5 datasets found
  1. COVID-19 State Profile Report - Maryland

    • s.cnmilf.com
    • data.virginia.gov
    • +3more
    Updated Jul 4, 2025
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    U.S. Department of Health and Human Services (2025). COVID-19 State Profile Report - Maryland [Dataset]. https://s.cnmilf.com/user74170196/https/catalog.data.gov/dataset/covid-19-state-profile-report-maryland
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    Dataset updated
    Jul 4, 2025
    Dataset provided by
    United States Department of Health and Human Serviceshttp://www.hhs.gov/
    Area covered
    Maryland
    Description

    After over two years of public reporting, the State Profile Report will no longer be produced and distributed after February 2023. The final release was on February 23, 2023. We want to thank everyone who contributed to the design, production, and review of this report and we hope that it provided insight into the data trends throughout the COVID-19 pandemic. Data about COVID-19 will continue to be updated at CDC’s COVID Data Tracker. The State Profile Report (SPR) is generated by the Data Strategy and Execution Workgroup in the Joint Coordination Cell, in collaboration with the White House. It is managed by an interagency team with representatives from multiple agencies and offices (including the United States Department of Health and Human Services (HHS), the Centers for Disease Control and Prevention, the HHS Assistant Secretary for Preparedness and Response, and the Indian Health Service). The SPR provides easily interpretable information on key indicators for each state, down to the county level. It is a weekly snapshot in time that: Focuses on recent outcomes in the last seven days and changes relative to the month prior Provides additional contextual information at the county level for each state, and includes national level information Supports rapid visual interpretation of results with color thresholds

  2. V

    Dataset from A Phase 1/2 Study of Delayed Heterologous SARS-CoV-2 Vaccine...

    • data.niaid.nih.gov
    Updated Feb 10, 2025
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    ImmPort (a data-sharing platform funded by the National Institutes of Health); Kirsten E Lyke, M.D.; Robert L Atmar, M.D. (2025). Dataset from A Phase 1/2 Study of Delayed Heterologous SARS-CoV-2 Vaccine Dosing (Boost) After Receipt of EUA Vaccines [Dataset]. http://doi.org/10.25934/PR00010057
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    Dataset updated
    Feb 10, 2025
    Dataset provided by
    University of Maryland School of Medicine, Center for Vaccine Development and Global Health
    Baylor College of Medicine
    Authors
    ImmPort (a data-sharing platform funded by the National Institutes of Health); Kirsten E Lyke, M.D.; Robert L Atmar, M.D.
    Area covered
    United States
    Variables measured
    Adverse Event, Chronic Disease, SARS-CoV-2 Antibody, Serious Adverse Event
    Description

    A phase 1/2, open-label clinical trial in individuals, 18 years of age and older, who are in good health, have no known history of Coronavirus Disease 2019 (COVID-19) or Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection, and meet all other eligibility criteria. This clinical trial is designed to assess the safety, reactogenicity and immunogenicity of a delayed (>/=12 weeks) vaccine boost on a range of Emergency Use Authorization (EUA)-dosed COVID-19 vaccines (mRNA-1273, and mRNA-1273.211 manufactured by ModernaTX, Inc.; BNT162b2 manufactured by Pfizer/BioNTech; or Ad26.COV2.S manufactured by Janssen Pharmaceuticals/Johnson & Johnson). This is an adaptive design and may add arms (and increase sample size) as vaccines are awarded EUA and/or variant lineage spike vaccines are manufactured or become available. Enrollment will occur at up to twelve domestic clinical research sites.

