Data for CDC’s COVID Data Tracker site on Rates of COVID-19 Cases and Deaths by Vaccination Status. Click 'More' for important dataset description and footnotes

Dataset and data visualization details: These data were posted on October 21, 2022, archived on November 18, 2022, and revised on February 22, 2023. These data reflect cases among persons with a positive specimen collection date through September 24, 2022, and deaths among persons with a positive specimen collection date through September 3, 2022.

Vaccination status: A person vaccinated with a primary series had SARS-CoV-2 RNA or antigen detected on a respiratory specimen collected ≥14 days after verifiably completing the primary series of an FDA-authorized or approved COVID-19 vaccine. An unvaccinated person had SARS-CoV-2 RNA or antigen detected on a respiratory specimen and has not been verified to have received COVID-19 vaccine. Excluded were partially vaccinated people who received at least one FDA-authorized vaccine dose but did not complete a primary series ≥14 days before collection of a specimen where SARS-CoV-2 RNA or antigen was detected. Additional or booster dose: A person vaccinated with a primary series and an additional or booster dose had SARS-CoV-2 RNA or antigen detected on a respiratory specimen collected ≥14 days after receipt of an additional or booster dose of any COVID-19 vaccine on or after August 13, 2021. For people ages 18 years and older, data are graphed starting the week including September 24, 2021, when a COVID-19 booster dose was first recommended by CDC for adults 65+ years old and people in certain populations and high risk occupational and institutional settings. For people ages 12-17 years, data are graphed starting the week of December 26, 2021, 2 weeks after the first recommendation for a booster dose for adolescents ages 16-17 years. For people ages 5-11 years, data are included starting the week of June 5, 2022, 2 weeks after the first recommendation for a booster dose for children aged 5-11 years. For people ages 50 years and older, data on second booster doses are graphed starting the week including March 29, 2022, when the recommendation was made for second boosters. Vertical lines represent dates when changes occurred in U.S. policy for COVID-19 vaccination (details provided above). Reporting is by primary series vaccine type rather than additional or booster dose vaccine type. The booster dose vaccine type may be different than the primary series vaccine type. ** Because data on the immune status of cases and associated deaths are unavailable, an additional dose in an immunocompromised person cannot be distinguished from a booster dose. This is a relevant consideration because vaccines can be less effective in this group. Deaths: A COVID-19–associated death occurred in a person with a documented COVID-19 diagnosis who died; health department staff reviewed to make a determination using vital records, public health investigation, or other data sources. Rates of COVID-19 deaths by vaccination status are reported based on when the patient was tested for COVID-19, not the date they died. Deaths usually occur up to 30 days after COVID-19 diagnosis. Participating jurisdictions: Currently, these 31 health departments that regularly link their case surveillance to immunization information system data are included in these incidence rate estimates: Alabama, Arizona, Arkansas, California, Colorado, Connecticut, District of Columbia, Florida, Georgia, Idaho, Indiana, Kansas, Kentucky, Louisiana, Massachusetts, Michigan, Minnesota, Nebraska, New Jersey, New Mexico, New York, New York City (New York), North Carolina, Philadelphia (Pennsylvania), Rhode Island, South Dakota, Tennessee, Texas, Utah, Washington, and West Virginia; 30 jurisdictions also report deaths among vaccinated and unvaccinated people. These jurisdictions represent 72% of the total U.S. population and all ten of the Health and Human Services Regions. Data on cases

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.

Between January 1, 2021 and May 31, 2022, there were approximately 30.6 thousand deaths involving COVID-19 among 80 to 89 year olds in England, with over 14 thousand deaths occurring among unvaccinated people in this age group. Across all the age groups in the provided time interval, deaths involving COVID-19 among the unvaccinated population was around double the amount of people who received at least two doses of a vaccine. For further information about the COVID-19 pandemic, please visit our dedicated Facts and Figures page.

As of March 10, 2023, there have been 1.1 million deaths related to COVID-19 in the United States. There have been 101,159 deaths in the state of California, more than any other state in the country – California is also the state with the highest number of COVID-19 cases.

