100+ datasets found
  1. d

    HIV/AIDS Cases

    • catalog.data.gov
    • healthdata.gov
    • +2more
    Updated Nov 27, 2024
    + more versions
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    California Department of Public Health (2024). HIV/AIDS Cases [Dataset]. https://catalog.data.gov/dataset/hiv-aids-cases-5805c
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    Dataset updated
    Nov 27, 2024
    Dataset provided by
    California Department of Public Health
    Description

    This data set includes tables on persons living with HIV/AIDS, newly diagnosed HIV cases and all cause deaths in HIV/AIDS cases by gender, age, race/ethnicity and transmission category. In all tables, cases are reported as of December 31 of the given year, as reported by January 9, 2019, to allow a minimum of 12 months reporting delay. Gender is determined by both current gender and sex at birth variables; transgender values are assigned when current gender is identified as "Transgender" or when a discrepancy is identified between a person's sex at birth and their current gender (e.g., cases where sex at birth is "Male" and current gender is "Female" will become Transgender: Male to Female.) Prior to 2003, Asian and Native Hawaiian/Pacific Islanders were classified as one combined group. In order to present these race/ethnicities separately, living cases recorded under this combined classification were split and redistributed according to their expected proportional population representation estimated from post-2003 data.

  2. HIV: annual data

    • gov.uk
    Updated Oct 1, 2024
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    UK Health Security Agency (2024). HIV: annual data [Dataset]. https://www.gov.uk/government/statistics/hiv-annual-data-tables
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    Dataset updated
    Oct 1, 2024
    Dataset provided by
    GOV.UKhttp://gov.uk/
    Authors
    UK Health Security Agency
    Description

    The following slide sets are available to download for presentational use:

    New HIV diagnoses, AIDS and deaths are collected from HIV outpatient clinics, laboratories and other healthcare settings. Data relating to people living with HIV is collected from HIV outpatient clinics. Data relates to England, Wales, Northern Ireland and Scotland, unless stated.

    HIV testing, pre-exposure prophylaxis, and post-exposure prophylaxis data relates to activity at sexual health services in England only.

    View the pre-release access lists for these statistics.

    Previous reports, data tables and slide sets are also available for:

    Our statistical practice is regulated by the Office for Statistics Regulation (OSR). The OSR sets the standards of trustworthiness, quality and value in the https://code.statisticsauthority.gov.uk/">Code of Practice for Statistics that all producers of Official Statistics should adhere to.

    Additional information on HIV surveillance can be found in the HIV Action Plan for England monitoring and evaluation framework reports. Other HIV in the UK reports published by Public Health England (PHE) are available online.

  3. o

    AVERT - HIV and AIDS Statistics - Dataset - openAFRICA

    • open.africa
    Updated Nov 4, 2015
    + more versions
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    (2015). AVERT - HIV and AIDS Statistics - Dataset - openAFRICA [Dataset]. https://open.africa/dataset/avert-hiv-and-aids-statistics
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    Dataset updated
    Nov 4, 2015
    License

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

    Description

    Statistics relating to HIV infection

  4. d

    DOHMH HIV/AIDS Annual Report

    • catalog.data.gov
    • data.cityofnewyork.us
    • +1more
    Updated Jun 29, 2025
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    data.cityofnewyork.us (2025). DOHMH HIV/AIDS Annual Report [Dataset]. https://catalog.data.gov/dataset/dohmh-hiv-aids-annual-report
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    Dataset updated
    Jun 29, 2025
    Dataset provided by
    data.cityofnewyork.us
    Description

    HIV/AIDS data from the HIV Surveillance Annual Report Data reported to the HIV Epidemiology Program by March 31, 2022. All data shown are for people ages 18 and older. Borough-wide and citywide totals may include cases assigned to a borough with an unknown UHF or assigned to NYC with an unknown borough, respectively. Therefore, UHF totals may not sum to borough totals and borough totals may not sum to citywide totals.""

