Factors of COVID‐19 vaccine hesitancy among participants by binary logistic regression analysis.

Participants’ beliefs regarding COVID-19 vaccination.

The barriers of COVID‐19 vaccination among the study participants.

IntroductionSince 2010, WHO has recommended oral cholera vaccines as an additional strategy for cholera control. During a cholera episode, pregnant women are at high risk of complications, and the risk of fetal death has been reported to be 2–36%. Due to a lack of safety data, pregnant women have been excluded from most cholera vaccination campaigns. In 2012, reactive campaigns using the bivalent killed whole-cell oral cholera vaccine (BivWC), included all people living in the targeted areas aged ≥1 year regardless of pregnancy status, were implemented in Guinea. We aimed to determine whether there was a difference in pregnancy outcomes between vaccinated and non-vaccinated pregnant women.Methods and FindingsFrom 11 November to 4 December 2013, we conducted a retrospective cohort study in Boffa prefecture among women who were pregnant in 2012 during or after the vaccination campaign. The primary outcome was pregnancy loss, as reported by the mother, and fetal malformations, after clinical examination. Primary exposure was the intake of the BivWC vaccine (Shanchol) during pregnancy, as determined by a vaccination card or oral history. We compared the risk of pregnancy loss between vaccinated and non-vaccinated women through binomial regression analysis. A total of 2,494 pregnancies were included in the analysis. The crude incidence of pregnancy loss was 3.7% (95%CI 2.7–4.8) for fetuses exposed to BivWC vaccine and 2.6% (0.7–4.5) for non-exposed fetuses. The incidence of malformation was 0.6% (0.1–1.0) and 1.2% (0.0–2.5) in BivWC-exposed and non-exposed fetuses, respectively. In both crude and adjusted analyses, fetal exposure to BivWC was not significantly associated with pregnancy loss (adjusted risk ratio (aRR = 1.09 [95%CI: 0.5–2.25], p = 0.818) or malformations (aRR = 0.50 [95%CI: 0.13–1.91], p = 0.314).ConclusionsIn this large retrospective cohort study, we found no association between fetal exposure to BivWC and risk of pregnancy loss or malformation. Despite the weaknesses of a retrospective design, we can conclude that if a risk exists, it is very low. Additional prospective studies are warranted to add to the evidence base on OCV use during pregnancy. Pregnant women are particularly vulnerable during cholera episodes and should be included in vaccination campaigns when the risk of cholera is high, such as during outbreaks.

In mid-January, there will be about ***** COVID-19 vaccination sites in the United Kingdom. This vaccination program, described as the biggest in NHS history, aims at offering jabs to most care home residents by the end of January and the most vulnerable by mid-February. Vaccinations will be available at over a thousand general practitioner-led sites, *** hospitals, and ***** mega centers. These centers will be capable of delivering thousands of vaccinations each week.

Furthermore, the UK has plans to step up capacity even further in the coming weeks, bringing *** pharmacy-led pilot sites and a further ** mass vaccination centers into play. That would take the total number of coronavirus vaccination hubs to about *****. The first ***** mega centers will open in Birmingham, Bristol, London, Manchester, Newcastle-upon-Tyne, Stevenage, and Surrey.

For further information about the coronavirus (COVID-19) pandemic, please visit our dedicated Facts and Figures page.

Background: The COVID-19 pandemic is our generation's greatest global challenge to our public health system. Vaccines are considered one of the most effective tools available for preventing COVID-19 infection and its complications and sequelae. Understanding and addressing the psychological stress related to COVID-19 vaccination may promote acceptance of these vaccines.Methods: We conducted an online survey from January 29 to April 26, 2021 to explore stress levels related to COVID-19 vaccination among the general public in China. Participants were asked to evaluate their psychological stress of considering whether or not to get vaccinated at the beginning period of the COVID-19 mass vaccination, after getting access to the information about the vaccine, as well as after getting vaccinated, using visual analog stress scale. Multiple linear regression analysis was performed to explore factors potentially associated with COVID-19-related psychological stress levels before and after getting vaccinated.Results: A total of 34,041 participants were included in the final analysis. The mean stress score concerning COVID-19 vaccination was 3.90 ± 2.60 among all participants, and significantly decreased over time. In addition, the vaccine-related stress level significantly decreased after accessing information about the COVID-19 vaccine (N = 29,396), as well as after getting vaccinated (N = 5,103). Multivariable regression analysis showed higher stress levels related to COVID-19 vaccination in participants who were younger, having lower education level, having history of chronic diseases, mistrusting vaccine's efficacy, experience of vaccine allergy events, being affected by the COVID-19 epidemic, and having mental illness symptoms. Moreover, mistrust in vaccine efficacy and experience of vaccine allergy events had a long-term impact on psychological stress levels about COVID-19 vaccination even after getting vaccinated.Conclusions: The current findings profiled the COVID-19 vaccine-related psychological stress among the general public in China. Population-specific management and interventions targeting the stress related to COVID-19 vaccination are needed to help governments and policy makers promote individual's willingness to get vaccinations for public well-being during the COVID-19 pandemic.

In December of 2020, and upon an FDA Emergency Use Authorization, a COVID-19 mass vaccination campaign was launched. Vaccine products were tested for safety and efficacy in large, albeit short term, RCTs, that included largely young and healthy adults. The urgency of the campaign did not allow time to assess the long-term effects of these products, nor their potential adverse effects on population subgroups, such as persons suffering from autoimmune conditions. As a result, the association between COVID-19 inoculations and these disorders is poorly documented or understood – whether these disorders result from the inoculations or drives higher rates of adverse effects, autoimmune or not, in persons suffering from them.

