30 datasets found
  1. f

    Data_Sheet_1_Evaluating spatial accessibility to COVID-19 vaccine resources...

    • frontiersin.figshare.com
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    Updated Jun 3, 2023
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    Feng Qi; Daniela Barragan; Maverick Garcia Rodriguez; Jiongcheng Lu (2023). Data_Sheet_1_Evaluating spatial accessibility to COVID-19 vaccine resources in diversely populated counties in the United States.PDF [Dataset]. http://doi.org/10.3389/fpubh.2022.895538.s001
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    pdfAvailable download formats
    Dataset updated
    Jun 3, 2023
    Dataset provided by
    Frontiers
    Authors
    Feng Qi; Daniela Barragan; Maverick Garcia Rodriguez; Jiongcheng Lu
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    United States
    Description

    This study examines the accessibility to COVID-19 vaccination resources in two counties surrounding Newark, NJ in the New York Metropolitan Area, United States. The study area represents diverse population makeups. COVID-19 vaccines were made available by different types of vaccination sites including county mass vaccination sites, medical facilities and pharmacies, and a FEMA community vaccination center in spring 2021. We used the two-step floating catchment area method to measure accessibility and calculated the average accessibility scores of different population groups. We examined the patterns and tested the significance of the differences in accessibility across population groups. The results showed clear spatial heterogeneity in the accessibility to vaccine resources with the existing infrastructure (medical/pharmacy vaccine sites). Accessibility patterns changed with the introduction of county mass sites and the FEMA community site. The county mass vaccination sites in one county greatly increased accessibilities for populations of minority and poverty. The FEMA community site in the other county accomplished the same. Both the local health department and the federal government played an important role in mitigating pre-existing inequalities during the vaccination campaign. Our study shows that social determinants of health need to be addressed and taken into explicit consideration when planning resource distribution during the pandemic.

  2. Number of coronavirus vaccination locations in the UK 2021

    • statista.com
    Updated Nov 30, 2023
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    Statista (2023). Number of coronavirus vaccination locations in the UK 2021 [Dataset]. https://www.statista.com/statistics/1195937/united-kingdom-number-of-vaccination-locations/
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    Dataset updated
    Nov 30, 2023
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    Jan 11, 2021
    Area covered
    United Kingdom
    Description

    In mid-January, there will be about 1,200 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, 223 hospitals, and seven 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 200 pharmacy-led pilot sites and a further 43 mass vaccination centers into play. That would take the total number of coronavirus vaccination hubs to about 1,500. The first seven 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.

  3. f

    Data_Sheet_1_Understanding COVID-19 vaccine hesitancy in health care...

    • frontiersin.figshare.com
    pdf
    Updated Jun 16, 2023
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    Shalkar Adambekov; Alexander Bongers; Jonathan Hare; Dragoslav Popovic; Harsha Rajashekharaiah; Stefan M. Lawson; Giovanna Riggall; Larissa Kokareva; Brian Chin (2023). Data_Sheet_1_Understanding COVID-19 vaccine hesitancy in health care professionals in Central and West Asia: lessons for future emergency mass vaccination campaigns.PDF [Dataset]. http://doi.org/10.3389/fpubh.2023.1196289.s002
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    pdfAvailable download formats
    Dataset updated
    Jun 16, 2023
    Dataset provided by
    Frontiers
    Authors
    Shalkar Adambekov; Alexander Bongers; Jonathan Hare; Dragoslav Popovic; Harsha Rajashekharaiah; Stefan M. Lawson; Giovanna Riggall; Larissa Kokareva; Brian Chin
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    A Quick Assessment of Vaccine Hesitancy approach was developed to collect population insights on vaccination hesitancy for low resource environments. Insights into COVID-19 vaccine hesitancy were collected through online webinars with heads of healthcare departments and anonymized online surveys of healthcare managers (HCM) and primary healthcare workers (HCW) in four countries in Central and West Asia (Armenia, Georgia, Tajikistan, and Kyrgyzstan) between 28 February 2022 and 29 March 2022. From the responses to the survey some key themes identified that underpinned in vaccine hesitancy across the region were perceived understanding of vaccine efficacy, conflict with individual religious beliefs, concerns for side effects, and the relatively rapid development of the vaccine and that improving communications strategies to address these concerns would be critical in combatting vaccine hesitancy through any future public health emergencies.

  4. Hepatitis A Vaccination Market Report | Global Forecast From 2025 To 2033

    • dataintelo.com
    csv, pdf, pptx
    Updated May 29, 2024
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    Dataintelo (2024). Hepatitis A Vaccination Market Report | Global Forecast From 2025 To 2033 [Dataset]. https://dataintelo.com/report/global-hepatitis-a-vaccination-market
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    pdf, pptx, csvAvailable download formats
    Dataset updated
    May 29, 2024
    Dataset authored and provided by
    Dataintelo
    License

    https://dataintelo.com/privacy-and-policyhttps://dataintelo.com/privacy-and-policy

    Time period covered
    2024 - 2032
    Area covered
    Global
    Description

    Hepatitis A Vaccination Market Outlook 2032



    The global Hepatitis A vaccination market size was USD 939.4 Million in 2023 and is projected to reach USD 1284.77 Million by 2032, expanding at a CAGR of 3.54% during 2024–2032. The market growth is attributed to rising demand for combination vaccines and advancements in vaccine technology and manufacturing processes.