The vaccine rollout in the U.S. Since the start of the pandemic, the world has eagerly awaited the arrival of a safe and effective COVID-19 vaccine. In the United States, the immunization campaign started in mid-December 2020 following the approval of a vaccine jointly developed by Pfizer and BioNTech. As of March 22, 2023, the number of COVID-19 vaccine doses administered in the U.S. had reached roughly 673 million. The states with the highest number of vaccines administered are California, Texas, and New York.

Vaccines achieved due to work of research groups Chinese authorities initially shared the genetic sequence to the novel coronavirus in January 2020, allowing research groups to start studying how it invades human cells. The surface of the virus is covered with spike proteins, which enable it to bind to human cells. Once attached, the virus can enter the cells and start to make people ill. These spikes were of particular interest to vaccine manufacturers because they hold the key to preventing viral entry.

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.

Age-standardised mortality rates for deaths involving coronavirus (COVID-19), non-COVID-19 deaths and all deaths by vaccination status, broken down by age group.

As of May 2, 2023, the outbreak of the coronavirus disease (COVID-19) had spread to almost every country in the world, and more than 6.86 million people had died after contracting the respiratory virus. Over 1.16 million of these deaths occurred in the United States.

Waves of infections Almost every country and territory worldwide have been affected by the COVID-19 disease. At the end of 2021 the virus was once again circulating at very high rates, even in countries with relatively high vaccination rates such as the United States and Germany. As rates of new infections increased, some countries in Europe, like Germany and Austria, tightened restrictions once again, specifically targeting those who were not yet vaccinated. However, by spring 2022, rates of new infections had decreased in many countries and restrictions were once again lifted.

What are the symptoms of the virus? It can take up to 14 days for symptoms of the illness to start being noticed. The most commonly reported symptoms are a fever and a dry cough, leading to shortness of breath. The early symptoms are similar to other common viruses such as the common cold and flu. These illnesses spread more during cold months, but there is no conclusive evidence to suggest that temperature impacts the spread of the SARS-CoV-2 virus. Medical advice should be sought if you are experiencing any of these symptoms.

Data for CDC’s COVID Data Tracker site on Rates of COVID-19 Cases and Deaths by Updated (Bivalent) Booster Status. Click 'More' for important dataset description and footnotes

Webpage: https://covid.cdc.gov/covid-data-tracker/#rates-by-vaccine-status

Dataset and data visualization details:

These data were posted and archived on May 30, 2023 and reflect cases among persons with a positive specimen collection date through April 22, 2023, and deaths among persons with a positive specimen collection date through April 1, 2023. These data will no longer be updated after May 2023.

Vaccination status: A person vaccinated with at least a primary series had SARS-CoV-2 RNA or antigen detected on a respiratory specimen collected ≥14 days after verifiably completing the primary series of an FDA-authorized or approved COVID-19 vaccine. An unvaccinated person had SARS-CoV-2 RNA or antigen detected on a respiratory specimen and has not been verified to have received COVID-19 vaccine. Excluded were partially vaccinated people who received at least one FDA-authorized vaccine dose but did not complete a primary series ≥14 days before collection of a specimen where SARS-CoV-2 RNA or antigen was detected. A person vaccinated with a primary series and a monovalent booster dose had SARS-CoV-2 RNA or antigen detected on a respiratory specimen collected ≥14 days after verifiably receiving a primary series of an FDA-authorized or approved vaccine and at least one additional dose of any monovalent FDA-authorized or approved COVID-19 vaccine on or after August 13, 2021. (Note: this definition does not distinguish between vaccine recipients who are immunocompromised and are receiving an additional dose versus those who are not immunocompromised and receiving a booster dose.) A person vaccinated with a primary series and an updated (bivalent) booster dose had SARS-CoV-2 RNA or antigen detected in a respiratory specimen collected ≥14 days after verifiably receiving a primary series of an FDA-authorized or approved vaccine and an additional dose of any bivalent FDA-authorized or approved vaccine COVID-19 vaccine on or after September 1, 2022. (Note: Doses with bivalent doses reported as first or second doses are classified as vaccinated with a bivalent booster dose.) People with primary series or a monovalent booster dose were combined in the “vaccinated without an updated booster” category.