The medical literature on the relationship between COVID-19 vaccination and autoimmune disorders reveals several areas of interest and concern. Rocco et al (2021) reported on the onset of autoimmune hepatitis upon COVID-19 vaccination in an elderly woman with a history of Hashimoto’s thyroiditis. McShane et al. reported on a similar case, albeit in an older patient with no prior history of autoimmune disorders. A case report of a healthy, 14-year-old girl deceased upon a third dose of an mRNA COVID-19 vaccine described the death as resulting from a fatal multiorgan inflammation activation, with multiple immune pathways potentially involved (Nushida 2023). Yet another case report described the onset of type 1 diabetes in a middle-aged woman with no prior history of diabetes, upon reception of a second those of the COVID-19 vaccine (Moon 2023). Finally, an observational, cross-sectional, pharmacovigilance cohort study examined individual case safety reports from VigiBase, the World Health Organization's pharmacovigilance database, and identified a rare, albeit statistically significant association between COVID-19 vaccines and transverse myelitis, a condition that, according to the NIH, involves autoimmune processes (Nguyen et al. 2022).

As to ongoing research, a search in the Cochrane Collaboration and the PROSPERO websites, conducted on June 18, 2023, revealed a small number of planned studies examining specific aspects of the relationship between COVID-19 inoculations and autoimmune disorders - such as one meta-analysis of the risk of autoimmune diseases following the inoculations, new immune-mediated disorders, or studies on the vaccine response in patients with previous autoimmune diagnosis. However, no completed or ongoing study has investigated this relationship broadly, scoping the literature on both autoimmune disorders in general and specifically - as described by Cooper & Stroehla (2003) in ‘The epidemiology of autoimmune diseases’, and in Medline Plus (National Library of Medicine, NIH) - concerning the six most frequent disorders: type 1 diabetes, rheumatoid arthritis, lupus, multiple sclerosis, Hashimoto’s thyroiditis, and Graves’ disease.

Therefore, our goal is to document, summarize, and disseminate information on a relatively underexplored area in the literature concerning COVID-19 vaccine safety, i.e., the relationship between COVID-19 vaccines and autoimmune disorders in general and the six most frequent ones listed earlier. We will follow Arksey and O’Malley’s framework for scoping reviews, enhanced by Levac and colleagues team-based approach, to achieve our goal, and identify gaps in the research that can inform the direction of future research, medical practice, and policy.

What is the FluPRINT database?

The FluPRINT represents fully integrated and normalized immunology measurements from eight clinical studies taken from 740 individuals undergoing influenza vaccination with inactivated or live attenuated seasonal influenza vaccines from 2007 to 2015 at the Stanford Human Immune Monitoring Center.

The FluPRINT dataset contains information on more than 3,000 parameters measured using mass cytometry, flow cytometry, phosphorylation-specific cytometry, multiplex cytokine assays, clinical lab tests (hormones and complete blood count), serological profiling and virological tests. In the dataset, vaccine protection is measured using a hemagglutination inhibition (HAI) assay, and following FDA guidelines individuals are marked as high or low responders depending on the HAI antibody titers after vaccination.

Want to know more?

To understand how the FluPRINT dataset was generated and validated, and how to use it, please refer to our open-access paper published in Scientific Data journal:

Tomic, A., Tomic, I., Dekker, C.L. et al. The FluPRINT dataset, a multidimensional analysis of the influenza vaccine imprint on the immune system. Sci Data 6, 214 (2019). https://doi.org/10.1038/s41597-019-0213-4

For additional exploration, please check out the project’s website: www.fluprint.com, where you can also explore the FluPRINT dataset on the following link: https://fluprint.com/#/database-access.

If you want to host your own FluPRINT database, please follow our instructions provided on the Github repository: https://github.com/LogIN-/fluprint.

How to use FluPRINT?

Here, you can download the entire FluPRINT database export as an SQL file, or as a CSV file. Additionally, we included the file with the SQL query to obtain those files.

Files are provided in two formats: zip and 7zip (7z). 7zip is a free and open-source file archiver available for download here: https://www.7-zip.org.

In the FluPRINT database, there are 4 tables: donor, donor_visits, experimental_data, and medical_history.
The exact description of each table is available in the FluPRINT paper.

Briefly, in the table donor, each row represents an individual with information about the clinical study in which an individual was enrolled (study ID and study internal ID), gender, and race. The second table, named donor_visits describes information about the donor’s age, cytomegalovirus (CMV) and Epstein-Barr virus (EBV) status, Body Mass Index (BMI), and vaccine received on each clinical visit. Information about vaccine outcome is available as geometric mean titers (geo_mean), the difference in the geometric mean titers before and after vaccination (delta_geo_mean), and the difference for each vaccine strain (delta_single). In the last field, each individual is classified as a high and low responder (vaccine_resp). On each visit, samples were analyzed and information about which assays were performed (assay field) and value of the measured analytes (units and data) are stored in the experimental_data table. Finally, the medical_history table describes information connected with each clinical visit about the usage of statins (statin_use) and if influenza vaccine was received in the past (influenza vaccine history), if yes, how many times (total_vaccines_received). Also, we provide information on which type of influenza vaccine was received in the previous years (1 to 5 years prior to enrolment in the clinical study). Lastly, information about influenza infection history and influenza-related hospitalization is provided.

How to cite FluPRINT?