    Growing incidence of Hepatitis A outbreaks is projected to boost the market. Outbreaks in both developed and developing countries have highlighted the need for effective vaccination strategies. These outbreaks often lead to increased media coverage and public concern, which in turn fuel vaccination efforts. Health authorities are responding to these outbreaks by implementing mass vaccination campaigns, further increasing vaccine uptake. The recurrence of such outbreaks underscores the necessity of widespread immunization, thereby propelling the market.





    Rising travel and tourism activities are likely to propel the Hepatitis A vaccination market. Travelers to endemic regions are at a higher risk of contracting Hepatitis A, prompting them to seek vaccination before their trips. Travel clinics and healthcare providers are increasingly recommending Hepatitis A vaccines as part of pre-travel health consultations. The rise in international travel, along with the growing awareness of travel-related health risks, is boosting the demand for these vaccines. This trend is particularly pronounced among travelers from countries with low Hepatitis A incidence, who are susceptible to infection when visiting high-risk areas.



    Impact of Artificial Intelligence (AI) in Hepatitis A Vaccination Market



    Artificial Intelligence has a positive impact on Hepatitis A vaccination market. AI algorithms analyze vast datasets to identify potential vaccine candidates quickly and accurately, accelerating the research and development process. Machine learning models predict outbreaks and identify high-risk areas,

  5. p

    Points of Interest

    • data.peelregion.ca
    Updated Dec 6, 2019
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    Regional Municipality of Peel (2019). Points of Interest [Dataset]. https://data.peelregion.ca/maps/2f28a4aa168e40fba85afda276c7af39
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    Dataset updated
    Dec 6, 2019
    Dataset authored and provided by
    Regional Municipality of Peel
    License

    https://data.peelregion.ca/pages/licensehttps://data.peelregion.ca/pages/license

    Area covered
    Description

    Points of interest (POI) includes a wide array of features. These features are usually locations that are of interest to the public. The data is collected from a variety of sources, including web searches, data from external partners, and data from internal departments. See notes below for more information.Data categories range from institutional to public housing to early years centres. Some examples of the categories contained within the data are:Temporary: COVID-19 mass vaccination sites and pharmacy vaccination sitesArts, museum, and cultural spacesEmergency responder stations: fire, police, and paramedicsInstitutional buildings: city/town halls, court houses, librariesHospitals, medical centres, and walk-in clinicsHousing: public housing, co-operative housing, sheltersFood banksLong term care homes and retirement homesPost officesRecreation centres and other municipal meeting places: arenas, pools, community centres, meeting hallsSettlement services and other related services for immigrants and newcomersShopping centres: plazas, big box centres, and mallsTransportation: airports, major bus stations, and passenger rail stations

  6. N

    Needle Free Injection Market Report

    • promarketreports.com
    doc, pdf, ppt
    Updated Jan 4, 2025
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    Pro Market Reports (2025). Needle Free Injection Market Report [Dataset]. https://www.promarketreports.com/reports/needle-free-injection-market-6881
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    doc, pdf, pptAvailable download formats
    Dataset updated
    Jan 4, 2025
    Dataset authored and provided by
    Pro Market Reports
    License

    https://www.promarketreports.com/privacy-policyhttps://www.promarketreports.com/privacy-policy

    Time period covered
    2025 - 2033
    Area covered
    Global
    Variables measured
    Market Size
    Description

    Fillable:Disposable Systems: Single-use, cost-effective, ideal for mass vaccination campaigns.Reusable Systems: Durable, multi-use, suitable for clinics and hospitals.Technology:Jet-Based: Delivers high-volume injections through a pressurized stream.Needle-Free Needles: Uses micro-needles to penetrate the skin painlessly.Micro-Array Patches: Tiny needles arranged on a patch, provide sustained drug delivery.Usability:Single-Use: Disposable after one use, minimizes infection risk.Reusable: Can be sterilized and reused multiple times, cost-effective.Type of Medication:Liquid-Based: Contains liquid medication, requires specific delivery systems.Dry Powder: Formulated as a dry powder, requires reconstitution before injection.Site of Delivery:Intradermal: Injects into the outermost layer of the skin.Subcutaneous: Injects into the layer of fat beneath the skin.Intramuscular: Injects into the muscle tissue.Application:Vaccination: Mass immunization campaigns, needle-free delivery of vaccines.End Users: Hospitals, clinics, vaccination centers, home healthcare settings. Recent developments include: The pharmaceutical business as we know it originated in Europe. It also houses the world's oldest and still functioning pharmaceutical firm, Merck KGaA, often known as the Merck Group in the United States, which marked its 350th anniversary in 2018. Europe and the United States continue to be the world's largest and most influential pharmaceutical markets. It's no surprise that the first widely authorized and used COVID-19 vaccine came from a joint venture between BioNTech in Germany and Pfizer in the United States., Medical International Technology, Inc. is a company that manufactures, markets, and sells needle-free jet injector solutions for single and mass injections in people and animals. In the sphere of medical equipment, the company focuses on the medical and paramedical sectors The company's product lines include a home use injector for diabetics and other therapies that require daily injections, as well as a vaccine and other biological injectable medicines targeting physicians in their clinics..

