10 datasets found
  1. Match-back to eHARS data available 12 months after index date to confirm...

    • figshare.com
    xls
    Updated May 30, 2023
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    Kate Buchacz; Miao-Jung Chen; Maree Kay Parisi; Maya Yoshida-Cervantes; Erin Antunez; Viva Delgado; Nicholas J. Moss; Susan Scheer (2023). Match-back to eHARS data available 12 months after index date to confirm persons’ original eligibility and to assess re-engagement in care based on new HIV laboratory data, the RSVP Project, San Francisco, 2012–2013. [Dataset]. http://doi.org/10.1371/journal.pone.0118923.t002
    Explore at:
    xlsAvailable download formats
    Dataset updated
    May 30, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Kate Buchacz; Miao-Jung Chen; Maree Kay Parisi; Maya Yoshida-Cervantes; Erin Antunez; Viva Delgado; Nicholas J. Moss; Susan Scheer
    License

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

    Area covered
    San Francisco
    Description

    Match-back to eHARS data available 12 months after index date to confirm persons’ original eligibility and to assess re-engagement in care based on new HIV laboratory data, the RSVP Project, San Francisco, 2012–2013.

  2. Characteristics* of the eligible population and investigated cases, the RSVP...

    • plos.figshare.com
    xls
    Updated Jun 2, 2023
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    Kate Buchacz; Miao-Jung Chen; Maree Kay Parisi; Maya Yoshida-Cervantes; Erin Antunez; Viva Delgado; Nicholas J. Moss; Susan Scheer (2023). Characteristics* of the eligible population and investigated cases, the RSVP project, San Francisco, 2012–2013. [Dataset]. http://doi.org/10.1371/journal.pone.0118923.t001
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 2, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Kate Buchacz; Miao-Jung Chen; Maree Kay Parisi; Maya Yoshida-Cervantes; Erin Antunez; Viva Delgado; Nicholas J. Moss; Susan Scheer
    License

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

    Description

    Characteristics* of the eligible population and investigated cases, the RSVP project, San Francisco, 2012–2013.

  3. S

    HIV/AIDS transmission rate among adults and adolescents, New Jersey, by...

    • healthdata.nj.gov
    • data.wu.ac.at
    application/rdfxml +5
    Updated Sep 30, 2020
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    New Jersey Enhanced HIV/AIDS Reporting System (eHARS) (2020). HIV/AIDS transmission rate among adults and adolescents, New Jersey, by year: Beginning 2010 [Dataset]. https://healthdata.nj.gov/dataset/HIV-AIDS-transmission-rate-among-adults-and-adoles/8jin-3bai
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    tsv, xml, application/rdfxml, application/rssxml, csv, jsonAvailable download formats
    Dataset updated
    Sep 30, 2020
    Dataset authored and provided by
    New Jersey Enhanced HIV/AIDS Reporting System (eHARS)
    Area covered
    New Jersey
    Description

    Rate: Number of new cases of HIV/AIDS infections per 100,000 population.

    Definition: The rate of HIV transmission among adolescents and adults age 13+ per 100,000 population.

    Data Source: New Jersey Enhanced HIV/AIDS Reporting System (eHARS) Division of HIV/AIDS, STD, and TB Services, New Jersey Department of Health

  4. d

    Blog | HealthData.gov Reaches 3,000 Datasets: A Look Back and What’s Ahead

    • catalog.data.gov
    • data.virginia.gov
    Updated Mar 26, 2025
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    Damon Davis (2025). Blog | HealthData.gov Reaches 3,000 Datasets: A Look Back and What’s Ahead [Dataset]. https://catalog.data.gov/dataset/blog-healthdata-gov-reaches-3000-datasets-a-look-back-and-whats-ahead
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    Dataset updated
    Mar 26, 2025
    Dataset provided by
    Damon Davis
    Description

    This blog post was posted by Damon Davis on January 6, 2017.

  5. HIV diagnosis among men who have sex with men by race/ethnicity and age

    • data-sccphd.opendata.arcgis.com
    • hub.arcgis.com
    Updated Feb 9, 2018
    + more versions
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    Santa Clara County Public Health (2018). HIV diagnosis among men who have sex with men by race/ethnicity and age [Dataset]. https://data-sccphd.opendata.arcgis.com/datasets/sccphd::hiv-diagnosis-among-men-who-have-sex-with-men-by-race-ethnicity-and-age/about
    Explore at:
    Dataset updated
    Feb 9, 2018
    Dataset provided by
    Santa Clara County Public Health Departmenthttps://publichealth.sccgov.org/
    Authors
    Santa Clara County Public Health
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    Percentages of MSM newly diagnosed with HIV infection by age and race/ethnicity, 2016, Santa Clara County. Source: Santa Clara County Public Health Department, enhanced HIV/AIDS reporting system (eHARS), data as of 4/30/2017. METADATA:Notes (String): Lists table title, notes and sourcesCategory (String): Lists the category representing the data: Age group: 13-24, 25-29, 30-39, 40-49, 50 and older; race/ethnicity:Asian/Pacific Islander, Black/African American, Latino, White (non-Hispanic White only), Other/Unknown.Percentage (Numeric): Percentage of MSM diagnosed with HIV in a particular category among all MSM diagnoses

  6. q

    Data from: What's in this? Students Deliberate on Endocrine Disrupting...