If you use FluPRINT in an academic publication, please use the following citation:

Tomic, A., Tomic, I., Dekker, C.L. et al. The FluPRINT dataset, a multidimensional analysis of the influenza vaccine imprint on the immune system. Sci Data 6, 214 (2019). https://doi.org/10.1038/s41597-019-0213-4

Contact Information

If you are interested to find out more about the FluPRINT, or if you experience any problems with downloading files, please contact us at info@adrianatomic.com.

Context

Coronavirus disease 2019 (COVID-19) is a contagious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The first known case was identified in Wuhan, China, in December 2019. The disease has since spread worldwide, leading to an ongoing pandemic.

Symptoms of COVID-19 are variable, but often include fever, cough, headache, fatigue, breathing difficulties, and loss of smell and taste. Symptoms may begin one to fourteen days after exposure to the virus. At least a third of people who are infected do not develop noticeable symptoms. Of those people who develop symptoms noticeable enough to be classed as patients, most (81%) develop mild to moderate symptoms (up to mild pneumonia), while 14% develop severe symptoms (dyspnea, hypoxia, or more than 50% lung involvement on imaging), and 5% suffer critical symptoms (respiratory failure, shock, or multiorgan dysfunction). Older people are at a higher risk of developing severe symptoms. Some people continue to experience a range of effects (long COVID) for months after recovery, and damage to organs has been observed. Multi-year studies are underway to further investigate the long-term effects of the disease.

COVID-19 transmits when people breathe in air contaminated by droplets and small airborne particles containing the virus. The risk of breathing these in is highest when people are in close proximity, but they can be inhaled over longer distances, particularly indoors. Transmission can also occur if splashed or sprayed with contaminated fluids in the eyes, nose, or mouth, and, rarely, via contaminated surfaces. People remain contagious for up to 20 days and can spread the virus even if they do not develop symptoms.

Several testing methods have been developed to diagnose the disease. The standard diagnostic method is by detection of the virus' nucleic acid by real-time reverse transcription-polymerase chain reaction (rRT-PCR), transcription-mediated amplification (TMA), or by reverse transcription loop-mediated isothermal amplification (RT-LAMP) from a nasopharyngeal swab.

Preventive measures include physical or social distancing, quarantining, ventilation of indoor spaces, covering coughs and sneezes, hand washing, and keeping unwashed hands away from the face. The use of face masks or coverings has been recommended in public settings to minimize the risk of transmissions.

While work is underway to develop drugs that inhibit the virus (and several vaccines for it have been approved and distributed in various countries, which have since initiated mass vaccination campaigns), the primary treatment is symptomatic. Management involves the treatment of symptoms, supportive care, isolation, and experimental measures.

Source - https://en.wikipedia.org/wiki/COVID-19

Content

This Dataset is a collection of records for COVID-19 (World and Continent wise).

Structure of the Dataset

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Acknowledgements

This Dataset is created from: https://www.worldometers.info/. If you want to learn more, you can visit the Website.

Cover Photo by Hakan Nural on Unsplash

Abstract

Nigeria implemented series of preventive immunization campaigns to combat measles and yellow fever, two major public health concerns, from October to November 2024. These mass vaccination campaigns aimed to prevent, control, and ultimately eliminate these diseases nationwide. To assess the effectiveness of these efforts, Integrated Post Campaign Coverage Surveys (IPCCS) were conducted after each immunization round to evaluate coverage rates in participating states. This proactive approach is crucial, given Nigeria's history of measles outbreaks and ongoing challenges in achieving optimal vaccination coverage.

Measles: Nigeria's measles vaccination coverage reached 84.2 percent nationwide, but fell short of the 95 percent campaign target threshold set for measles elimination during Supplementary Immunization Activities (SIAs). Vaccination coverage by state ranged between 59 percent in FCT and 97 percent in Ekiti. Children aged 48-59 months had the highest coverage at 85.9 percent whereas those aged 9-11 months had the lowest coverage at 78.2 percent. Urban areas had higher coverage rate of 86.0 percent compared to rural areas at 81.8 percent. No significant difference in vaccination coverage was observed between males and females. The percentage of children that received measles vaccine for the first time during the campaign was 11.7. North Central reported the highest proportion of first-time vaccinations at 16.1 percent, followed by South-South at 12.9 percent, while North East had the lowest at 8.2 percent.

Evidence by card retention, history or recall and finger mark were accessed during the survey. Findings shows that card retention had 44.2 percent, history/recall (38.5 percent) and Finger mark seen (15.8 percent). Card retention across the surveyed states show that respondents in Niger state had highest card retention with 74.0 percent while Ogun state recorded the least card retention with 28.3 percent

Majority of respondents (53.2 percent) learned about the campaign through town criers/ mobilizers/ community health workers. More than 7.0 percent of respondents were not informed of the measles campaign, ranging from 1.9 percent in Ekiti state to 28.9 percent in FCT. The primary reason for non-vaccination was lack of awareness among parents or caregivers (7.0 percent) and 1.3 percent of children were not vaccinated due to religious beliefs.

Yellow Fever: At the aggregate level, the vaccination coverage for Yellow Fever in Borno, Lagos and Yobe states was 67.9 percent which was below the expected 80 percent campaign target threshold. The vaccination coverage by state was 81.6 percent in Yobe, 49.9 percent in Borno state and 62.5 percent in Lagos. Further noticeable disparity in the coverage between urban and rural areas, with urban areas having a higher coverage rate of 72.7 percent compared to 64.7 percent in rural areas. Analysis by age group also shows that coverage among children aged 6-14 years has the highest at 76.8 percent, while the lowest is among adults aged 25-44 years at 57.3 percent. Additionally, vaccination coverage was the same among both males and females at 67.9 percent.