  7. C

    Covid-19 Vaccine Bottle Report

    • marketreportanalytics.com
    doc, pdf, ppt
    Updated Apr 6, 2025
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    Market Report Analytics (2025). Covid-19 Vaccine Bottle Report [Dataset]. https://www.marketreportanalytics.com/reports/covid-19-vaccine-bottle-65604
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    pdf, ppt, docAvailable download formats
    Dataset updated
    Apr 6, 2025
    Dataset authored and provided by
    Market Report Analytics
    License

    https://www.marketreportanalytics.com/privacy-policyhttps://www.marketreportanalytics.com/privacy-policy

    Time period covered
    2025 - 2033
    Area covered
    Global
    Variables measured
    Market Size
    Description

    The global market for COVID-19 vaccine bottles experienced significant growth during the pandemic and continues to evolve. Driven by the urgent need for mass vaccination campaigns worldwide, the market witnessed a surge in demand, primarily fueled by the high volume of vaccine doses requiring safe and effective containment. The market is segmented by application (scientific research centers, vaccine manufacturers, others) and by type (10-dose and 50-dose bottles), reflecting varying needs across the pharmaceutical supply chain. Major players like Schott, Corning, NEG, Shandong Pharmaceutical Glass Co., Ltd., and Cardinal Health dominate the market, leveraging their established expertise in glass manufacturing and pharmaceutical packaging. The high CAGR (let's assume a conservative 8% for illustrative purposes, given the initial surge and subsequent stabilization) indicates continued growth, though at a more moderate pace than during the peak pandemic years. Factors like ongoing booster campaigns, the emergence of new variants requiring updated vaccines, and the growing demand for temperature-controlled packaging contribute to sustained market expansion. Regional market dominance likely reflects manufacturing capacity and vaccine production hubs, with North America and Europe initially holding substantial shares, followed by Asia-Pacific experiencing increasing growth due to expanding domestic vaccine production. However, future growth will likely be influenced by factors such as the global economic climate and the evolving landscape of infectious disease control. Market restraints include potential shifts towards alternative vaccine delivery methods, fluctuations in raw material prices (glass and other packaging components), and regulatory hurdles related to packaging standardization and safety. The continued evolution of vaccine technology also presents both opportunities and challenges; for example, new mRNA vaccines may require specific packaging solutions not previously necessary, presenting opportunities for innovation within the vaccine bottle market. Long-term projections suggest that the market will maintain a steady growth trajectory, driven by ongoing vaccination programs and potential future pandemic preparedness initiatives. Further segmentation analysis would provide a more detailed understanding of the market's evolving dynamics. For example, exploring the different types of glass used (Type I, Type II, etc.) and their relative market share could offer additional insights into technological advancement and market preferences.

  8. f

    Household survey.

    • figshare.com
    zip
    Updated Apr 29, 2024
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    Zerin Jannat; Hemel Das; Md. Wazed Ali; Tasnuva Wahed; Md. Nurul Alam; Md. Jasim Uddin (2024). Household survey. [Dataset]. http://doi.org/10.1371/journal.pone.0302056.s006
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    zipAvailable download formats
    Dataset updated
    Apr 29, 2024
    Dataset provided by
    PLOS ONE
    Authors
    Zerin Jannat; Hemel Das; Md. Wazed Ali; Tasnuva Wahed; Md. Nurul Alam; Md. Jasim Uddin
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    BackgroundVaccination has been an indispensable step in controlling the coronavirus disease pandemic. In early 2021, Bangladesh launched a mass vaccination campaign to boost the COVID-19 vaccination rate when doses were available and immunized millions in the country. Although deemed a success, disparities became conspicuous in vaccination coverage across population of different socioeconomic background.MethodsThe purpose of this cross-sectional study was to assess the vaccination coverage for three doses and detect disparities in uptake of the COVID-19 vaccine among rural population of hard-to-reach areas and urban individuals belonging to the high-risk group -defined in our study as individuals from elusive population such as floating population/street dwellers, transgender, addicts and disabled population. We conducted household survey (n = 12,298) and survey with high risk group of people (2,520). The collected primary data were analysed using descriptive statistical analysis.ResultsOur findings show that coverage for the first dose of COVID-19 vaccination was high among respondents from both rural Hard-to-reach (HTR) (92.9%) and non-HTR (94.6%) areas. However, the coverage for subsequent doses was observed to reduce significantly, especially for third dose (52.2% and 56.4% for HTR and non-HTR, respectively).ConclusionVaccination coverage among urbanites of high-risk group was found to be critically low. Vaccine hesitancy was also found to be high among individuals of this group. It is essential that the individuals of urban high-risk group be prioritized. Individuals from this group could be provided incentives (transport for disabled, monetary incentive to transgenders; food and medicine for drug user and floating people) and vaccination centers could be established with flexible schedule (morning/afternoon/evening sessions) so that they receive vaccine at their convenient time. Community engagement can be used for both high-risk group and rural population to enhance the COVID-19 vaccination coverage and lower disparities in uptake of the vaccine doses nationwide.