    • qubeshub.org
    Updated Oct 4, 2022
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    Liz Rain-Griffith*; Emma Goodwin; Erin Shortlidge (2022). What's in this? Students Deliberate on Endocrine Disrupting Chemicals Found in Everyday Healthcare Items to Build Democratic Skills [Dataset]. https://qubeshub.org/community/groups/coursesource/publications?id=3510
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    Dataset updated
    Oct 4, 2022
    Dataset provided by
    QUBES
    Authors
    Liz Rain-Griffith*; Emma Goodwin; Erin Shortlidge
    Description

    In helping our students become informed and active members of society, it is necessary that they develop certain skills that will empower them to improve their community and governance. These skills include communication, collaboration, and application of information. One way of helping students develop these important skills is through deliberative pedagogy. In this article, we present the curriculum for a small group activity called Deliberative Democracy (DD). Here we describe one DD activity that was iteratively developed over five years for an introductory biology course. In this DD activity, students were asked to develop a policy statement that addresses the question: “What kind of regulations should be placed on cosmetics that contain potential endocrine disrupting chemicals (EDCs)?” We incorporate multiple strategies in this activity, including readings, videos, worksheets, clicker questions, small group and individual work, and whole class discussions. This activity supports students in developing important democratic skills and provides an opportunity to apply course content to real-world issues.

    Primary Image: Deliberative Democracy in Action. Principles of Biology students working small groups on a Deliberative Democracy activity.

  7. o

    Data and Code for: What’s Behind Her Smile? Health, Looks, and Self-Esteem

    • openicpsr.org
    Updated Jan 12, 2022
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    Francisco Gallego; Andrea Repetto; Cristian Larroulet (2022). Data and Code for: What’s Behind Her Smile? Health, Looks, and Self-Esteem [Dataset]. http://doi.org/10.3886/E159261V1
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    Dataset updated
    Jan 12, 2022
    Dataset provided by
    American Economic Association
    Authors
    Francisco Gallego; Andrea Repetto; Cristian Larroulet
    License

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

    Time period covered
    2011 - 2015
    Area covered
    Chile, Santiago
    Description

    These files contain the program and data for the article "What’s Behind Her Smile? Health, Looks, and Self-Esteem". The article examines how improving dental health affects economic, social, and psychological outcomes. In a randomized experiment, we provide a low-income group in Chile free dental care, including prostheses, and find significant and persistent impacts on men's and women's dental and self-perceived mental health. For women, treatment generates steady improvement in self-esteem, significant impact on appearance, short-run improvements in employment and earnings, and improvement in partner interactions. We find no impact for men in any of these dimensions. Heterogeneity analyses suggest that treatment effects on labor market outcomes are larger for women with more severe visible dental issues at baseline. In summary, we find that increasing access to dental care, including cosmetic elements, improves important aspects of people's lives.

  8. People living with HIV rates by census tract

    • data-sccphd.opendata.arcgis.com
    • hub.arcgis.com
    Updated Feb 23, 2018
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    Santa Clara County Public Health (2018). People living with HIV rates by census tract [Dataset]. https://data-sccphd.opendata.arcgis.com/maps/sccphd::people-living-with-hiv-rates-by-census-tract/about
    Explore at:
    Dataset updated
    Feb 23, 2018
    Dataset provided by
    Santa Clara County Public Health Departmenthttps://publichealth.sccgov.org/
    Authors
    Santa Clara County Public Health
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Area covered
    Description

    Geographic distribution of rates of people living with HIV infection, 2016, by census tract, Santa Clara County. Source: Santa Clara County Public Health Department, enhanced HIV/AIDS reporting system (eHARS), data as of 4/30/2017. 2010 U.S. Census