Further analysis on card retention, shows that only 40.0 percent of children who received the vaccination had a vaccination card. Yobe state had the highest proportion of children with vaccination cards at 46.6 percent, while Borno state had the lowest, at 25.9 percent. Evidence of vaccination by finger mark among the targeted States were 10.9 percent in Lagos state, 10.6 percent in Borno state and 3.7 percent in Yobe state.

Majority of respondents learned about the Yellow Fever campaign through town criers /mobilizers/community health workers (31.2 percent), followed by family members (17.5 percent). Among non-vaccinated children, the primary reason was lack of awareness among parents or caregivers (20.0 percent).

Geographic coverage

National Zone State Sector

Analysis unit

Individual

Universe

Individual members 9-59 months for Post Measles and 9-44 months for Post Yellow fever and Measles

Kind of data

Sample survey data [ssd]

Sampling procedure

The frame used for the Integrated Post Campaign Coverage Survey (IPCCS) was the newly digitalize list of enumeration areas for the next National Housing and Population Census. Samples were selected from the frame. However, some parts of Nigeria that were inaccessible due to security reasons were excluded from the sampling frame.

First Stage Selection Forty (40) enumeration areas were selected for coverage in each of the 25 states and FCT-Abuja, thus making 26 strata. A total of 1,028 EAs were selected in all the 25 states and FCT-Abuja.

Second Stage Selection A Systematic random sampling method was used to select households within each EA. A sample of fifteen (15) households were systematically selected per EA for the interview, making a total of 15,600 households across the 25 states and FCT-Abuja.

Third Stage Selection The selection of respondents within each visited household was determined by specific age cohorts and antigen-related criteria.

Measles All children aged 9 to 59 months during the campaign were selected from the household roster and were interviewed about measles vaccination and other additional indicators.

Yellow Fever Individuals from the household roster aged 9 months to 44 years were interviewed about yellow fever vaccination and other related indicators.

Sampling deviation

No Deviations

Mode of data collection

Face-to-face [f2f]

Research instrument

Three structured questionnaires were used for IPCCS of which each consists both household and individual questionnaire.The Questionnaires are -Post Measles Supplementary Immunisation Activity Coverage Survey Questionnaire -Post yellow fever, Supplementary Immunisation Activity Coverage Survey Questionnaire -Post Measles and Yellow fever Supplementary Immunisation Activity Coverage Survey Questionnaire

The household questionnaire was administered in each household, which collected information on Identification and Demographic while the Individual questionnaires are targeted at children 5-59 months for Post measles and 9-44 months for Yellow fever.The information collected includes identification,demographic and immunization.

Cleaning operations

Real - Time data editing took place at different stages throughout the processing which includes: 1) Data editing and cleaning 2) Structure checking and completeness 3) Secondary editing 4) Structural checking of data files

Response rate

The response rate is 100%.

Data appraisal

A series of data quality tables and graphs are available in the report.

Project Overview This portion of the COVID DIARIES project provides full bibliographic information (including original and permanent links) to media items related to the COVID-19 vaccination program, published on the official websites of 20 major U.S. news outlets, including television networks, magazines, and newspapers. It spans the period from December 2020, when states began implementing Phase 1a of the vaccine allocation plan, through September 2021, when vaccines became widely available to all adults and were frequently mandated. News items were collected to preserve a contemporaneous record of how the vaccination effort was discussed across national media. The dataset enables researchers to analyze media communication strategies during a nationwide public health emergency, with the broader aim of informing more effective public health messaging through mass media. This project represents a collaborative effort between the Yale School of Medicine and the Tobin Center for Economic Policy. Data and Data Collection Overview This collection comprises 5,383 unique publication links from 20 major news outlets—including television networks, magazines, and newspapers—published between December 1, 2020, and September 30, 2021. Only articles that were freely accessible online without subscription or paywall restrictions were included. Articles were collected by the research team (specifically AM) between August 2021 and November 2023. These 20 news outlets were selected based on a 2020–2021 survey of 511 U.S. adults, which identified the outlets most commonly used to obtain information about the COVID-19 vaccination program. A full list of news outlets, along with their reported usage and perceived trustworthiness, is provided in Sources_Selection.docx. Online publications were identified using Google search with a custom date range in week-long increments (e.g., 12/01/2020–12/07/2020), using the keyword “vaccine” in combination with the link to the respective news outlet’s website. Search results were manually reviewed by AM according to the following inclusion and exclusion criteria. Inclusion criteria: Articles published on the selected U.S. news outlets websites ending in “.com” or “.co” that relate to the COVID-19 vaccination program; Articles from the selected international news outlets that serve both their country of origin and the U.S. audience (e.g., BBC, The Daily Mail). Exclusion criteria: Articles published on the international news outlets websites that exclusively serve their country of origin (e.g., domains ending in .uk, .ca, etc. without .com, .co); Publications from universities, government agencies, or other organizations not affiliated with major U.S. news outlets (e.g., domains ending in .edu, .gov, .org); Videos without accompanying transcripts; Publications without textual content; Articles referencing vaccines unrelated to COVID-19; Non-English language publications. Selection and Organization of Shared Data The full list of publications is provided in the data file named "News_Outlets_Publications_Full_List." Entries are organized by news outlet (one per tab), then by publication year, month, week, and article title within each tab. For each entry, the list includes the article’s original download date by the research team, file format (e.g., PDF), original link to the publication, and a permanent link record. The list was verified by MC, CA, AV, AG, and AM, with final quality control performed by AM. Each article was assigned a unique identifier in the format: "Article Title – News Outlet Name", ensuring that each entry appears only once in the final dataset. Additional documentation includes this Data Narrative, a document explaining the source selection and an administrative README file.