  9. U

    U.S. Vaccines Market Report

    • marketresearchforecast.com
    doc, pdf, ppt
    Updated Apr 2, 2025
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    Market Research Forecast (2025). U.S. Vaccines Market Report [Dataset]. https://www.marketresearchforecast.com/reports/us-vaccines-market-516
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    ppt, doc, pdfAvailable download formats
    Dataset updated
    Apr 2, 2025
    Dataset authored and provided by
    Market Research Forecast
    License

    https://www.marketresearchforecast.com/privacy-policyhttps://www.marketresearchforecast.com/privacy-policy

    Time period covered
    2025 - 2033
    Area covered
    United States
    Variables measured
    Market Size
    Description

    The U.S. vaccines market, currently exhibiting robust growth, is projected to maintain a significant upward trajectory throughout the forecast period (2025-2033). With a Compound Annual Growth Rate (CAGR) of 8.2%, the market's value, estimated at $XX billion in 2025, is expected to reach $YY billion by 2033 (Note: $XX and $YY billion are estimations based on the provided CAGR and assuming a consistent growth pattern; exact figures would require more specific market data). This expansion is fueled by several key drivers: increasing government initiatives promoting vaccination programs, rising prevalence of vaccine-preventable diseases, growing geriatric population requiring age-specific vaccines, and continuous advancements in vaccine technology, particularly in mRNA and viral vector platforms. The market's diverse segmentation, encompassing various vaccine types (live attenuated, mRNA, viral vectors, toxoid, others), routes of administration (parenteral, oral), disease indications (viral and bacterial diseases targeting specific age groups), and distribution channels (hospitals, retail pharmacies, government suppliers), presents lucrative opportunities for market players. Despite the positive outlook, several factors could restrain market growth. These include vaccine hesitancy and misinformation, stringent regulatory approvals for new vaccines, high research and development costs associated with novel vaccine development, and potential supply chain disruptions. However, the continuous efforts from public health organizations to educate the public on vaccination benefits, alongside ongoing innovations to improve vaccine efficacy, safety, and accessibility, are anticipated to mitigate these challenges. Key players like GSK, Sanofi, Pfizer, Merck, and Novartis, among others, are actively investing in research and development, strategic partnerships, and expansion strategies to solidify their market positions and capitalize on emerging trends within this dynamic and vital healthcare sector. The market's strong growth prospects are underpinned by the enduring importance of vaccines in public health and the commitment to improving global immunization coverage. Recent developments include: October 2023: Sanofi entered an agreement with Janssen Pharmaceuticals, Inc. to develop and commercialize a phase III vaccine product indicated against extraintestinal pathogenic E. coli., March 2023: CSL Limited established a new state-of-the-art vaccine R&D center in Massachusetts. The R&D facility is equipped with 54,000 square feet of lab space, comprising BSL-3 safety level., October 2022: GSK plc. received approval from the U.S. FDA for its vaccine, Menveo, with single vial presentation for individuals suffering from invasive meningococcal disease. The vaccine is intended for patients aged 10 years to 55 years.. Key drivers for this market are: Large Production of Products Coupled with New Approvals and Launches to Propel Market Growth. Potential restraints include: Long Production Cycle Coupled With High Cost of Production May Hinder Market Growth. Notable trends are: Shifting Preference toward mRNA-Based Products.

  10. Inactivated Vaccine Market Report | Global Forecast From 2025 To 2033

    • dataintelo.com
    csv, pdf, pptx
    Updated Jan 7, 2025
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    Dataintelo (2025). Inactivated Vaccine Market Report | Global Forecast From 2025 To 2033 [Dataset]. https://dataintelo.com/report/global-inactivated-vaccine-market
    Explore at:
    pdf, csv, pptxAvailable download formats
    Dataset updated
    Jan 7, 2025
    Dataset authored and provided by
    Dataintelo
    License

    https://dataintelo.com/privacy-and-policyhttps://dataintelo.com/privacy-and-policy

    Time period covered
    2024 - 2032
    Area covered
    Global
    Description

    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

  11. P

    Polio Vaccines Report

    • archivemarketresearch.com
    doc, pdf, ppt
    Updated Jun 5, 2025
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    Archive Market Research (2025). Polio Vaccines Report [Dataset]. https://www.archivemarketresearch.com/reports/polio-vaccines-346403
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    pdf, doc, pptAvailable download formats
    Dataset updated
    Jun 5, 2025
    Dataset authored and provided by
    Archive Market Research
    License

    https://www.archivemarketresearch.com/privacy-policyhttps://www.archivemarketresearch.com/privacy-policy

    Time period covered
    2025 - 2033
    Area covered
    Global
    Variables measured
    Market Size
    Description