Deaths: A COVID-19–associated death occurred in a person with a documented COVID-19 diagnosis who died; health department staff reviewed to make a determination using vital records, public health investigation, or other data sources. Per the interim guidance of the Council of State and Territorial Epidemiologists (CSTE), this should include persons whose death certificate lists COVID-19 disease or SARS-CoV-2 as the underlying cause of death or as a significant condition contributing to death. Rates of COVID-19 deaths by vaccination status are primarily reported based on when the patient was tested for COVID-19. In select jurisdictions, deaths are included that are not laboratory confirmed and are reported based on alternative dates (i.e., onset date for most; or date of death or report date, where onset date is unavailable). Deaths usually occur up to 30 days after COVID-19 diagnosis.

Participating jurisdictions: Currently, these 24 health departments that regularly link their case surveillance to immunization information system data are included in these incidence rate estimates: Alabama, Arizona, Colorado, District of Columbia, Georgia, Idaho, Indiana, Kansas, Kentucky, Louisiana, Massachusetts, Michigan, Minnesota, Nebraska, New Jersey, New Mexico, New York, New York City (NY), North Carolina, Rhode Island, Tennessee, Texas, Utah, and West Virginia; 23 jurisdictions also report deaths among vaccinated and unvaccinated people. These jurisdictions represent 48% of the total U.S. population and all ten of the Health and Human Services Regions. This list will be

The New York Times is releasing a series of data files with cumulative counts of coronavirus cases in the United States, at the state and county level, over time. We are compiling this time series data from state and local governments and health departments in an attempt to provide a complete record of the ongoing outbreak.

Since the first reported coronavirus case in Washington State on Jan. 21, 2020, The Times has tracked cases of coronavirus in real time as they were identified after testing. Because of the widespread shortage of testing, however, the data is necessarily limited in the picture it presents of the outbreak.

We have used this data to power our maps and reporting tracking the outbreak, and it is now being made available to the public in response to requests from researchers, scientists and government officials who would like access to the data to better understand the outbreak.

The data begins with the first reported coronavirus case in Washington State on Jan. 21, 2020. We will publish regular updates to the data in this repository.

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. 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.

IntroductionThe end of the coronavirus disease 2019 (COVID-19) pandemic has been declared by the World Health Organization on May 5, 2023. Several vaccines were developed, and new data is being published about their effectiveness. However, the clinical trials for the vaccines were performed before the Omicron variant appeared and there are population groups where vaccine effectiveness still needs to be tested. The overarching goal of the present study was to analyze the effects of COVID-19 vaccination before and after the Omicron variant in patients considering comorbidities in a population from Nuevo Leon, Mexico.MethodsEpidemiological COVID-19 data from the Mexican Social Security Institute were collected from 67 hospitals located in northeastern Mexico, from July 2020 to May 2023, and a total of 669,393 cases were compiled, 255,819 reported a SARS-CoV-2 positive reverse transcription quantitative polymerase chain reaction (RT-qPCR) test or a positive COVID-19 antigen rapid test.ResultsBefore Omicron (BO, 2020-2021), after 14 days of two doses of COVID-19 vaccine, BNT162b2 and ChAdOx1 vaccines were effective against infection in non-comorbid and all comorbid subgroups, whereas after Omicron (AO, 2022- 2023) there was no significant effectiveness against infection with none of the vaccines. Regarding hospitalization BO, BNT162b2, ChAdOx1, CoronaVac and mRNA-1273 significantly protected non-comorbid patients whereas BNT162b2, ChAdOx1, and mRNA-1273, protected all comorbid subgroups against hospitalization. AO, BNT162b2, ChAdOx1, CoronaVac and mRNA-1273 were effective against hospitalization in non-comorbid patients whereas for most comorbid subgroups BNT162b2, ChAdOx1 and CoronaVac were effective against hospitalization. Non-comorbid patients were protected against death as an outcome of COVID-19 during the BO period with most vaccines whereas a reduction in effectiveness was observed AO with mRNA-1273 vaccines in patients with hypertension, and diabetes mellitus.DiscussionBO, COVID-19 vaccines were effective against infection, hospitalization, and death whereas AO, COVID-19 vaccines failed to protect the population from COVID-19 infection. A varying effectiveness against hospitalization and death is observed AO.