In order to curb the rapid dissemination of the B.1.351 variant of SARS-CoV-2 in the district of Schwaz and beyond, the EU allocated additional vaccine doses at the beginning of March 2021 to implement a rapid mass vaccination of the population (16+). The aim of our study was to determine the seroprevalence of SARS-CoV-2 among the adult population in the district of Schwaz at the time of the implementation. Data on previous history of infections, symptoms and immunization status were collected using a structured questionnaire. Blood samples were used to determine SARS-CoV-2 specific anti-spike, anti-nucleocapsid and neutralizing antibodies. We recruited 2,474 individuals with a median age (IQR) of 42 (31–54) years. Using the official data on distribution of age and sex, we found a standardized prevalence of undocumented infections at 15.0% (95% CI: 13.2–16.7). Taken together with the officially documented infections, we estimated that 24.0% (95% CI: 22.5–25.6) of the adult population had prior SARS-CoV-2 infection. Hence, the proportion of undocumented infections identified by our study was 55.8% (95% CI: 52.7–58.5). With a vaccination coverage of 10% among the adults population at that time, we imply that a minimum of two-thirds of the target popuation was susceptible to the circulating threat when this unique campaign started.

Moderna generated total revenues of some 3.2 billion U.S. dollars in 2024, a massive decrease compared to the years before. The drop was mainly due to the decreasing demand for its COVID-19 vaccine Spikevax. Working hard to produce the first 'blockbuster' Moderna is a clinical stage biotech company that is pioneering messenger RNA (mRNA) therapeutics and vaccines. Beside its COVID-19 vaccine, the company is yet to generate revenues from the sale of potential drugs, and this will remain the same until it successfully completes clinical development and obtains regulatory approval for one of its medicines. Like many other biotech companies, Moderna invests significant amounts of money into research and development projects, and annual costs continue to grow. One of the very first COVID-19 vaccines approved Moderna, in partnership with the National Institutes of Health (NIH) and the Coalition for Epidemic Preparedness Innovations (CEPI), was one of the very first to develop a vaccine to fight COVID-19. The vaccine codenamed mRNA-1273 – designed and manufactured in only 25 days – prevents future infections of the novel coronavirus that has caused the pandemic. The Moderna vaccine successfully went through all necessaryclinical phases, and was the second vaccine - after the Biontech/Pfizer vaccine - to be approved for widely usage already in late 2020.

Reporting of Aggregate Case and Death Count data was discontinued May 11, 2023, with the expiration of the COVID-19 public health emergency declaration. Although these data will continue to be publicly available, this dataset will no longer be updated.

This archived public use dataset has 11 data elements reflecting United States COVID-19 community levels for all available counties.

The COVID-19 community levels were developed using a combination of three metrics — new COVID-19 admissions per 100,000 population in the past 7 days, the percent of staffed inpatient beds occupied by COVID-19 patients, and total new COVID-19 cases per 100,000 population in the past 7 days. The COVID-19 community level was determined by the higher of the new admissions and inpatient beds metrics, based on the current level of new cases per 100,000 population in the past 7 days. New COVID-19 admissions and the percent of staffed inpatient beds occupied represent the current potential for strain on the health system. Data on new cases acts as an early warning indicator of potential increases in health system strain in the event of a COVID-19 surge.

Using these data, the COVID-19 community level was classified as low, medium, or high.

COVID-19 Community Levels were used to help communities and individuals make decisions based on their local context and their unique needs. Community vaccination coverage and other local information, like early alerts from surveillance, such as through wastewater or the number of emergency department visits for COVID-19, when available, can also inform decision making for health officials and individuals.

For the most accurate and up-to-date data for any county or state, visit the relevant health department website. COVID Data Tracker may display data that differ from state and local websites. This can be due to differences in how data were collected, how metrics were calculated, or the timing of web updates.

Archived Data Notes:

This dataset was renamed from "United States COVID-19 Community Levels by County as Originally Posted" to "United States COVID-19 Community Levels by County" on March 31, 2022.

March 31, 2022: Column name for county population was changed to “county_population”. No change was made to the data points previous released.

March 31, 2022: New column, “health_service_area_population”, was added to the dataset to denote the total population in the designated Health Service Area based on 2019 Census estimate.

March 31, 2022: FIPS codes for territories American Samoa, Guam, Commonwealth of the Northern Mariana Islands, and United States Virgin Islands were re-formatted to 5-digit numeric for records released on 3/3/2022 to be consistent with other records in the dataset.

March 31, 2022: Changes were made to the text fields in variables “county”, “state”, and “health_service_area” so the formats are consistent across releases.

March 31, 2022: The “%” sign was removed from the text field in column “covid_inpatient_bed_utilization”. No change was made to the data. As indicated in the column description, values in this column represent the percentage of staffed inpatient beds occupied by COVID-19 patients (7-day average).

March 31, 2022: Data values for columns, “county_population”, “health_service_area_number”, and “health_service_area” were backfilled for records released on 2/24/2022. These columns were added since the week of 3/3/2022, thus the values were previously missing for records released the week prior.

April 7, 2022: Updates made to data released on 3/24/2022 for Guam, Commonwealth of the Northern Mariana Islands, and United States Virgin Islands to correct a data mapping error.

April 21, 2022: COVID-19 Community Level (CCL) data released for counties in Nebraska for the week of April 21, 2022 have 3 counties identified in the high category and 37 in the medium category. CDC has been working with state officials to verify the data submitted, as other data systems are not providing alerts for substantial increases in disease transmission or severity in the state.