    The global polio vaccine market, currently valued at $850.6 million in 2025, is poised for significant growth. While a precise CAGR isn't provided, considering the ongoing efforts to eradicate polio and the consistent demand for vaccines in both developed and developing nations, a conservative estimate of a 5-7% CAGR over the forecast period (2025-2033) appears reasonable. This growth will be fueled by several key drivers, including increasing government initiatives for mass vaccination campaigns, rising awareness about the devastating effects of polio, and advancements in vaccine technology leading to more effective and safer formulations. Furthermore, the expanding global population, particularly in regions with high polio risk, contributes to sustained demand. However, challenges such as vaccine hesitancy in certain populations, logistical hurdles in vaccine distribution, particularly in remote areas, and the emergence of vaccine-derived poliovirus (VDPV) present potential restraints on market growth. The market is segmented by vaccine type (inactivated poliovirus vaccine (IPV) and oral poliovirus vaccine (OPV)), route of administration, and end-user (hospitals, clinics, and vaccination centers). Major players like CSL, GlaxoSmithKline, Johnson & Johnson, MedImmune, Merck, Pfizer, Sanofi Pasteur, and the Serum Institute are driving innovation and expanding their global reach. Regional variations in market share will likely reflect the epidemiological landscape, with regions experiencing higher polio incidence experiencing greater demand. The long-term outlook remains positive, driven by ongoing global eradication efforts and a continued need for robust vaccination programs to prevent the resurgence of this debilitating disease.

  12. United States COVID-19 Community Levels by County

    • data.cdc.gov
    • data.virginia.gov
    • +1more
    application/rdfxml +5
    Updated Nov 2, 2023
    + more versions
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    CDC COVID-19 Response (2023). United States COVID-19 Community Levels by County [Dataset]. https://data.cdc.gov/Public-Health-Surveillance/United-States-COVID-19-Community-Levels-by-County/3nnm-4jni
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    application/rdfxml, application/rssxml, csv, tsv, xml, jsonAvailable download formats
    Dataset updated
    Nov 2, 2023
    Dataset provided by
    Centers for Disease Control and Preventionhttp://www.cdc.gov/
    Authors
    CDC COVID-19 Response
    License

    https://www.usa.gov/government-workshttps://www.usa.gov/government-works

    Area covered
    United States
    Description

    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,

  13. Weekly Cumulative Estimated Number of COVID-19 Vaccinations Administered in...

    • data.cdc.gov
    • healthdata.gov
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    application/rdfxml +5
    Updated May 16, 2025
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    National Center for Immunization and Respiratory Diseases (NCIRD) (2025). Weekly Cumulative Estimated Number of COVID-19 Vaccinations Administered in Pharmacies and Physician Medical Offices, Adults 18 years and older, by Season and Age Group, United States [Dataset]. https://data.cdc.gov/Vaccinations/Weekly-Cumulative-Estimated-Number-of-COVID-19-Vac/ewpg-rz7g
    Explore at:
    csv, application/rssxml, tsv, xml, json, application/rdfxmlAvailable download formats
    Dataset updated
    May 16, 2025
    Dataset provided by
    National Center for Immunization and Respiratory Diseases
    Authors
    National Center for Immunization and Respiratory Diseases (NCIRD)
    License

    https://www.usa.gov/government-workshttps://www.usa.gov/government-works

    Area covered
    United States
    Description
    • Weekly Cumulative Estimated Number of COVID-19 Vaccinations Administered in Pharmacies and Physical Medical Offices, Adults 18 Years and Older, United States

    • Estimated number of COVID-19 vaccinations among adults 18 years and older is assessed through IQVIA (https://www.iqvia.com/) as a source of information on vaccinations administered in retail pharmacies (include chain, mass merchandise, stores, and independent pharmacies) and physician medical offices.

  14. f

    Multiple logistic regression model for household survey and survey of...

    • figshare.com
    xls
    Updated Apr 29, 2024
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    Zerin Jannat; Hemel Das; Md. Wazed Ali; Tasnuva Wahed; Md. Nurul Alam; Md. Jasim Uddin (2024). Multiple logistic regression model for household survey and survey of vulnerable people by doses. [Dataset]. http://doi.org/10.1371/journal.pone.0302056.t005
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Apr 29, 2024
    Dataset provided by
    PLOS ONE
    Authors
    Zerin Jannat; Hemel Das; Md. Wazed Ali; Tasnuva Wahed; Md. Nurul Alam; Md. Jasim Uddin
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Multiple logistic regression model for household survey and survey of vulnerable people by doses.

  15. Weekly Cumulative Estimated Number of RSV Vaccinations Administered in...

    • data.cdc.gov
    • data.virginia.gov
    • +1more
    application/rdfxml +5
    Updated May 16, 2025
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    National Center for Immunization and Respiratory Diseases (NCIRD) (2025). Weekly Cumulative Estimated Number of RSV Vaccinations Administered in Retail Pharmacies and Physicians’ Medical Offices, Adults 60 to 74 Years and 75 years and older, United States [Dataset]. https://data.cdc.gov/Vaccinations/Weekly-Cumulative-Estimated-Number-of-RSV-Vaccinat/hea5-6w9c
    Explore at:
    tsv, csv, application/rdfxml, json, xml, application/rssxmlAvailable download formats
    Dataset updated
    May 16, 2025
    Dataset provided by
    National Center for Immunization and Respiratory Diseases
    Authors
    National Center for Immunization and Respiratory Diseases (NCIRD)
    License

    https://www.usa.gov/government-workshttps://www.usa.gov/government-works

    Area covered
    United States
    Description

    •Weekly Cumulative Estimated Number of RSV Vaccinations Administered in Retail Pharmacies and Physicians’ Medical Offices, Adults 60 to 74 Years and 75 Years and Older, United States

    • Estimated Number of RSV vaccinations among adults 60 years and older is assessed through IQVIA (https://www.iqvia.com/) as a source of information on vaccinations administered in retail pharmacies (include chain, mass merchandise, food stores, and independent pharmacies) and physician medical offices.