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

According to Cognitive Market Research, the global Emerging Cancer Vaccines market size is USD XX million in 2024 and will expand at a compound annual growth rate (CAGR) of 12.50% from 2024 to 2031.

North America held the major market of more than 40% of the global revenue with a market size of USD XX million in 2024 and will grow at a compound annual growth rate (CAGR) of 10.7% from 2024 to 2031.
Europe accounted for a share of over 30% of the global market size of USD XX million.
Asia Pacific held the market of around 23% of the global revenue with a market size of USD XX million in 2024 and will grow at a compound annual growth rate (CAGR) of 14.5% from 2024 to 2031.
Latin America market of more than 5% of the global revenue with a market size of USD XX million in 2024 and will grow at a compound annual growth rate (CAGR) of 11.9% from 2024 to 2031.
Middle East and Africa held the major market of around 2% of the global revenue with a market size of USD XX million in 2024 and will grow at a compound annual growth rate (CAGR) of 12.2% from 2024 to 2031.
The Genetic vaccines held the highest Emerging Cancer Vaccines market revenue share in 2024

Market Dynamics of Emerging Cancer Vaccines Market

Key Drivers for Emerging Cancer Vaccines Market

Increasing Prevalence of Cancer to Propel the Market Revenue Growth

One of the major factor that propel the emerging cancer market is rising prevalence of cancer across the globe as the traditional therapy such as chemotherapy and radiation therapy often have a significant side-effets. This side effects turn medical personnel for the R&D of cancer vaccines, which anticipated to drive the penetration of market revenue growth. For instance, according to the estimates by American Cancer Society, around 20 million cancer cases were newly diagnosed and 9.7 million people died from the cancer globally in 2022. This number of cancer cases is projected to grow 35 million by 2050. Thus, the aforementioned stats support the market growth.

Rising Clinical Trials to Boost Market Growth

The growing clinical trials are expected to propel the market growth during the forecast period. For instance, in December 2023, nixa Biosciences, Inc., a biotechnology business that specializes in cancer therapy and prevention, recently released updated and fresh positive data from their breast cancer vaccine's Phase 1 clinical study. The trial is being carried out with financial support from a grant from the U.S. Department of Defense in association with Cleveland Clinic.G. Thomas Budd, M.D., a staff physician at Cleveland Clinic Cancer Institute and the study's principal investigator, presented the data at the 2023 San Antonio Breast Cancer Symposium in a poster titled "Phase I Trial of alpha-lactalbumin vaccine in high-risk operable triple negative breast cancer (TNBC) and patients at high genetic risk for TNBC.

Source: https://www.prnewswire.com/news-releases/anixa-biosciences-and-cleveland-clinic-present-positive-new-data-from-phase-1-study-of-breast-cancer-vaccine-302007568.html.

Restraint Factor for the Emerging Cancer Vaccines Market

Complexity of Cancer Immunology to Limit the Market Growth

The complexity of cancer immunology is expected to hamper the market growth during the forecast period. As cancer disease is complex and heterogeneous in nature, and immune systems response to these disease is also very complex in nature. The R&D of the effective cancer vaccines demanding a good knowledge of tumor biology, immune evasion mechanisms, and the interplay between cancer cells and the immune system. The complex nature cancer immunology is the major challenge in identifying suitable vaccine targets and optimizing vaccine design, which may impede the development of theraupeutic treatment of cancer such as vaccines.

Impact of Covid-19 on the Emerging Cancer Vaccines Market

The COVID-19 pandemic had a mix impact on the emerging cancer vaccines market. The mRNA based vaccines manufactured by the global company such as Pfizer-BioNTech and Moderna, has brought attention to the potential of mRNA technology in the production of vaccines. As the same technology is used to modified target cancer-specific antigens, which has increased demand and funding for mRNA-based cancer vaccines. Furthermore, the COVID-19 has raised awareness of the significance of immunotherapy and vaccinations in fight aginst various disease including cancer, in...