May 26, 2022: COVID-19 Community Level (CCL) data released for McCracken County, KY for the week of May 5, 2022 have been updated to correct a data processing error. McCracken County, KY should have appeared in the low community level category during the week of May 5, 2022. This correction is reflected in this update.

May 26, 2022: COVID-19 Community Level (CCL) data released for several Florida counties for the week of May 19th, 2022, have been corrected for a data processing error. Of note, Broward, Miami-Dade, Palm Beach Counties should have appeared in the high CCL category, and Osceola County should have appeared in the medium CCL category. These corrections are reflected in this update.

May 26, 2022: COVID-19 Community Level (CCL) data released for Orange County, New York for the week of May 26, 2022 displayed an erroneous case rate of zero and a CCL category of low due to a data source error. This county should have appeared in the medium CCL category.

June 2, 2022: COVID-19 Community Level (CCL) data released for Tolland County, CT for the week of May 26, 2022 have been updated to correct a data processing error. Tolland County, CT should have appeared in the medium community level category during the week of May 26, 2022. This correction is reflected in this update.

June 9, 2022: COVID-19 Community Level (CCL) data released for Tolland County, CT for the week of May 26, 2022 have been updated to correct a misspelling. The medium community level category for Tolland County, CT on the week of May 26, 2022 was misspelled as “meduim” in the data set. This correction is reflected in this update.

June 9, 2022: COVID-19 Community Level (CCL) data released for Mississippi counties for the week of June 9, 2022 should be interpreted with caution due to a reporting cadence change over the Memorial Day holiday that resulted in artificially inflated case rates in the state.

July 7, 2022: COVID-19 Community Level (CCL) data released for Rock County, Minnesota for the week of July 7, 2022 displayed an artificially low case rate and CCL category due to a data source error. This county should have appeared in the high CCL category.

July 14, 2022: COVID-19 Community Level (CCL) data released for Massachusetts counties for the week of July 14, 2022 should be interpreted with caution due to a reporting cadence change that resulted in lower than expected case rates and CCL categories in the state.

July 28, 2022: COVID-19 Community Level (CCL) data released for all Montana counties for the week of July 21, 2022 had case rates of 0 due to a reporting issue. The case rates have been corrected in this update.

July 28, 2022: COVID-19 Community Level (CCL) data released for Alaska for all weeks prior to July 21, 2022 included non-resident cases. The case rates for the time series have been corrected in this update.

July 28, 2022: A laboratory in Nevada reported a backlog of historic COVID-19 cases. As a result, the 7-day case count and rate will be inflated in Clark County, NV for the week of July 28, 2022.

August 4, 2022: COVID-19 Community Level (CCL) data was updated on August 2, 2022 in error during performance testing. Data for the week of July 28, 2022 was changed during this update due to additional case and hospital data as a result of late reporting between July 28, 2022 and August 2, 2022. Since the purpose of this data set is to provide point-in-time views of COVID-19 Community Levels on Thursdays, any changes made to the data set during the August 2, 2022 update have been reverted in this update.

August 4, 2022: COVID-19 Community Level (CCL) data for the week of July 28, 2022 for 8 counties in Utah (Beaver County, Daggett County, Duchesne County, Garfield County, Iron County, Kane County, Uintah County, and Washington County) case data was missing due to data collection issues. CDC and its partners have resolved the issue and the correction is reflected in this update.

August 4, 2022: Due to a reporting cadence change, case rates for all Alabama counties will be lower than expected. As a result, the CCL levels published on August 4, 2022 should be interpreted with caution.

August 11, 2022: COVID-19 Community Level (CCL) data for the week of August 4, 2022 for South Carolina have been updated to correct a data collection error that resulted in incorrect case data. CDC and its partners have resolved the issue and the correction is reflected in this update.

August 18, 2022: COVID-19 Community Level (CCL) data for the week of August 11, 2022 for Connecticut have been updated to correct a data ingestion error that inflated the CT case rates. CDC, in collaboration with CT, has resolved the issue and the correction is reflected in this update.

August 25, 2022: A laboratory in Tennessee reported a backlog of historic COVID-19 cases. As a result, the 7-day case count and rate may be inflated in many counties and the CCLs published on August 25, 2022 should be interpreted with caution.

August 25, 2022: Due to a data source error, the 7-day case rate for St. Louis County, Missouri, is reported as zero in the COVID-19 Community Level data released on August 25, 2022. Therefore, the COVID-19 Community Level for this county should be interpreted with caution.

September 1, 2022: Due to a reporting issue, case rates for all Nebraska counties will include 6 days of data instead of 7 days in the COVID-19 Community Level (CCL) data released on September 1, 2022. Therefore, the CCLs for all Nebraska counties should be interpreted with caution.

September 8, 2022: Due to a data processing error, the case rate for Philadelphia County, Pennsylvania,

These files contain correspondence between the Department and shire and municipal councils (mainly), medical officers of health, and individuals, regarding the operation of government subsidized mass anti-diphtheria immunization campaigns conducted by local councils.

As well as providing a fairly complete outline of the operation of the scheme, these files include returns showing the names, addresses, ages and sex of children immunized, parent's name, details of dosage, fees paid to doctors and nurses. These returns, however, ceased to be a departmental requirement after 1955 and figures do not therefore appear consistently after that date. Moreover, those files dealing with the larger municipalities and shires were often split by the department to reduce their size and material for urban and suburban areas is therefore not available for the period 1936 to the mid 1940s.

(12/918-59). 42 boxes.

Note:

This description is extracted from Concise Guide to the State Archives of New South Wales, 3rd Edition 2000.