    This study includes two cohorts. Cohort 1 will include approximately 880 individuals (50 subjects/group; Groups 1E-11E) greater than 18 years of age and older, stratified into two age strata (18-55 years and >/=56 years) who previously received COVID-19 vaccine at Emergency Use Authorization dosing (EUA) (two vaccinations of mRNA-1273 at the 100 mcg dose, two vaccinations of BNT162b2 at the 30 mcg dose, or one vaccination of Ad26.COV2.S at the 5x10^10 vp dose). Groups 15E-17E will enroll 60 subjects, split (approximately evenly) between age strata as able. Those subjects will be offered enrollment into this study >/=12 weeks after they received the last dose of their EUA vaccine. Subjects will receive a single open-label intramuscular (IM) injection of the designated delayed booster vaccine and will be followed through 12 months after vaccination: 1) Group 1E - previously EUA-dosed vaccination with Janssen - Ad26.COV.2.S at 5x10^10 vp followed by a 100-mcg dose of mRNA-1273, Group 4E - previously EUA-dosed vaccination with Janssen - Ad26.COV.2.S at 5x10^10 vp followed by a 5x10^10 vp dose of Ad26.COV2.S, Group 7E - previously EUA-dosed vaccination with Janssen - Ad26.COV.2.S 5x10^10 vp followed by a 30-mcg dose of BNT162b2, Group 10E - previously EUA-dosed vaccination with Janssen - Ad26.COV2-S 5x10^10 vp followed by a 100-mcg dose of mRNA-1273.211; Group 12E - previously EUA-dosed vaccination with Janssen - Ad26.COV2-S 5x10^10 vp followed by a 50-mcg dose of mRNA-1273; Group 15E - previously EUA-dosed vaccination with Janssen (two doses for Group 15E) - Ad26.COV2.S at 5x1010 vp followed by a dose of NVX-CoV2373 (5 mcg Prototype SARS-CoV-2 rS vaccine with 50 mcg Matrix-M); 2) Group 2E - previously EUA-dosed vaccination with Moderna - mRNA-1273 at 100 mcg for two doses followed by a 100-mcg dose of mRNA-1273, Group 5E - previously EUA-dosed vaccination with Moderna - mRNA-1273 at 100 mcg for two doses followed by a 5x10^10 vp dose of Ad26.COV2.S, Group 8E - previously EUA-dosed vaccination with Moderna - mRNA-1273 at 100 mcg for two doses followed by a 30-mcg dose of BNT162b2, Group 13E - previously EUA-dosed vaccination with Moderna - mRNA-1273 at 100 mcg for two doses followed by a 50-mcg dose of mRNA-1273; Group 16E - previously EUA-dosed vaccination with Moderna - mRNA-1273 at 100 mcg for two doses followed by a dose of NVX-CoV2373 (5 mcg Prototype SARS-CoV2 rS vaccine with 50 mcg Matrix-M); 3) Group 3E - previously EUA-dosed vaccination with Pfizer/BioNTech - BNT162b2 at 30 mcg for two doses followed by a 100-mcg dose of mRNA-1273. Group 6E - previously EUA-dosed vaccination with Pfizer/BioNTech - BNT162b2 at 30 mcg for two doses followed by a 5x10^10 vp dose of Ad26.COV2.S, Group 9E - previously EUA-dosed vaccination with Pfizer/BioNTech - BNT162b2 at 30 mcg for two doses followed by a 30-mcg dose of BNT162b2, Group 11E - previously EUA-dosed vaccination with Pfizer/BioNTech - BNT162b2 at 30 mcg for two doses followed by a 100-mcg dose of mRNA-1273.211. Group 14E - previously EUA-dosed vaccination with Pfizer/BioNTech - BNT162b2 at 30 mcg for two doses followed by a 50-mcg dose of mRNA-1273, Group 17E - previously EUA-dosed vaccination with Pfizer/BioNTech - BNT162b2 at 30 mcg for two doses followed by a dose of NVX-CoV2373 (5 mcg Prototype SARS-CoV2 rS vaccine with 50 mcg Matrix-M).

    A telephone visit will occur one week after each primary EUA vaccination and one week after the booster dose. In person follow-up visits will occur on 14 days following completion of EUA vaccinations and on days 14, and 28 days after the booster dose, as well as 3, 6, and 12 months post the booster vaccination. Additional pools of subjects can be included if needed as additional COVID-19 vaccines are awarded EUA.

