6 datasets found
  1. f

    Data_Sheet_1_Addressing COVID-19 Testing Inequities Among Underserved...

    • frontiersin.figshare.com
    pdf
    Updated Jun 4, 2023
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    Rebekka M. Lee; Veronica L. Handunge; Samantha L. Augenbraun; Huy Nguyen; Cristina Huebner Torres; Alyssa Ruiz; Karen M. Emmons; for the RADx-MA Research Partnership (2023). Data_Sheet_1_Addressing COVID-19 Testing Inequities Among Underserved Populations in Massachusetts: A Rapid Qualitative Exploration of Health Center Staff, Partner, and Resident Perceptions.PDF [Dataset]. http://doi.org/10.3389/fpubh.2022.838544.s001
    Explore at:
    pdfAvailable download formats
    Dataset updated
    Jun 4, 2023
    Dataset provided by
    Frontiers
    Authors
    Rebekka M. Lee; Veronica L. Handunge; Samantha L. Augenbraun; Huy Nguyen; Cristina Huebner Torres; Alyssa Ruiz; Karen M. Emmons; for the RADx-MA Research Partnership
    License

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

    Area covered
    Massachusetts
    Description

    IntroductionAccess to COVID-19 testing has been inequitable and misaligned with community need. However, community health centers have played a critical role in addressing the COVID-19 testing needs of historically disadvantaged communities. The aim of this paper is to explore the perceptions of COVID-19 testing barriers in six Massachusetts communities that are predominantly low income and describe how these findings were used to build tailored clinical-community strategies to addressing testing inequities.MethodsBetween November 2020 and February 2021, we conducted 84 semi-structured qualitative interviews with 107 community health center staff, community partners, and residents. Resident interviews were conducted in English, Spanish, Vietnamese, and Arabic. We used a 2-phase framework analysis to analyze the data, including deductive coding to facilitate rapid analysis for action and an in-depth thematic analysis applying the Social Ecological Model.ResultsThrough the rapid needs assessment, we developed cross-site suggestions to improve testing implementation and communications, as well as community-specific recommendations (e.g., locations for mobile testing sites and local communication channels). Upstream barriers identified in the thematic analysis included accessibility of state-run testing sites, weak social safety nets, and lack of testing supplies and staffing that contributed to long wait times. These factors hindered residents' abilities to get tested, which was further exacerbated by individual fears surrounding the testing process and limited knowledge on testing availability.DiscussionOur rapid, qualitative approach created the foundation for implementing strategies that reached underserved populations at the peak of the COVID-19 pandemic in winter 2021. We explored perceptions of testing barriers and created actionable summaries within 1–2 months of data collection. Partnering community health centers in Massachusetts were able to use these data to respond to the local needs of each community. This study underscores the substantial impact of upstream, structural disparities on the individual experience of COVID-19 and demonstrates the utility of shifting from a typical years' long research translation process to a rapid approach of using data for action.

  2. m

    COVID-19 reporting

    • mass.gov
    Updated Dec 4, 2023
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    Executive Office of Health and Human Services (2023). COVID-19 reporting [Dataset]. https://www.mass.gov/info-details/covid-19-reporting
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    Dataset updated
    Dec 4, 2023
    Dataset provided by
    Executive Office of Health and Human Services
    Department of Public Health
    Area covered
    Massachusetts
    Description

    The COVID-19 dashboard includes data on city/town COVID-19 activity, confirmed and probable cases of COVID-19, confirmed and probable deaths related to COVID-19, and the demographic characteristics of cases and deaths.

  3. O

    COVID-19 Case Type Breakdown 5/11/2023 (Historical)

    • data.cambridgema.gov
    application/rdfxml +5
    Updated May 11, 2023
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    Cambridge Department of Public Health (2023). COVID-19 Case Type Breakdown 5/11/2023 (Historical) [Dataset]. https://data.cambridgema.gov/Public-Health/COVID-19-Case-Type-Breakdown-5-11-2023-Historical-/ikju-95st
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    csv, application/rssxml, application/rdfxml, json, xml, tsvAvailable download formats
    Dataset updated
    May 11, 2023
    Dataset authored and provided by
    Cambridge Department of Public Health
    Description

    This dataset is no longer being updated as of 5/11/2023. It is being retained on the Open Data Portal for its potential historical interest.

    This table reports case classification and status data.

    The "test mode" rows show confirmed and probable case counts for all Cambridge residents who have tested positive for COVID-19 or have been clinically diagnosed with the disease to date. The numbers represented in these rows reflect individual people (cases), not tests performed. If someone is clinically diagnosed and later gets an antibody test, for example, they will be removed from the “clinical diagnosis” category and added to the “antibody positive” category. Case classification is based on guidance from the Massachusetts Department of Public Health and is as follows:

    Confirmed Case: A person with a positive viral (PCR) test for COVID-19. This test is also known as a molecular test.