Inactivated Vaccine Market Outlook

The global inactivated vaccine market size was valued at USD 15.3 billion in 2023 and is projected to reach USD 23.8 billion by 2032, growing at a compound annual growth rate (CAGR) of 5.2% during the forecast period from 2024 to 2032. The growth of this market is primarily driven by increasing awareness about vaccination benefits, government initiatives to expand immunization programs, and rising prevalence of infectious diseases.

The expanding awareness among the global population regarding the importance and benefits of vaccination has significantly contributed to the growth of the inactivated vaccine market. Immunization programs have received a boost through extensive campaigns led by health organizations and governments worldwide. These programs emphasize the critical role vaccinations play in preventing life-threatening diseases, which has resulted in higher demand for inactivated vaccines. Moreover, as educational outreach intensifies, an increasing number of individuals are opting for vaccinations, thereby driving market growth.

Government initiatives and policies aimed at expanding immunization coverage have also played a pivotal role in market growth. Many countries have launched national immunization programs that include inactivated vaccines as a core component. These initiatives are often supported by funding from both governmental and non-governmental organizations, making vaccines more accessible to the public. Additionally, improvements in healthcare infrastructure and the establishment of specialized vaccination centers have further facilitated the widespread distribution and administration of inactivated vaccines.

The rising prevalence of infectious diseases, such as influenza, hepatitis, and polio, has necessitated the development and distribution of effective vaccines. Inactivated vaccines, known for their safety and efficacy, have become a preferred choice in combating these illnesses. The increasing incidence of these diseases has compelled healthcare providers to adopt comprehensive vaccination strategies, thereby boosting the market for inactivated vaccines. Furthermore, emerging infectious diseases and potential pandemics underscore the need for ongoing vaccine development and deployment, contributing to market expansion.

From a regional perspective, North America holds a substantial share of the inactivated vaccine market, owing to its well-established healthcare infrastructure and high awareness levels among the population. Europe follows closely, driven by robust immunization programs and significant government support. The Asia Pacific region is expected to witness the highest growth rate during the forecast period due to increasing healthcare investments, growing population, and rising prevalence of infectious diseases. Latin America and the Middle East & Africa are also showing promising growth potential, albeit at a slightly slower pace.

Vaccine Type Analysis

The inactivated vaccine market is segmented based on vaccine type into whole virus vaccines, split virus vaccines, and subunit vaccines. Whole virus vaccines, which include entire virus particles that have been killed or inactivated, remain a cornerstone of many immunization programs. These vaccines are noted for their ability to induce a strong immune response, providing comprehensive protection against the infectious agent. Their long history of use and proven efficacy make them a reliable choice for mass immunization efforts. As a result, whole virus vaccines continue to hold a significant share of the inactivated vaccine market.

Split virus vaccines, which contain virus particles that have been chemically disrupted, represent another important segment. These vaccines offer an alternative to whole virus vaccines, often providing a better safety profile by reducing reactogenicity. Split virus vaccines are particularly beneficial for individuals with compromised immune systems or those who may experience adverse reactions to whole virus vaccines. The growing demand for safer vaccine options has driven the adoption of split virus vaccines, contributing to market growth within this segment.

Subunit vaccines, which include only the essential antigens of the virus necessary to elicit an immune response, have gained prominence due to their high safety and specificity. These vaccines minimize the risk of side effects while effectively stimulating the immune system to recognize and combat the virus. Advances in biotechnology and recombinant DNA technology have facilitated the development of more sophist

BackgroundCanine transmitted rabies kills an estimated 59,000 people annually, despite proven methods for elimination through mass dog vaccination. Challenges in directing and monitoring numerous remote vaccination teams across large geographic areas remain a significant barrier to the up-scaling of focal vaccination programmes to sub-national and national level. Smartphone technology (mHealth) is increasingly being used to enhance the coordination and efficiency of public health initiatives in developing countries, however examples of successful scaling beyond pilot implementation are rare. This study describes a smartphone app and website platform, “Mission Rabies App”, used to co-ordinate rabies control activities at project sites in four continents to vaccinate over one million dogs.MethodsMission Rabies App made it possible to not only gather relevant campaign data from the field, but also to direct vaccination teams systematically in near real-time. The display of user-allocated boundaries on Google maps within data collection forms enabled a project manager to define each team’s region of work, assess their output and assign subsequent areas to progressively vaccinate across a geographic area. This ability to monitor work and react to a rapidly changing situation has the potential to improve efficiency and coverage achieved, compared to regular project management structures, as well as enhancing capacity for data review and analysis from remote areas. The ability to plot the location of every vaccine administered facilitated engagement with stakeholders through transparent reporting, and has the potential to motivate politicians to support such activities.ResultsSince the system launched in September 2014, over 1.5 million data entries have been made to record dog vaccinations, rabies education classes and field surveys in 16 countries. Use of the system has increased year-on-year with adoption for mass dog vaccination campaigns at the India state level in Goa and national level in Haiti.ConclusionsInnovative approaches to rapidly scale mass dog vaccination programmes in a sustained and systematic fashion are urgently needed to achieve the WHO, OIE and FAO goal to eliminate canine-transmitted human deaths by 2030. The Mission Rabies App is an mHealth innovation which greatly reduces the logistical and managerial barriers to implementing large scale rabies control activities. Free access to the platform aims to support pilot campaigns to better structure and report on proof-of-concept initiatives, clearly presenting outcomes and opportunities for expansion. The functionalities of the Mission Rabies App may also be beneficial to other infectious disease interventions.

