study seeks to assess ex-ante the impact of PPR control strategies on farm-level profitability and the socioeconomic consequences concerning food and nutrition security at a national level in Senegal. A bi-level system dynamics model, compartmentalised into five modules consisting of integrated production-epidemiological, economics, disease control, marketing, and policy modules, was developed with the STELLA Architect software, validated, and simulated for 30 years at a weekly timestep. The model was parameterised with data from household surveys from pastoral areas in Northern Senegal and relevant existing data. Nine vaccination scenarios were examined considering different vaccination parameters (vaccination coverage, vaccine wastage, and the provision of government subsidies). The findings indicate that compared to a no-vaccination scenario, all the vaccination scenarios for both 26.5% (actual vaccination coverage) and 70% (expected vaccination coverage) resulted in statistically significant differences in the gross margin earnings and the potential per capita consumption for the supply of mutton and goat meat. At the prevailing vaccination coverage (with or without the provision of government subsidies), farm households will earn an average gross margin of $69.43 (annually) more than without vaccination, and the average per capita consumption for mutton and goat meat will increase by 1.13kg/person/year. When the vaccination coverage is increased to the prescribed threshold for PPR eradication (i.e., 70%), with or without the provision of government subsidies, the average gross margin earnings would be $72.23 annually and the per capita consumption will increase by 1.23kg/person/year compared to the baseline (without vaccination). This study’s findings offer an empirical justification for a sustainable approach to PPR eradication. The information on the socioeconomic benefits of vaccination can be promoted via sensitization campaigns to stimulate farmers’ uptake of the practice. This study can inform investment in PPR control.

• GDP  =  gross domestic product; I$  =  international dollars. Values represent the added cost of the 9-valent HPV vaccine at which the incremental cost-effectiveness ratio (compared to current 2- or 4-valent vaccines) would be equal to 1x per capita GDP in each country.† Base case scenario  =  some benefits to prevent cervical cancer with unidentifiable types and multiple infections, defined as a function of the prevalence of the five targeted HPV types relative to the prevalence of all non-16/18 types, with 37.4% cross-protection against non-vaccine types.Impact of discount rate on thresholds of incremental cost (I$) per vaccinated girl associated with the 9-valent vaccine*.