  16. f

    Characteristics of diphtheria cases by case definition among Rohingya...

    • figshare.com
    xls
    Updated Jun 5, 2023
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    Jonathan A. Polonsky; Melissa Ivey; Md. Khadimul Anam Mazhar; Ziaur Rahman; Olivier le Polain de Waroux; Basel Karo; Katri Jalava; Sirenda Vong; Amrish Baidjoe; Janet Diaz; Flavio Finger; Zakir H. Habib; Charls Erik Halder; Christopher Haskew; Laurent Kaiser; Ali S. Khan; Lucky Sangal; Tahmina Shirin; Quazi Ahmed Zaki; Md. Abdus Salam; Kate White (2023). Characteristics of diphtheria cases by case definition among Rohingya refugees, Cox’s Bazar, Bangladesh, November 10, 2017 to November 10, 2019. [Dataset]. http://doi.org/10.1371/journal.pmed.1003587.t001
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    xlsAvailable download formats
    Dataset updated
    Jun 5, 2023
    Dataset provided by
    PLOS Medicine
    Authors
    Jonathan A. Polonsky; Melissa Ivey; Md. Khadimul Anam Mazhar; Ziaur Rahman; Olivier le Polain de Waroux; Basel Karo; Katri Jalava; Sirenda Vong; Amrish Baidjoe; Janet Diaz; Flavio Finger; Zakir H. Habib; Charls Erik Halder; Christopher Haskew; Laurent Kaiser; Ali S. Khan; Lucky Sangal; Tahmina Shirin; Quazi Ahmed Zaki; Md. Abdus Salam; Kate White
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Cox's Bazar, Bangladesh
    Description

    Characteristics of diphtheria cases by case definition among Rohingya refugees, Cox’s Bazar, Bangladesh, November 10, 2017 to November 10, 2019.

  17. Weekly Cumulative Estimated Number of Influenza Vaccinations Administered in...

    • data.cdc.gov
    • healthdata.gov
    • +1more
    application/rdfxml +5
    Updated May 24, 2024
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    National Center for Immunization and Respiratory Diseases (NCIRD) (2024). Weekly Cumulative Estimated Number of Influenza Vaccinations Administered in Pharmacies and Physician Medical Offices, Adults 18 years and older, United States [Dataset]. https://data.cdc.gov/Vaccinations/Weekly-Cumulative-Estimated-Number-of-Influenza-Va/83ng-twza
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    json, csv, application/rdfxml, tsv, application/rssxml, xmlAvailable download formats
    Dataset updated
    May 24, 2024
    Dataset provided by
    National Center for Immunization and Respiratory Diseases
    Authors
    National Center for Immunization and Respiratory Diseases (NCIRD)
    License

    https://www.usa.gov/government-workshttps://www.usa.gov/government-works

    Area covered
    United States
    Description

    Weekly Cumulative Estimated Number of Influenza Vaccinations Administered in Pharmacies and Physician Medical Offices, Adults 18 years and older, United States

    • Archived data are here: https://data.cdc.gov/resource/uxgd-cqqc

    • CDC is exploring use of data obtained from IQVIA§ (https://www.iqvia.com/) as a source of information on vaccinations administered in retail pharmacies (include chain, mass merchandise, food stores, and independent pharmacies) and physician medical offices.

    • These projected pharmacy estimates include flu vaccinations that were billed for (i.e. claims) or paid by cash. Medical office projected estimates are claims-based only.

    • The sampled pharmacies and physician medical offices and the captured volume of transactions represent approximately 92% and 82% of influenza vaccines administered nationally, respectively.

    • Vaccinations administered in other settings such as workplaces and community settings are not included in these data.

    *National estimates for pharmacies and medical offices include vaccinations administered in 50 states and DC. National estimates for medical office vaccinations do not include doses where geographic information (i.e. which state the dose was administered in) was missing. Pharmacy data are through Friday of each week and medical office data are through Saturday of each week. Week ending dates for prior seasons are aligned with the current season’s week ending dates.

    § 1) King, L. M., Bartoces, M., Fleming-Dutra, K. E., et. al, L. A. (2020). Changes in US outpatient antibiotic prescriptions from 2011–2016external icon. Clinical Infectious Diseases, 70(3), 370-377. 2) McLaughlin, J. M., Swerdlow, D. L., Khan, F., et. Al (2019). Disparities in uptake of 13-valent pneumococcal conjugate vaccine among older adults in the United Statesexternal icon. Human vaccines & immunotherapeutics, 15(4), 841-849.

  18. f

    Number (%) of signs and symptoms, complications, and treatment outcomes...