  5. o

    HIV prevalence among young people - Dataset - openAFRICA

    • open.africa
    Updated Aug 17, 2019
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    (2019). HIV prevalence among young people - Dataset - openAFRICA [Dataset]. https://open.africa/dataset/hiv-prevalence-among-young-people
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    Dataset updated
    Aug 17, 2019
    Description

    Young people age 15-24 are an important group to monitor for reduction of HIV incidence. This was specified in the United Nations General Assembly Special Session (UNGASS) on HIV and AIDS.

  6. b

    HIV diagnosed prevalence (aged 15 to 59) - WMCA

    • cityobservatory.birmingham.gov.uk
    csv, excel, geojson +1
    Updated Aug 4, 2025
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    (2025). HIV diagnosed prevalence (aged 15 to 59) - WMCA [Dataset]. https://cityobservatory.birmingham.gov.uk/explore/dataset/hiv-diagnosed-prevalence-aged-15-to-59-wmca/
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    geojson, csv, json, excelAvailable download formats
    Dataset updated
    Aug 4, 2025
    License

    Open Government Licence 3.0http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/
    License information was derived automatically

    Description

    People aged 15 to 59 years seen at HIV services in the UK, expressed as a rate per 1,000 population.Data is presented by area of residence, and exclude people diagnosed with HIV in England who are resident in Wales, Scotland, Northern Ireland or abroad.RationaleThe geographical distribution of people seen for HIV care and treatment is not uniform across or within regions in England. Knowledge of local diagnosed HIV prevalence and identification of local risk groups can be used to help direct resources for HIV prevention and treatment.In 2008, http://www.bhiva.org/HIV-testing-guidelines.aspx recommended that Local Authority and NHS bodies consider implementing routine HIV testing for all general medical admissions as well as new registrants in primary care where the diagnosed HIV prevalence exceeds 2 in 1,000 population aged 15 to 59 years.In 2017, guidelines were updated by https://www.nice.org.uk/guidance/NG60 which is co-badged with Public Health England. This guidance continues to define high HIV prevalence local authorities as those with a diagnosed HIV prevalence of between 2 and 5 per 1,000 and extremely high prevalence local authorities as those with a diagnosed HIV prevalence of 5 or more per 1,000 people aged 15 to 59 years.When this is applied to national late HIV diagnosis data, it shows that two-thirds of late HIV diagnoses occur in high-prevalence and extremely-high-prevalence local authorities. This means that if this recommendation is successfully applied in high and extremely-high-prevalence areas, it could potentially affect two-thirds of late diagnoses nationally.Local authorities should find out their diagnosed prevalence published in UKHSA's http://fingertips.phe.org.uk/profile/sexualhealth , as well as that of surrounding areas and adapt their strategy for HIV testing using the national guidelines.Commissioners can use these data to plan and ensure access to comprehensive and specialist local HIV care and treatment for HIV diagnosed individuals according to the http://www.medfash.org.uk/uploads/files/p17abl6hvc4p71ovpkr81ugsh60v.pdf and http://www.bhiva.org/monitoring-guidelines.aspx .Definition of numeratorThe number of people (aged 15 to 59 years) living with a diagnosed HIV infection and accessing HIV care at an NHS service in the UK and who are resident in England.Definition of denominatorResident population aged 15 to 59.The denominators for 2011 to 2023 are taken from the respective 2011 to 2023 Office for National Statistics (ONS) revised population estimates from the 2021 Census.Further details on the ONS census are available from the https://www.ons.gov.uk/census .CaveatsData is presented by geographical area of residence. Where data on residence were unavailable, residence have been assigned to the local health area of care.Every effort is made to ensure accuracy and completeness of the data, including web-based reporting with integrated checks on data quality. The overall data quality is high as the dataset is used for commissioning purposes and for the national allocation of funding. However, responsibility for the accuracy and completeness of data lies with the reporting service.Data is as reported but rely on ‘record linkage’ to integrate data and ‘de-duplication’ to prevent double counting of the same individual. The data may not be representative in areas where residence information is not known for a significant proportion of people accessing HIV care.Data supplied for previous years are updated on an annual basis due to clinic or laboratory resubmissions and improvements to data cleaning. Data may therefore differ from previous publications.Values are benchmarked against set thresholds and categorised into the following groups: <2 (low), 2 to 5 (high) and≥5 (extremely high). These have been determined by developments in national testing guidelines.The data reported in 2020 and 2021 is impacted by the reconfiguration of sexual health services during the national response to COVID-19.