On March 10, 2023, the Johns Hopkins Coronavirus Resource Center ceased its collecting and reporting of global COVID-19 data. For updated cases, deaths, and vaccine data please visit: World Health Organization (WHO)For more information, visit the Johns Hopkins Coronavirus Resource Center.COVID-19 Trends MethodologyOur goal is to analyze and present daily updates in the form of recent trends within countries, states, or counties during the COVID-19 global pandemic. The data we are analyzing is taken directly from the Johns Hopkins University Coronavirus COVID-19 Global Cases Dashboard, though we expect to be one day behind the dashboard’s live feeds to allow for quality assurance of the data.DOI: https://doi.org/10.6084/m9.figshare.125529863/7/2022 - Adjusted the rate of active cases calculation in the U.S. to reflect the rates of serious and severe cases due nearly completely dominant Omicron variant.6/24/2020 - Expanded Case Rates discussion to include fix on 6/23 for calculating active cases.6/22/2020 - Added Executive Summary and Subsequent Outbreaks sectionsRevisions on 6/10/2020 based on updated CDC reporting. This affects the estimate of active cases by revising the average duration of cases with hospital stays downward from 30 days to 25 days. The result shifted 76 U.S. counties out of Epidemic to Spreading trend and no change for national level trends.Methodology update on 6/2/2020: This sets the length of the tail of new cases to 6 to a maximum of 14 days, rather than 21 days as determined by the last 1/3 of cases. This was done to align trends and criteria for them with U.S. CDC guidance. The impact is areas transition into Controlled trend sooner for not bearing the burden of new case 15-21 days earlier.Correction on 6/1/2020Discussion of our assertion of an abundance of caution in assigning trends in rural counties added 5/7/2020. Revisions added on 4/30/2020 are highlighted.Revisions added on 4/23/2020 are highlighted.Executive SummaryCOVID-19 Trends is a methodology for characterizing the current trend for places during the COVID-19 global pandemic. Each day we assign one of five trends: Emergent, Spreading, Epidemic, Controlled, or End Stage to geographic areas to geographic areas based on the number of new cases, the number of active cases, the total population, and an algorithm (described below) that contextualize the most recent fourteen days with the overall COVID-19 case history. Currently we analyze the countries of the world and the U.S. Counties. The purpose is to give policymakers, citizens, and analysts a fact-based data driven sense for the direction each place is currently going. When a place has the initial cases, they are assigned Emergent, and if that place controls the rate of new cases, they can move directly to Controlled, and even to End Stage in a short time. However, if the reporting or measures to curtail spread are not adequate and significant numbers of new cases continue, they are assigned to Spreading, and in cases where the spread is clearly uncontrolled, Epidemic trend.We analyze the data reported by Johns Hopkins University to produce the trends, and we report the rates of cases, spikes of new cases, the number of days since the last reported case, and number of deaths. We also make adjustments to the assignments based on population so rural areas are not assigned trends based solely on case rates, which can be quite high relative to local populations.Two key factors are not consistently known or available and should be taken into consideration with the assigned trend. First is the amount of resources, e.g., hospital beds, physicians, etc.that are currently available in each area. Second is the number of recoveries, which are often not tested or reported. On the latter, we provide a probable number of active cases based on CDC guidance for the typical duration of mild to severe cases.Reasons for undertaking this work in March of 2020:The popular online maps and dashboards show counts of confirmed cases, deaths, and recoveries by country or administrative sub-region. Comparing the counts of one country to another can only provide a basis for comparison during the initial stages of the outbreak when counts were low and the number of local outbreaks in each country was low. By late March 2020, countries with small populations were being left out of the mainstream news because it was not easy to recognize they had high per capita rates of cases (Switzerland, Luxembourg, Iceland, etc.). Additionally, comparing countries that have had confirmed COVID-19 cases for high numbers of days to countries where the outbreak occurred recently is also a poor basis for comparison.The graphs of confirmed cases and daily increases in cases were fit into a standard size rectangle, though the Y-axis for one country had a maximum value of 50, and for another country 100,000, which potentially misled people interpreting the slope of the curve. Such misleading circumstances affected comparing large population countries to small population counties or countries with low numbers of cases to China which had a large count of cases in the early part of the outbreak. These challenges for interpreting and comparing these graphs represent work each reader must do based on their experience and ability. Thus, we felt it would be a service to attempt to automate the thought process experts would use when visually analyzing these graphs, particularly the most recent tail of the graph, and provide readers with an a resulting synthesis to characterize the state of the pandemic in that country, state, or county.The lack of reliable data for confirmed recoveries and therefore active cases. Merely subtracting deaths from total cases to arrive at this figure progressively loses accuracy after two weeks. The reason is 81% of cases recover after experiencing mild symptoms in 10 to 14 days. Severe cases are 14% and last 15-30 days (based on average days with symptoms of 11 when admitted to hospital plus 12 days median stay, and plus of one week to include a full range of severely affected people who recover). Critical cases are 5% and last 31-56 days. Sources:U.S. CDC. April 3, 2020 Interim Clinical Guidance for Management of Patients with Confirmed Coronavirus Disease (COVID-19). Accessed online. Initial older guidance was also obtained online. Additionally, many people who recover may not be tested, and many who are, may not be tracked due to privacy laws. Thus, the formula used to compute an estimate of active cases is: Active Cases = 100% of new cases in past 14 days + 19% from past 15-25 days + 5% from past 26-49 days - total deaths. On 3/17/2022, the U.S. calculation was adjusted to: Active Cases = 100% of new cases in past 14 days + 6% from past 15-25 days + 3% from past 26-49 days - total deaths. Sources: https://www.cdc.gov/mmwr/volumes/71/wr/mm7104e4.htm https://covid.cdc.gov/covid-data-tracker/#variant-proportions If a new variant arrives and appears to cause higher rates of serious cases, we will roll back this adjustment. We’ve never been inside a pandemic with the ability to learn of new cases as they are confirmed anywhere in the world. After reviewing epidemiological and pandemic scientific literature, three needs arose. We need to specify which portions of the pandemic lifecycle this map cover. The World Health Organization (WHO) specifies six phases. The source data for this map begins just after the beginning of Phase 5: human to human spread and encompasses Phase 6: pandemic phase. Phase six is only characterized in terms of pre- and post-peak. However, these two phases are after-the-fact analyses and cannot ascertained during the event. Instead, we describe (below) a series of five trends for Phase 6 of the COVID-19 pandemic.Choosing terms to describe the five trends was informed by the scientific literature, particularly the use of epidemic, which signifies uncontrolled spread. The five trends are: Emergent, Spreading, Epidemic, Controlled, and End Stage. Not every locale will experience all five, but all will experience at least three: emergent, controlled, and end stage.This layer presents the current trends for the COVID-19 pandemic by country (or appropriate level). There are five trends:Emergent: Early stages of outbreak. Spreading: Early stages and depending on an administrative area’s capacity, this may represent a manageable rate of spread. Epidemic: Uncontrolled spread. Controlled: Very low levels of new casesEnd Stage: No New cases These trends can be applied at several levels of administration: Local: Ex., City, District or County – a.k.a. Admin level 2State: Ex., State or Province – a.k.a. Admin level 1National: Country – a.k.a. Admin level 0Recommend that at least 100,000 persons be represented by a unit; granted this may not be possible, and then the case rate per 100,000 will become more important.Key Concepts and Basis for Methodology: 10 Total Cases minimum threshold: Empirically, there must be enough cases to constitute an outbreak. Ideally, this would be 5.0 per 100,000, but not every area has a population of 100,000 or more. Ten, or fewer, cases are also relatively less difficult to track and trace to sources. 21 Days of Cases minimum threshold: Empirically based on COVID-19 and would need to be adjusted for any other event. 21 days is also the minimum threshold for analyzing the “tail” of the new cases curve, providing seven cases as the basis for a likely trend (note that 21 days in the tail is preferred). This is the minimum needed to encompass the onset and duration of a normal case (5-7 days plus 10-14 days). Specifically, a median of 5.1 days incubation time, and 11.2 days for 97.5% of cases to incubate. This is also driven by pressure to understand trends and could easily be adjusted to 28 days. Source