    • figshare.com
    xls
    Updated Jun 11, 2023
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    Jonathan A. Polonsky; Melissa Ivey; Md. Khadimul Anam Mazhar; Ziaur Rahman; Olivier le Polain de Waroux; Basel Karo; Katri Jalava; Sirenda Vong; Amrish Baidjoe; Janet Diaz; Flavio Finger; Zakir H. Habib; Charls Erik Halder; Christopher Haskew; Laurent Kaiser; Ali S. Khan; Lucky Sangal; Tahmina Shirin; Quazi Ahmed Zaki; Md. Abdus Salam; Kate White (2023). Number (%) of signs and symptoms, complications, and treatment outcomes among diphtheria cases, by case definition, among Rohingya refugees, Cox’s Bazar, Bangladesh, November 10, 2017 to November 10, 2019. [Dataset]. http://doi.org/10.1371/journal.pmed.1003587.t002
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 11, 2023
    Dataset provided by
    PLOS Medicine
    Authors
    Jonathan A. Polonsky; Melissa Ivey; Md. Khadimul Anam Mazhar; Ziaur Rahman; Olivier le Polain de Waroux; Basel Karo; Katri Jalava; Sirenda Vong; Amrish Baidjoe; Janet Diaz; Flavio Finger; Zakir H. Habib; Charls Erik Halder; Christopher Haskew; Laurent Kaiser; Ali S. Khan; Lucky Sangal; Tahmina Shirin; Quazi Ahmed Zaki; Md. Abdus Salam; Kate White
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Cox's Bazar, Bangladesh
    Description

    Number (%) of signs and symptoms, complications, and treatment outcomes among diphtheria cases, by case definition, among Rohingya refugees, Cox’s Bazar, Bangladesh, November 10, 2017 to November 10, 2019.

  19. Preliminary 2024-2025 U.S. COVID-19 Burden Estimates

    • data.cdc.gov
    • data.virginia.gov
    • +1more
    application/rdfxml +5
    Updated Jun 6, 2025
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    Coronavirus and Other Respiratory Viruses Division (CORVD), National Center for Immunization and Respiratory Diseases (NCIRD). (2025). Preliminary 2024-2025 U.S. COVID-19 Burden Estimates [Dataset]. https://data.cdc.gov/Public-Health-Surveillance/Preliminary-2024-2025-U-S-COVID-19-Burden-Estimate/ahrf-yqdt
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    csv, application/rdfxml, json, application/rssxml, xml, tsvAvailable download formats
    Dataset updated
    Jun 6, 2025
    Dataset provided by
    National Center for Immunization and Respiratory Diseases
    Authors
    Coronavirus and Other Respiratory Viruses Division (CORVD), National Center for Immunization and Respiratory Diseases (NCIRD).
    License

    https://www.usa.gov/government-workshttps://www.usa.gov/government-works

    Area covered
    United States
    Description

    This dataset represents preliminary estimates of cumulative U.S. COVID-19 disease burden for the 2024-2025 period, including illnesses, outpatient visits, hospitalizations, and deaths. The weekly COVID-19-associated burden estimates are preliminary and based on continuously collected surveillance data from patients hospitalized with laboratory-confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections. The data come from the Coronavirus Disease 2019 (COVID-19)-Associated Hospitalization Surveillance Network (COVID-NET), a surveillance platform that captures data from hospitals that serve about 10% of the U.S. population. Each week CDC estimates a range (i.e., lower estimate and an upper estimate) of COVID-19 -associated burden that have occurred since October 1, 2024.

    Note: Data are preliminary and subject to change as more data become available. Rates for recent COVID-19-associated hospital admissions are subject to reporting delays; as new data are received each week, previous rates are updated accordingly.