  9. HIV/STD co-infection

    • hub.arcgis.com
    • data-sccphd.opendata.arcgis.com
    Updated Feb 9, 2018
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    Santa Clara County Public Health (2018). HIV/STD co-infection [Dataset]. https://hub.arcgis.com/datasets/sccphd::hiv-std-co-infection
    Explore at:
    Dataset updated
    Feb 9, 2018
    Dataset provided by
    Santa Clara County Public Health Departmenthttps://publichealth.sccgov.org/
    Authors
    Santa Clara County Public Health
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    Percentage of HIV and STDs co-infection among persons living with HIV infection (PLWH) ages 13 and older, 2016, Santa Clara County. STD co-infections among PLWH were identified by matching the list of PLWH and the list of STD cases newly reported in Santa Clara County in 2016. STDs include chlamydia, gonorrhea, syphilis(primary, secondary, and early latent). Source: Santa Clara County Public Health Department, enhanced HIV/AIDS reporting system (eHARS), data as of 4/30/2017; CalREDIE, data as of March 15, 2017METADATA:Notes (String): Lists table title, notes and sourcesCategory (String): Lists the category representing the data: Santa Clara County is for total population living with HIV infection; sex: male, female; age group: 13-19, 20-29, 30-39, 40-49, 50-59, 60-64, 65 and older; race/ethnicity: African American, Asian/Pacific Islander, Latino and White (non-Hispanic White only); transmission mode: MSM, IDU, MSM & IDU, heterosexual contactPercentage (Numeric): Percentage of people living with HIV who was diagnosed with chlamydia, gonorrhea, or early syphilis among all people living with HIV in 2016.

  10. HIV Care Continuum

    • hub.arcgis.com
    • data-sccphd.opendata.arcgis.com
    Updated Mar 1, 2018
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    Santa Clara County Public Health (2018). HIV Care Continuum [Dataset]. https://hub.arcgis.com/datasets/sccphd::hiv-care-continuum/about
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    Dataset updated
    Mar 1, 2018
    Dataset provided by
    Santa Clara County Public Health Departmenthttps://publichealth.sccgov.org/
    Authors
    Santa Clara County Public Health
    License

    MIT Licensehttps://opensource.org/licenses/MIT
    License information was derived automatically

    Description

    HIV care continuum among persons with HIV infection ages 13 and older, 2016, Santa Clara County. The HIV care continuum is a model to track the delivery of services to persons with HIV infection across the entire continuum of diagnosis and care. It has five major stages of HIV medical care that persons with HIV infection will go through from initial HIV diagnosis to achieving viral suppression. They are 1) HIV diagnosis, 2) linkage to care, 3) engagement and retention in care, 4) receiving antiretroviral therapy, and 5) achieving viral suppression. Estimates of linkage to care, engagement and retention in care, and viral suppression are included in this data table. Source: Santa Clara County Public Health Department, enhanced HIV/AIDS reporting system (eHARS), data as of 4/30/2017. METADATA:Notes (String): Lists table title, notes and sourcesCategory (String): Lists the category representing the data: Santa Clara County is for total population living with HIV infection; sex: male, female; age group: 13-24, 25-44, 45-64, 65 and older; race/ethnicity: African American, Asian/Pacific Islander, Latino and White (non-Hispanic White only); transmission mode: MSM, IDU, MSM & IDU, heterosexual contactPercentage of linkage to care (Numeric): Percentage of persons with one or more documented viral load or CD4 test within one month of diagnosis among all persons newly diagnosed with HIV infection in 2016. Percentages are not reported if the denominator is less than 20.Percentage of in care (Numeric): Percentage of persons with at least 1 documented CD4 or viral load test in 2016 among those diagnosed with HIV through 2015 and alive in 2016. Percentages are not reported if the denominator is less than 20.Percentage of retention in care (Numeric): Percentage of persons with at least 2 documented CD4 or viral load tests in 2016, at least 3 months apart among those diagnosed with HIV through 2015 and alive in 2016. Percentages are not reported if the denominator is less than 20.Percentage of viral load suppression (Numeric): Percentage of persons with most recent HIV viral load in 2016 less than 200 copies/ml among those diagnosed with HIV through 2015 and alive in 2016. Percentages are not reported if the denominator is less than 20.

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    Learn how you can add new datasets to our index.

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Kate Buchacz; Miao-Jung Chen; Maree Kay Parisi; Maya Yoshida-Cervantes; Erin Antunez; Viva Delgado; Nicholas J. Moss; Susan Scheer (2023). Match-back to eHARS data available 12 months after index date to confirm persons’ original eligibility and to assess re-engagement in care based on new HIV laboratory data, the RSVP Project, San Francisco, 2012–2013. [Dataset]. http://doi.org/10.1371/journal.pone.0118923.t002
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Match-back to eHARS data available 12 months after index date to confirm persons’ original eligibility and to assess re-engagement in care based on new HIV laboratory data, the RSVP Project, San Francisco, 2012–2013.

Related Article
Explore at:
xlsAvailable download formats
Dataset updated
May 30, 2023
Dataset provided by
PLOShttp://plos.org/
Authors
Kate Buchacz; Miao-Jung Chen; Maree Kay Parisi; Maya Yoshida-Cervantes; Erin Antunez; Viva Delgado; Nicholas J. Moss; Susan Scheer
License

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

Area covered
San Francisco
Description

Match-back to eHARS data available 12 months after index date to confirm persons’ original eligibility and to assess re-engagement in care based on new HIV laboratory data, the RSVP Project, San Francisco, 2012–2013.

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