IntroductionIn Hungary, the HUN-VE 3 study determined the comparative effectiveness of various primary and booster vaccination strategies during the Delta COVID-19 wave. That study included more than 8 million 18-100-year-old individuals from the beginning of the pandemic. Immunocompromised (IC) individuals have increased risk for COVID-19 and disease course might be more severe in them. In this study, we wished to estimate the risk of SARS-CoV-2 infection and COVID-19 related death in IC individuals compared to healthy ones and the effectiveness of the BNT162b2 vaccine by reassessing HUN-VE 3 data.Patients and methodsAmong the 8,087,988 individuals undergoing follow-up from the onset of the pandemic in the HUN-VE 3 cohort, we selected all the 263,116 patients with a diagnosis corresponding with IC and 6,128,518 controls from the second wave, before vaccinations started. The IC state was defined as two occurrences of corresponding ICD-10 codes in outpatient or inpatient claims data since 1 January, 2013. The control group included patients without chronic diseases. The data about vaccination, SARS-CoV-2 infection and COVID-19 related death were obtained from the National Public Health Center (NPHC) during the Delta wave. Cases of SARS-CoV-2 infection were reported on a daily basis using a centralized system via the National Public Health Center (NPHC).ResultsOut of the 263,116 IC patients 12,055 patients (4.58%) and out of the 6,128,518 healthy controls 202,163 (3.30%) acquired SARS-CoV-2 infection. Altogether 436 IC patients and 2141 healthy controls died in relation to COVID-19. The crude incidence rate ratio (IRR) of SARS-CoV-2 infection was 1.40 (95%CI: 1.37-1.42) comparing IC patients to healthy controls. The crude mortality rate ratio was 4.75 (95%CI: 4.28-5.27). With respect to SARS-CoV-2 infection, interestingly, the BNT162b2 vaccine was more effective in IC patients compared to controls. Primary vaccine effectiveness (VE) was higher in IC patients compared to controls and the booster restored VE after waning. VE regarding COVID-19 related death was less in IC patients compared to healthy individuals. Booster vaccination increased VE against COVID-19-related death in both IC patients and healthy controls.ConclusionThere is increased risk of SARS-CoV-2 infection and COVID-19 related mortality in IC patient. Moreover, booster vaccination using BNT162b2 might restore impaired VE in these individuals.

Between the beginning of January 2020 and June 14, 2023, of the 1,134,641 deaths caused by COVID-19 in the United States, around 307,169 had occurred among those aged 85 years and older. This statistic shows the number of coronavirus disease 2019 (COVID-19) deaths in the U.S. from January 2020 to June 2023, by age.

In 2022, around 1,029 petitions were filed with the United States National Injury Compensation Program (VICP) seeking compensation for injury or death caused by vaccines. However, just because a petition was filed seeking compensation for injury or death due to a vaccination does not mean that compensation was awarded. Over half of all such petitions filed in the U.S. since 1988 have been dismissed, and in 60 percent of cases in which compensation was awarded it was still not determined whether the alleged vaccine caused the alleged injury.

The impact of vaccinations Vaccinations in the United States have had a significant impact on infectious diseases. For example, as of 2017, there are only about 120 new cases of measles per year, compared to over half a million annual cases before the use of vaccination. Vaccinations in the U.S. have also greatly decreased the number of annual cases of hepatitis A and B, rubella, and tetanus.

COVID-19 vaccination hesitancy Vaccine hesitancy is a persistent issue in the United States. The issue became especially pertinent during the COVID-19 pandemic in which many people in the United States expressed reluctance to getting a COVID-19 vaccination. In December 2020, 59 percent of adults in the United States who stated they would definitely not or probably not get a COVID-19 vaccine said so because they were worried about possible side effects, while 55 percent said they probably wouldn’t get a COVID-19 vaccination because they do not trust the government to make sure the vaccine is safe and effective. Shockingly, one survey found that even 29 percent of health care workers stated they would probably or definitely not get a COVID-19 vaccine.