    The primary objectives of this study are 1) to evaluate the safety and reactogenicity of delayed heterologous or homologous vaccine doses after EUA dosed vaccines, and 2) to evaluate the breadth of the humoral immune responses of heterologous and homologous delayed boost regimens following EUA dosing.

  3. Data from: COVID-CT-MD: COVID-19 Computed Tomography Scan Dataset Applicable...

    • springernature.figshare.com
    bin
    Updated Apr 20, 2021
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    Anastasia Oikonomou; Konstantinos Plataniotis; Arash Mohammadi; Parnian Afshar; Farnoosh Naderkhani; Shahin Heidarian; Nastaran Enshaei; Moezedin Javad Rafiee; Faranak Babaki Fard; Kaveh Samimi (2021). COVID-CT-MD: COVID-19 Computed Tomography Scan Dataset Applicable in Machine Learning and Deep Learning [Dataset]. http://doi.org/10.6084/m9.figshare.12991592.v1
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    binAvailable download formats
    Dataset updated
    Apr 20, 2021
    Dataset provided by
    Figsharehttp://figshare.com/
    Authors
    Anastasia Oikonomou; Konstantinos Plataniotis; Arash Mohammadi; Parnian Afshar; Farnoosh Naderkhani; Shahin Heidarian; Nastaran Enshaei; Moezedin Javad Rafiee; Faranak Babaki Fard; Kaveh Samimi
    License

    CC0 1.0 Universal Public Domain Dedicationhttps://creativecommons.org/publicdomain/zero/1.0/
    License information was derived automatically

    Description

    COVID-19, CAP and Normal subjects are placed in separate folders, within which patients are arranged in folders, followed by CT scan slices in DICOM format. Index.csv is related to the patients having slice-level and lobe-level labels. The indices given to patients in Index.csv file are then used in Slice-level-labels.npy and Lobe-level-labels.npy to indicate the slice and lobe labels. Slice-level-labels.npy is a 2D binary Numpy array in which the existence of infection in a specific slice is indicated by 1 and the lack of infection is shown by 0. In Slice-level-labels.npy, the first dimension represents the case index and the second one represents the slice numbers. Lobe-level-labels.npy is a 3D binary Numpy array in which the existence of infection in a specific lobe and slice is determined by 1 in the corresponding element of the array. Like the slice-level array, in Lobe-level-labels.npy, the two first dimensions represent the case index and slice numbers respectively. The third dimension shows the lobe indices which are specified as follows: 0 : Left Lower Lobe (LLL) 1 : Left Upper Lobe (LUL) 2 : Right Lower Lobe (RLL) 3 : Right Middle Lobe (RML) 4 : Right Upper Lobe (RUL) It is worth noting that CT slices are sorted based on the "Slice Location" value stored in the corresponding DICOM tag "(0020,1041) - DS - Slice Location". The slice-level and lobe-level labels are provided according to described slice order. The researchers, however, can re-arrange the slices using other CT attributes based on their preference, as long as they re-arrange the labels accordingly. The COVID-CT-MD dataset is also accompanied with the clinical data, stored in "Clinical-data.csv". Finally, to facilitate the inter-observer reliability studies, labels assigned by the three radiologists are separately provided in "Radiogists-seperated-labels.csv".

  4. Socio-demographic and media related variables among respondents with level...

    • plos.figshare.com
    xls
    Updated Jun 10, 2023
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    Md. Bakebillah; Md. Arif Billah; Befikadu L. Wubishet; Md. Nuruzzaman Khan (2023). Socio-demographic and media related variables among respondents with level of COVID-19 related misconception, Satkhira district- Bangladesh, 2020. [Dataset]. http://doi.org/10.1371/journal.pone.0257410.t003
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    xlsAvailable download formats
    Dataset updated
    Jun 10, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Md. Bakebillah; Md. Arif Billah; Befikadu L. Wubishet; Md. Nuruzzaman Khan
    License

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

    Area covered
    Satkhira District, Bangladesh
    Description

    Socio-demographic and media related variables among respondents with level of COVID-19 related misconception, Satkhira district- Bangladesh, 2020.