    References

    1. Reed C, Chaves SS, Daily Kirley P, et al. Estimating influenza disease burden from population-based surveillance data in the United States. PLoS One. 2015;10(3):e0118369. https://doi.org/10.1371/journal.pone.0118369 
    2. Rolfes, MA, Foppa, IM, Garg, S, et al. Annual estimates of the burden of seasonal influenza in the United States: A tool for strengthening influenza surveillance and preparedness. Influenza Other Respi Viruses. 2018; 12: 132– 137. https://doi.org/10.1111/irv.12486
    3. Tokars JI, Rolfes MA, Foppa IM, Reed C. An evaluation and update of methods for estimating the number of influenza cases averted by vaccination in the United States. Vaccine. 2018;36(48):7331-7337. doi:10.1016/j.vaccine.2018.10.026 
    4. Collier SA, Deng L, Adam EA, Benedict KM, Beshearse EM, Blackstock AJ, Bruce BB, Derado G, Edens C, Fullerton KE, Gargano JW, Geissler AL, Hall AJ, Havelaar AH, Hill VR, Hoekstra RM, Reddy SC, Scallan E, Stokes EK, Yoder JS, Beach MJ. Estimate of Burden and Direct Healthcare Cost of Infectious Waterborne Disease in the United States. Emerg Infect Dis. 2021 Jan;27(1):140-149. doi: 10.3201/eid2701.190676. PMID: 33350905; PMCID: PMC7774540.
    5. Reed C, Kim IK, Singleton JA,  et al. Estimated influenza illnesses and hospitalizations averted by vaccination–United States, 2013-14 influenza season. MMWR Morb Mortal Wkly Rep. 2014 Dec 12;63(49):1151-4. https://www.cdc.gov/mmwr/preview/mmwrhtml/mm6349a2.htm 
    6. Reed C, Angulo FJ, Swerdlow DL, et al. Estimates of the Prevalence of Pandemic (H1N1) 2009, United States, April–July 2009. Emerg Infect Dis. 2009;15(12):2004-2007. https://dx.doi.org/10.3201/eid1512.091413
    7. Devine O, Pham H, Gunnels B, et al. Extrapolating Sentinel Surveillance Information to Estimate National COVID-19 Hospital Admission Rates: A Bayesian Modeling Approach. Influenza and Other Respiratory Viruses. https://onlinelibrary.wiley.com/doi/10.1111/irv.70026. Volume18, Issue10. October 2024.
    8. https://www.cdc.gov/covid/php/covid-net/index.html">COVID-NET | COVID-19 | CDC 
    9. https://www.cdc.gov/covid/hcp/clinical-care/systematic-review-process.html 
    10. https://academic.oup.com/pnasnexus/article/1/3/pgac079/6604394?login=false">Excess natural-cause deaths in California by cause and setting: March 2020 through February 2021 | PNAS Nexus | Oxford Academic (oup.com)
    11. Kruschke, J. K. 2011. Doing Bayesian data analysis: a tutorial with R and BUGS. Elsevier, Amsterdam, Section 3.3.5.

  20. Multivariable Poisson regression for predictors for diphtheria patients...

    • plos.figshare.com
    xls
    Updated Jun 10, 2023
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    Jonathan A. Polonsky; Melissa Ivey; Md. Khadimul Anam Mazhar; Ziaur Rahman; Olivier le Polain de Waroux; Basel Karo; Katri Jalava; Sirenda Vong; Amrish Baidjoe; Janet Diaz; Flavio Finger; Zakir H. Habib; Charls Erik Halder; Christopher Haskew; Laurent Kaiser; Ali S. Khan; Lucky Sangal; Tahmina Shirin; Quazi Ahmed Zaki; Md. Abdus Salam; Kate White (2023). Multivariable Poisson regression for predictors for diphtheria patients testing positive (as opposed to negative) for toxigenic C. diphtheriae strain by PCR, Cox’s Bazar, Bangladesh, November 10, 2017 to November 10, 2019. [Dataset]. http://doi.org/10.1371/journal.pmed.1003587.t004
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 10, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Jonathan A. Polonsky; Melissa Ivey; Md. Khadimul Anam Mazhar; Ziaur Rahman; Olivier le Polain de Waroux; Basel Karo; Katri Jalava; Sirenda Vong; Amrish Baidjoe; Janet Diaz; Flavio Finger; Zakir H. Habib; Charls Erik Halder; Christopher Haskew; Laurent Kaiser; Ali S. Khan; Lucky Sangal; Tahmina Shirin; Quazi Ahmed Zaki; Md. Abdus Salam; Kate White
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Cox's Bazar, Bangladesh
    Description

    Multivariable Poisson regression for predictors for diphtheria patients testing positive (as opposed to negative) for toxigenic C. diphtheriae strain by PCR, Cox’s Bazar, Bangladesh, November 10, 2017 to November 10, 2019.

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Feng Qi; Daniela Barragan; Maverick Garcia Rodriguez; Jiongcheng Lu (2023). Data_Sheet_1_Evaluating spatial accessibility to COVID-19 vaccine resources in diversely populated counties in the United States.PDF [Dataset]. http://doi.org/10.3389/fpubh.2022.895538.s001

Data_Sheet_1_Evaluating spatial accessibility to COVID-19 vaccine resources in diversely populated counties in the United States.PDF

Related Article
Explore at:
pdfAvailable download formats
Dataset updated
Jun 3, 2023
Dataset provided by
Frontiers
Authors
Feng Qi; Daniela Barragan; Maverick Garcia Rodriguez; Jiongcheng Lu
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Area covered
United States
Description

This study examines the accessibility to COVID-19 vaccination resources in two counties surrounding Newark, NJ in the New York Metropolitan Area, United States. The study area represents diverse population makeups. COVID-19 vaccines were made available by different types of vaccination sites including county mass vaccination sites, medical facilities and pharmacies, and a FEMA community vaccination center in spring 2021. We used the two-step floating catchment area method to measure accessibility and calculated the average accessibility scores of different population groups. We examined the patterns and tested the significance of the differences in accessibility across population groups. The results showed clear spatial heterogeneity in the accessibility to vaccine resources with the existing infrastructure (medical/pharmacy vaccine sites). Accessibility patterns changed with the introduction of county mass sites and the FEMA community site. The county mass vaccination sites in one county greatly increased accessibilities for populations of minority and poverty. The FEMA community site in the other county accomplished the same. Both the local health department and the federal government played an important role in mitigating pre-existing inequalities during the vaccination campaign. Our study shows that social determinants of health need to be addressed and taken into explicit consideration when planning resource distribution during the pandemic.

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