    Probable Case: A person with a positive antigen test. This test is also known as a rapid test. A person who is a known contact of a confirmed case and has received a clinical diagnosis based on their symptoms. People in this category have not received a viral or antibody test. Whenever possible, lab results from a viral (PCR) test are used to confirm a clinical diagnosis, and if that is not feasible, antibody testing can be used.

    Suspect Case: A person with a positive antibody test. This test is also known as a serology test.

    The "case status" rows show current outcomes for all Cambridge residents who are classified as confirmed, probable, or suspect COVID-19 cases. Outcomes include:

    Recovered Case: The Cambridge Public Health Department determines if a Cambridge COVID-19 case has recovered based on the Center for Disease Control and Prevention’s criteria for ending home isolation: https://www.cdc.gov/coronavirus/2019-ncov/hcp/disposition-in-home-patients.html. Staff from the Cambridge Public Health Department (CPHD) or the state’s Community Tracing Collaborative (CTC) follow up with all reported COVID-19 cases multiple times throughout their illness. It is through these conversations that CPHD or CTC staff determine when a Cambridge resident infected with COVID-19 has met the CDC criteria for ending isolation, which connotes recovery. While many people with mild COVID-19 illness will meet the CDC criteria for ending isolation (i.e., recovery) in under two weeks, people who survive severe illness might not meet the criteria for six weeks or more.

    Active Case: This category reflects Cambridge COVID-19 cases who are currently infected. Note: There may be a delay in the time between a person being released from isolation (recovered) and when their recovery is reported.

    Death: This category reflects total deaths among Cambridge COVID 19 cases.

    Unknown Outcome: This category reflects Cambridge COVID-19 cases who public health staff have been unable to reach by phone or letter, or who have stopped responding to follow up from public health staff.

  4. O

    COVID-19 Long Term Care Facility Cases 5/11/2023

    • data.cambridgema.gov
    application/rdfxml +5
    Updated May 11, 2023
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    Cambridge Department of Public Health (2023). COVID-19 Long Term Care Facility Cases 5/11/2023 [Dataset]. https://data.cambridgema.gov/dataset/COVID-19-Long-Term-Care-Facility-Cases-5-11-2023/ckq7-kjti
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    application/rssxml, xml, tsv, csv, json, application/rdfxmlAvailable download formats
    Dataset updated
    May 11, 2023
    Dataset authored and provided by
    Cambridge Department of Public Health
    License

    ODC Public Domain Dedication and Licence (PDDL) v1.0http://www.opendatacommons.org/licenses/pddl/1.0/
    License information was derived automatically

    Description

    This dataset is no longer being updated as of m/d/yyyy. It is being retained on the Open Data Portal for its potential historical interest.

    This table shows selected demographic information for Cambridge residents living in skilled nursing or assisted living facilities who are classified as confirmed, probable, or suspect cases (see “Case Count by Classification” section for definitions). Demographic information includes gender, age range, and race/ethnicity.

    About the COVID-19 Rapid Testing Program: On April 9, the Broad Institute, in partnership with the City of Cambridge and Pro EMS, launched a surveillance testing pilot program in Cambridge skilled nursing and assisted living facilities. The goal of the program is to gain an accurate picture of the true infection rate in these facilities by testing all residents and workers regardless of whether they have symptoms or feel ill. Positive cases among facility residents reflect three rounds of testing in April and May of all residents at the seven skilled nursing and assisted living facilities in Cambridge, as well as other testing ordered by medical providers.

    Of note:

    The case count includes those who have recovered, are currently sick with COVID-19, and who have died from complications of the disease. Any category with a case count less than five is omitted to protect individual privacy. The Cambridge case count reflects current data received from the Massachusetts Department of Public Health.

    It is important to note that race and ethnicity data are collected and reported by multiple entities and may or may not reflect self-reporting by the individual case. The Cambridge Public Health Department (CPHD) is actively reaching out to cases to collect this information. Due to these efforts, race and ethnicity information have been confirmed for over 80% of Cambridge cases, as of June 2020. Race/Ethnicity Category Definitions: “White” indicates “White, not of Hispanic origin.” “Black” indicates “Black, not of Hispanic origin.” “Hispanic” refers to a person having Hispanic origin. A person having Hispanic origin may be of any race. “Asian” indicates “Asian, not of Hispanic origin.” "Unknown" indicates that the originating reporter or reporting system did not capture race and ethnicity information or the individual refused to provide the information. "Other" indicates multiple races, another race that is not listed above, and cases who have reported nationality in lieu of a race category recognized by the US Census. Population data are from the U.S. Census Bureau’s 2014–2018 American Community Survey estimates and may differ from actual population counts. "Other" also includes a small number of people who identify as Native American or Native Hawaiian/Pacific islander. Because the count for Native Americans or Native Hawaiian/Pacific Islanders is currently < 5 people, these categories have been combined with “Other” to protect individual privacy.