  5. S1 Data -

    • plos.figshare.com
    xlsx
    Updated Dec 20, 2023
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    Muhammad Mainuddin Patwary; Asma Safia Disha; Mahadi Hasan; Mondira Bardhan; Mehedi Hasan; Faiza Imam Tuhi; Sama Jamila Rahim; Md. Navid Newaz; Sardar Al Imran; Md. Zahidul Haque; Md. Riad Hossain; Md Pervez Kabir; Sarya Swed (2023). S1 Data - [Dataset]. http://doi.org/10.1371/journal.pone.0290412.s001
    Explore at:
    xlsxAvailable download formats
    Dataset updated
    Dec 20, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Muhammad Mainuddin Patwary; Asma Safia Disha; Mahadi Hasan; Mondira Bardhan; Mehedi Hasan; Faiza Imam Tuhi; Sama Jamila Rahim; Md. Navid Newaz; Sardar Al Imran; Md. Zahidul Haque; Md. Riad Hossain; Md Pervez Kabir; Sarya Swed
    License

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

    Description

    IntroductionThe vaccination against coronavirus disease 2019 (COVID-19) has been identified as a promising strategy to reduce the severity of the pandemic. Despite the safe and effective COVID-19 vaccines, bringing socioeconomically disadvantaged people under vaccination coverage has been challenging for developing countries like Bangladesh. Therefore, this study explored the determinants of vaccine acceptance among urban slum residents of Bangladesh using the Health Belief Model (HBM) and Theory of Planned Behavior (TPB).MethodsA face-to-face survey of 400 urban slum dwellers in two large cities in Bangladesh was conducted between July 5 to August 5, 2021. The questionnaire included vaccine acceptance, socio-demographics, health-related characteristics, trust in health authorities, reasons for vaccine hesitancy, and dimensions of HBM and TPB frameworks. Hierarchical logistic regression was performed to evaluate the association between these characteristics and vaccination acceptance.ResultsAround 82% (n = 327) of respondents were willing to accept the COVID-19 vaccine. In a fully adjusted model, respondents with secondary level education had higher intention (OR = 46.93, 95%CI = 1.21–1807.90, p < 0. 05) to accept COVID-19 vaccine. Respondents with bad (OR = 0.11, 95%CI = 0.01–0.35, p

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U.S. Department of Health and Human Services (2025). COVID-19 State Profile Report - Maryland [Dataset]. https://s.cnmilf.com/user74170196/https/catalog.data.gov/dataset/covid-19-state-profile-report-maryland
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COVID-19 State Profile Report - Maryland

Explore at:
Dataset updated
Jul 4, 2025
Dataset provided by
United States Department of Health and Human Serviceshttp://www.hhs.gov/
Area covered
Maryland
Description

After over two years of public reporting, the State Profile Report will no longer be produced and distributed after February 2023. The final release was on February 23, 2023. We want to thank everyone who contributed to the design, production, and review of this report and we hope that it provided insight into the data trends throughout the COVID-19 pandemic. Data about COVID-19 will continue to be updated at CDC’s COVID Data Tracker. The State Profile Report (SPR) is generated by the Data Strategy and Execution Workgroup in the Joint Coordination Cell, in collaboration with the White House. It is managed by an interagency team with representatives from multiple agencies and offices (including the United States Department of Health and Human Services (HHS), the Centers for Disease Control and Prevention, the HHS Assistant Secretary for Preparedness and Response, and the Indian Health Service). The SPR provides easily interpretable information on key indicators for each state, down to the county level. It is a weekly snapshot in time that: Focuses on recent outcomes in the last seven days and changes relative to the month prior Provides additional contextual information at the county level for each state, and includes national level information Supports rapid visual interpretation of results with color thresholds

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