  7. g

    Statistics Relating to Notification of HIV Aids Cases and Deaths for...

    • data.govmu.org
    Updated Sep 30, 2024
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    (2024). Statistics Relating to Notification of HIV Aids Cases and Deaths for Mauritius [Dataset]. https://data.govmu.org/dataset/statistics-relating-notification-hiv-aids-cases-and-deaths-mauritius
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    Dataset updated
    Sep 30, 2024
    License

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

    Area covered
    Mauritius
    Description

    Dataset refers to the Statistics Relating to Notification of HIV Aids Cases and Deaths in Mauritius for the year 2000 to 2021

  8. Epidemic HIV heath

    • kaggle.com
    Updated Mar 27, 2025
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    willian oliveira (2025). Epidemic HIV heath [Dataset]. http://doi.org/10.34740/kaggle/dsv/11188352
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Mar 27, 2025
    Dataset provided by
    Kaggle
    Authors
    willian oliveira
    License

    https://creativecommons.org/publicdomain/zero/1.0/https://creativecommons.org/publicdomain/zero/1.0/

    Description

    ART not only saves lives but also gives a chance for people living with HIV/AIDS to live long lives. Without ART very few infected people survive beyond ten years.1

    Today, a person living in a high-income country who started ART in their twenties can expect to live for another 46 years — that is well into their 60s.2

    While the life expectancy of people living with HIV/AIDS in high-income countries has still not reached the life expectancy of the general population, we are getting closer to this goal.3

    The combination of antiretroviral drugs which make-up ART have progressively improved. Recent research shows that a person who started ART in the late 1990s would be expected to live ten years less than a person who started ART in 2008.4 This increase goes beyond the general increase in life expectancy in that period and reflects the improvements in ART — fewer side effects, more people following the prescribed treatment, and more support for the people in need of ART.

  9. w

    Uganda - AIDS Indicator Survey 2011 - Dataset - waterdata

    • wbwaterdata.org
    Updated Mar 16, 2020
    + more versions
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    (2020). Uganda - AIDS Indicator Survey 2011 - Dataset - waterdata [Dataset]. https://wbwaterdata.org/dataset/uganda-aids-indicator-survey-2011
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    Dataset updated
    Mar 16, 2020
    License

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

    Area covered
    Uganda
    Description

    The 2011 Uganda AIDS Indicator Survey (AIS) is a nationally representative, population-based, HIV serological survey. The survey was designed to obtain national and sub-national estimates of the prevalence of HIV and syphilis infection as well as information about other indicators of programme coverage, such as knowledge, attitudes, and sexual behaviour related to HIV/AIDS. Data collection took place from 8 February to the first few days of September 2011. The UAIS was implemented by the Ministry of Health. ICF International provided financial and technical assistance for the survey through a contract with USAID/Uganda. Financial and technical assistance was also provided by the U.S. Centers for Disease Control and Prevention (CDC). Financial support was provided by the Government of Uganda, the U.S. Agency for International Development (USAID), the President’s Emergency Fund for AIDS Relief (PEPFAR), the World Health Organisation (WHO), the UK Department for International Development (DFID), and the Danish International Development Agency (DANIDA) through the Partnership Fund. The Uganda Bureau of Statistics also partnered in the implementation of the survey. Central testing was conducted at the Uganda Virus Research Institute, with CDC conducting CD4 counts, polymerase chain reaction (PCR) testing for children, and quality control tests. The survey provided information on knowledge, attitudes, and behaviour regarding HIV/AIDS and indicators of coverage and access to other programmes, for example, HIV testing, access to antiretroviral therapy, services for treating sexually transmitted infections, and coverage of interventions to prevent motherto-child transmission of HIV. The survey also collected information on the prevalence of HIV and syphilis and their social and demographic variations in the country. The overall goal of the survey was to provide programme managers and policymakers involved in HIV/AIDS programmes with strategic information to effectively plan, implement, and evaluate HIV/AIDS interventions. The information obtained from the survey will help programme implementers to monitor and evaluate existing programmes and design new strategies for combating the HIV/AIDS epidemic in Uganda. The survey data will in addition be used to make population projections and to calculate indicators developed by the UN General Assembly Special Session (UNGASS), USAID, PEPFAR, the UNAIDS Programme, WHO, the Uganda Health Sector Strategic and Investment Plan, and the Uganda AIDS Commission. The specific objectives of the 2011 UAIS were to provide information on: • Prevalence and distribution of HIV and syphilis • Indicators of knowledge, attitudes, and behaviour related to HIV/AIDS and other sexually transmitted infections • HIV/AIDS programme coverage indicators • Levels of CD4 T-lymphocyte counts among HIV-positive adults to quantify HIV treatment needs and to calibrate model-based estimates • HIV prevalence that can be used to calibrate and improve the sentinel surveillance system • Risk factors for HIV and syphilis infections in Uganda.