ObjectivesThe objective of this study is to estimate the effectiveness of COVID-19 vaccines in people treated within the social security system whose vaccination status was reported to the epidemiological surveillance system.Study designCase-control study.MethodsThis was a case-control study conducted. The records of individuals with suspected cases of COVID-19 registered in the epidemiological surveillance system between February 1 and June 30, 2021, were studied. RT–qPCR was performed to determine SARS-CoV-2 infection; those with a positive result were considered cases, and those with a negative result were considered controls. The ratio between cases and controls was 1:1.3. The crude and adjusted vaccine effectiveness was considered the prevention of symptomatic infection and death and calculated as the difference between the dose and the risk, with a survival analysis among vaccinated people.ResultsA total of 94,416 individuals were included, of whom 40,192 were considered cases and 54,224 controls; 3,781 (4.00%) had been vaccinated against COVID-19. Vaccination also proved to be a protective factor against COVID-19, especially in the population who received a second dose (OR = 0.31; 95% CI 0.28–0.35). With the application of the vaccine, there was a protective effect against mortality (OR = 0.76; 95% CI 0.66–0.87). Disease prevention was higher for the BNT162-2 mRNA vaccine (82%) followed by the ChAdOx1 vaccine (33%). In the survival analysis, vaccination provided a protective effect.ConclusionsThere was a positive impact of vaccines for the prevention of symptomatic COVID-19, with a second dose generating greater efficacy and a reduction in deaths.

President Trump's haphazard decision to delegate Covid-19 vaccine distribution to US states set up conditions for evaluating state-level vaccine prioritization policies using a quasi-experimental design. Despite agreement on the goal, state-formulated vaccine distribution plans diverged beyond initial priority groups: some prioritized based on mortality risks only (i.e., age), while others also included several high-exposure risk groups. After establishing that this divergence was driven by stochastic rather than systematic factors, I leverage it as an identification strategy to test a key insight from network theory: reducing contagion requires disabling the transmission potential of the most connected actors. Based on this, I argue that early prioritization of high-exposure risk groups, especially public-facing essential workers, led to a greater reduction in Covid-19 cases than prioritization based solely on mortality risks. Analysis of daily Covid-19 data in a matched sample of Oregon and California counties shows strong support for this hypothesis.

From January 18th to August 13th, 2021, 13,804 unvaccinated and 1,156 patients who had received at least one COVID-19 vaccine dose were tested qPCR-positive for SARS-CoV-2 in our center. Among vaccinated patients, 949, 205 and 2 had received a single, two or three vaccine doses, respectively. Most patients (80.3%) had received the Pfizer-BioNTech vaccine. The SARS-CoV-2 variants infecting vaccinated patients varied over time, reflecting those circulating in the Marseille area, with a predominance of the Marseille-4/20A.EU2 variant from weeks 3 to 6, of the Alpha/20I variant from weeks 7 to 25, and of the Delta/21A variant from week 26. SARS-CoV-2 infection was significantly more likely to occur in the first 13 days post-vaccine injection in those who received a single dose (48.9%) than two doses (27.4%, p< 10–3). Among 161 patients considered as fully vaccinated, i.e., >14 days after the completion of the vaccinal scheme (one dose for Johnson and Johnson and two doses for Pfizer/BioNTech, Moderna and Sputnik vaccines), 10 (6.2%) required hospitalization and four (2.5%) died. Risks of complications increased with age in a nonlinear pattern, with a first breakpoint at 54, 33, and 53 years for death, transfer to ICU, and hospitalization, respectively. Among patients infected by the Delta/21A or Alpha/20I variants, partial or complete vaccination exhibited a protective effect with a risk divided by 3.1 for mortality in patients ≥ 55 years, by 2.8 for ICU transfer in patients ≥ 34 years, and by 1.8 for hospitalization in patients ≥ 54 years. Compared to partial vaccination, complete vaccination provided an even stronger protective effect, confirming effectiveness to prevent severe forms of COVID-19.