    The table is updated daily at 4 p.m.

    **Living in a facility is defined as a Cambridge resident who lives in a skilled nursing or assisted living facility.

    ^Positive cases among facility residents reflect three rounds of testing in April and May of all residents at the seven skilled nursing and assisted living facilities in Cambridge, as well as other testing ordered by medical providers.

  5. n

    Coronavirus (Covid-19) Data in the United States

    • nytimes.com
    • openicpsr.org
    • +2more
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    New York Times, Coronavirus (Covid-19) Data in the United States [Dataset]. https://www.nytimes.com/interactive/2020/us/coronavirus-us-cases.html
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    Dataset provided by
    New York Times
    Description

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

    Since late January, The Times has tracked cases of coronavirus in real time as they were identified after testing. Because of the widespread shortage of testing, however, the data is necessarily limited in the picture it presents of the outbreak.

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

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

  6. m

    Viral respiratory illness reporting

    • mass.gov
    Updated Oct 5, 2023
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    Executive Office of Health and Human Services (2023). Viral respiratory illness reporting [Dataset]. https://www.mass.gov/info-details/viral-respiratory-illness-reporting
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    Dataset updated
    Oct 5, 2023
    Dataset provided by
    Executive Office of Health and Human Services
    Department of Public Health
    Area covered
    Massachusetts
    Description

    The following dashboards provide data on contagious respiratory viruses, including acute respiratory diseases, COVID-19, influenza (flu), and respiratory syncytial virus (RSV) in Massachusetts. The data presented here can help track trends in respiratory disease and vaccination activity across Massachusetts.

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Rebekka M. Lee; Veronica L. Handunge; Samantha L. Augenbraun; Huy Nguyen; Cristina Huebner Torres; Alyssa Ruiz; Karen M. Emmons; for the RADx-MA Research Partnership (2023). Data_Sheet_1_Addressing COVID-19 Testing Inequities Among Underserved Populations in Massachusetts: A Rapid Qualitative Exploration of Health Center Staff, Partner, and Resident Perceptions.PDF [Dataset]. http://doi.org/10.3389/fpubh.2022.838544.s001

Data_Sheet_1_Addressing COVID-19 Testing Inequities Among Underserved Populations in Massachusetts: A Rapid Qualitative Exploration of Health Center Staff, Partner, and Resident Perceptions.PDF

Related Article
Explore at:
pdfAvailable download formats
Dataset updated
Jun 4, 2023
Dataset provided by
Frontiers
Authors
Rebekka M. Lee; Veronica L. Handunge; Samantha L. Augenbraun; Huy Nguyen; Cristina Huebner Torres; Alyssa Ruiz; Karen M. Emmons; for the RADx-MA Research Partnership
License

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

Area covered
Massachusetts
Description

IntroductionAccess to COVID-19 testing has been inequitable and misaligned with community need. However, community health centers have played a critical role in addressing the COVID-19 testing needs of historically disadvantaged communities. The aim of this paper is to explore the perceptions of COVID-19 testing barriers in six Massachusetts communities that are predominantly low income and describe how these findings were used to build tailored clinical-community strategies to addressing testing inequities.MethodsBetween November 2020 and February 2021, we conducted 84 semi-structured qualitative interviews with 107 community health center staff, community partners, and residents. Resident interviews were conducted in English, Spanish, Vietnamese, and Arabic. We used a 2-phase framework analysis to analyze the data, including deductive coding to facilitate rapid analysis for action and an in-depth thematic analysis applying the Social Ecological Model.ResultsThrough the rapid needs assessment, we developed cross-site suggestions to improve testing implementation and communications, as well as community-specific recommendations (e.g., locations for mobile testing sites and local communication channels). Upstream barriers identified in the thematic analysis included accessibility of state-run testing sites, weak social safety nets, and lack of testing supplies and staffing that contributed to long wait times. These factors hindered residents' abilities to get tested, which was further exacerbated by individual fears surrounding the testing process and limited knowledge on testing availability.DiscussionOur rapid, qualitative approach created the foundation for implementing strategies that reached underserved populations at the peak of the COVID-19 pandemic in winter 2021. We explored perceptions of testing barriers and created actionable summaries within 1–2 months of data collection. Partnering community health centers in Massachusetts were able to use these data to respond to the local needs of each community. This study underscores the substantial impact of upstream, structural disparities on the individual experience of COVID-19 and demonstrates the utility of shifting from a typical years' long research translation process to a rapid approach of using data for action.

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