  10. o

    HIV/AIDS data sheet for Myanmar - Dataset OD Mekong Datahub

    • data.opendevelopmentmekong.net
    Updated May 19, 2015
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    (2015). HIV/AIDS data sheet for Myanmar - Dataset OD Mekong Datahub [Dataset]. https://data.opendevelopmentmekong.net/dataset/hiv-aids-data-sheet-for-myanmar
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    Dataset updated
    May 19, 2015
    License

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

    Area covered
    Mekong River, Myanmar (Burma)
    Description

    A dataset of key HIV/AIDS indicators for Myanmar in .XLSX format. Published by Evidence to Action. Contains worksheets covering Sociodemographic indicators, HIV prevalence and epidemiology, Risk behaviours, Vulnerability and HIV knowledge, HIV expenditure and National response.

  11. HIV/AIDS yearly statistics in Hong Kong | DATA.GOV.HK

    • data.gov.hk
    Updated Dec 25, 2019
    + more versions
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    data.gov.hk (2019). HIV/AIDS yearly statistics in Hong Kong | DATA.GOV.HK [Dataset]. https://data.gov.hk/en-data/dataset/hk-dh-dh_spp-dh-spp-hiv-aids-1984-to-2023-yearly-figures
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    Dataset updated
    Dec 25, 2019
    Dataset provided by
    data.gov.hk
    Area covered
    Hong Kong
    Description

    HIV/AIDS yearly statistics in Hong Kong 1984 - 2023

  12. U

    United States US: Prevalence of HIV: Total: % of Population Aged 15-49

    • ceicdata.com
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    CEICdata.com, United States US: Prevalence of HIV: Total: % of Population Aged 15-49 [Dataset]. https://www.ceicdata.com/en/united-states/health-statistics/us-prevalence-of-hiv-total--of-population-aged-1549
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    Dataset provided by
    CEICdata.com
    License

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

    Time period covered
    Dec 1, 2008 - Dec 1, 2014
    Area covered
    United States
    Description

    United States US: Prevalence of HIV: Total: % of Population Aged 15-49 data was reported at 0.500 % in 2014. This stayed constant from the previous number of 0.500 % for 2013. United States US: Prevalence of HIV: Total: % of Population Aged 15-49 data is updated yearly, averaging 0.500 % from Dec 2008 (Median) to 2014, with 7 observations. The data reached an all-time high of 0.500 % in 2014 and a record low of 0.500 % in 2014. United States US: Prevalence of HIV: Total: % of Population Aged 15-49 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Health Statistics. Prevalence of HIV refers to the percentage of people ages 15-49 who are infected with HIV.; ; UNAIDS estimates.; Weighted Average;