Oral Vaccine Adjuvants Market Outlook

The oral vaccine adjuvants market size was valued at approximately USD 1.2 billion in 2023 and is projected to reach around USD 2.5 billion by 2032, growing at a CAGR of 8.5% during the forecast period. The growth of this market is driven by the increasing prevalence of infectious diseases and the rising demand for more effective and long-lasting immunization methods. Oral vaccine adjuvants are integral in enhancing the body's immune response to vaccines administered orally, making them crucial in the fight against various diseases.

One significant growth factor for the oral vaccine adjuvants market is the ongoing advancements in vaccine development technology. Innovations in molecular biology and immunology have paved the way for more effective adjuvants that better stimulate the immune system. These advancements not only improve the efficacy of vaccines but also enhance their safety profiles, making them more acceptable to the public and regulatory bodies. Companies and research institutions are heavily investing in R&D to discover novel adjuvants that can provide robust immunity with fewer doses, which is particularly beneficial in regions with limited healthcare access.

Another key driver is the increasing awareness and acceptance of vaccination programs. Governments and health organizations worldwide are emphasizing the importance of immunization to prevent disease outbreaks. Oral vaccines, being easier to administer and more patient-friendly, are gaining favor, especially for mass immunization programs. Additionally, the convenience of oral vaccines encourages higher compliance rates among populations, which is crucial in achieving herd immunity. As public health campaigns continue to promote the benefits of vaccination, the demand for effective oral vaccine adjuvants is expected to rise significantly.

The growing incidence of zoonotic diseases also contributes to the demand for oral vaccine adjuvants. Veterinary vaccines, particularly for diseases that can transfer from animals to humans, are essential in maintaining both animal and public health. Oral vaccine adjuvants play a vital role in veterinary medicine by enabling more effective vaccines for livestock and pets. This not only helps in controlling disease outbreaks in animal populations but also mitigates the risk of zoonotic diseases affecting human populations. Thus, the veterinary vaccine segment is anticipated to see substantial growth, further propelling the oral vaccine adjuvants market.

From a regional perspective, North America and Europe are currently the largest markets for oral vaccine adjuvants. These regions have well-established healthcare infrastructures, significant R&D investments, and high public awareness about vaccination benefits. However, the Asia Pacific region is expected to witness the highest growth rate during the forecast period. The increasing population, rising healthcare expenditure, and government initiatives to improve immunization coverage in countries like China and India are key factors driving the market in this region. As these emerging markets continue to develop, they present lucrative opportunities for companies operating in the oral vaccine adjuvants market.

Type Analysis

The type segment in the oral vaccine adjuvants market encompasses alum, liposomes, emulsions, pathogen components, and others. Alum-based adjuvants have been traditionally used and are well-established in the market due to their proven efficacy and safety. Alum works by creating a depot effect, slowly releasing the antigen and enhancing the immune response. Its long history of use in various vaccines makes it a reliable choice, particularly for vaccines that require strong antibody responses. Despite the emergence of newer adjuvants, alum continues to hold a significant share of the market due to its cost-effectiveness and established regulatory acceptance.

Liposomes are another critical type of oral vaccine adjuvant. These spherical vesicles can encapsulate antigens and deliver them effectively to the immune system. Liposomes enhance the stability of the antigen and facilitate its uptake by immune cells, leading to a more robust and prolonged immune response. The versatility of liposomes in delivering various types of antigens, including proteins, peptides, and nucleic acids, makes them highly valuable in the development of new vaccines. As research advances, liposome-based adjuvants are expected to gain more traction in the market, especially for complex and novel vaccines.

Emulsions, particularly o

Abstract

Clalit, the largest healthcare payer/provider system in Israel, is a well-integrated system that owns and operates 14 hospitals and over 1,500 clinics.

Documentation

Clalit, the largest healthcare payer/provider system in Israel, is a well-integrated system that owns and operates 14 hospitals and over 1,500 clinics, as well as a nation-wide network of pharmacies, imaging centers, labs and even complimentary medicine clinics. Because members very infrequently switch among health plans (50% of the Israel population), Inpatient, outpatient, pharmacy data, laboratory data, and imaging data, all available for over 15 years.

The Clalit data warehouse contains variables relating to demographics (i.e. age, sex, linkage to mother/father for family mapping analyses, place of birth), health history (body mass index, smoking status, comorbidities, vaccination history, etc.), hospital admission data (i.e. diagnoses, length of stay, procedures performed), outpatient clinics data (i.e. signs and symptoms, diagnoses, specialization visited), laboratory values (test type, lab result and norm values), pharmacy data (prescribing and dispensing data), cost (pricelist and real-life monthly cost per patient), and other administrative data (all health services consumption paid for). Diagnostic data are primarily based on the International Classification of Diseases, 9th revision (ICD-9) and their associated free text. Additional unstructured data includes text, imaging and pathology studies.

This data is augmented by the largest ongoing patient experience survey in Israel, which is collected through the Clalit patient portal and Personal Health Record (PHR).

Details of the cohort and related publications can be found on the website.

Patient characteristics Individuals enrolled in Clalit Health Services

Data categories Types of data captured include: Detailed demographic information (e.g. sex, date of birth, members and parent place of birth) Diagnoses (both EHR and claims driven) Clinical measures (e.g. BMI, blood pressure) Lab test results and imaging tests conducted Patient reported information (e.g. smoking status and willingness to quit smoking) Cost (pricelist and real life monthly cost per patient) Medications prescribed and dispensed Administrative data (e.g. total costs, health services consumption) and more.

Notes If you are interested in working with these data, please contact the Population Health Sciences Data Core at phsdatacore@stanford.edu.