Introduction: Decisions about prevention of and response to Ebola outbreaks require an understanding of the macroeconomic implications of these interventions. Prophylactic vaccines hold promise to mitigate the negative economic impacts of infectious disease outbreaks. The objective of this study was to evaluate the relationship between outbreak size and economic impact among countries with recorded Ebola outbreaks and to quantify the hypothetical benefits of prophylactic Ebola vaccination interventions in these outbreaks.

Methods: The synthetic control method was used to estimate the causal impacts of Ebola outbreaks on per capita gross domestic product (GDP) of five countries in sub-Saharan Africa that have previously experienced Ebola outbreaks between 2000 and 2016, where no vaccines were deployed. Using illustrative assumptions about vaccine coverage, efficacy, and protective immunity, the potential economic benefits of prophylactic Ebola vaccination were estimated using the number of cases in an outbreak as a key indicator.

Results: The impact of Ebola outbreaks on the macroeconomy of the selected countries led to a decline in GDP of up to 36%, which was greatest in the third year after the onset of each outbreak and increased exponentially with the size of outbreak (i.e., number of reported cases). Over three years, the aggregate loss estimated for Sierra Leone from its 2014-2016 outbreak is estimated at 16.1 billion International$. Prophylactic vaccination could have prevented up to 89% of an outbreak’s negative impact on GDP, reducing the outbreak’s impact to as little as 1.6% of GDP lost.

Conclusion: This study supports the case that macroeconomic returns are associated with prophylactic Ebola vaccination. Our findings support recommendations for prophylactic Ebola vaccination as a core component of prevention and response measures for global health security.

Between January 1, 2021 and April 30, 2022 the death rate due to COVID-19 in the United States was about 2,487 per one million population. An analysis published in May 2022 found that if 100 percent of the population in the United States had been vaccinated at this time then the death rate over this period would have been around 1,237 per one million population. It was estimated that a 100 percent vaccination rate could have prevented 318,981 of 641,305 total deaths reported over this period. As of May 2022, around 66 percent of the U.S. population had been fully vaccinated against COVID-19. This table shows the actual death rate due to COVID-19 in the United States between January 2021 and April 2022 compared to the death rate if 100 percent of the population had been vaccinated.