  13. Age-Specific Notification Rate Of HIV/AIDS In Singapore Residents By Gender,...

    • data.gov.sg
    Updated Aug 14, 2025
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    Singapore Department of Statistics (2025). Age-Specific Notification Rate Of HIV/AIDS In Singapore Residents By Gender, Annual [Dataset]. https://data.gov.sg/datasets/d_6d8bcb5f8e9cf2616b758c53095768fb/view
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    Dataset updated
    Aug 14, 2025
    Dataset authored and provided by
    Singapore Department of Statistics
    License

    https://data.gov.sg/open-data-licencehttps://data.gov.sg/open-data-licence

    Time period covered
    Jan 2010 - Dec 2023
    Area covered
    Singapore
    Description

    Dataset from Singapore Department of Statistics. For more information, visit https://data.gov.sg/datasets/d_6d8bcb5f8e9cf2616b758c53095768fb/view

  14. f

    Data from: Modeling the Marked Presence-Only Data: A Case Study of...

    • tandf.figshare.com
    pdf
    Updated Jun 6, 2023
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    Ian Laga; Xiaoyue Niu; Le Bao (2023). Modeling the Marked Presence-Only Data: A Case Study of Estimating the Female Sex Worker Size in Malawi [Dataset]. http://doi.org/10.6084/m9.figshare.14818313.v2
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    pdfAvailable download formats
    Dataset updated
    Jun 6, 2023
    Dataset provided by
    Taylor & Francis
    Authors
    Ian Laga; Xiaoyue Niu; Le Bao
    License

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

    Area covered
    Malawi
    Description

    Certain subpopulations like female sex workers (FSW), men who have sex with men (MSM), and people who inject drugs (PWID) often have higher prevalence of HIV/AIDS and are difficult to map directly due to stigma, discrimination, and criminalization. Fine-scale mapping of those populations contributes to the progress toward reducing the inequalities and ending the AIDS epidemic. In 2016 and 2017, the PLACE surveys were conducted at 3290 venues in 20 out of the total 28 districts in Malawi to estimate the FSW sizes. These venues represent a presence-only dataset where, instead of knowing both where people live and do not live (presence–absence data), only information about visited locations is available. In this study, we develop a Bayesian model for presence-only data and utilize the PLACE data to estimate the FSW size and uncertainty interval at a1.5×1.5-km resolution for all of Malawi. The estimates can also be aggregated to any desirable level (city/district/region) for implementing targeted HIV prevention and treatment programs in FSW communities, which have been successful in lowering the incidence of HIV and other sexually transmitted infections. Supplementary materials for this article, including a standardized description of the materials available for reproducing the work, are available as an online supplement.

  15. o

    Kenya HIV Estimates 2014 - Dataset - openAFRICA

    • open.africa
    Updated Mar 27, 2016
    + more versions
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    (2016). Kenya HIV Estimates 2014 - Dataset - openAFRICA [Dataset]. https://open.africa/dataset/kenya-hiv-estimates-2014
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    Dataset updated
    Mar 27, 2016
    Area covered
    Kenya
    Description

    The National AIDs Control Council as the coordinating body for the AIDS response is charged with the responsibility of coordinating the national AIDS response. In order to effectively support County governments and facilitate their planning, implementation and monitoring of the response, the NACC has profiled the status of the HIV epidemic in each county. The reports details statistics on HIV Prevalence, Mother to child transmission rates, Demand and supply of HIV treatment and the rate of new infections per county to name a few.

  16. Find Ryan White HIV/AIDS Medical Care Providers

    • catalog.data.gov
    • data.virginia.gov
    • +4more
    Updated Jul 25, 2025
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    Health Resources and Services Administration, Department of Health & Human Services (2025). Find Ryan White HIV/AIDS Medical Care Providers [Dataset]. https://catalog.data.gov/dataset/find-ryan-white-hiv-aids-medical-care-providers
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    Dataset updated
    Jul 25, 2025
    Description

    The Find Ryan White HIV/AIDS Medical Care Providers tool is a locator that helps people living with HIV/AIDS access medical care and related services. Users can search for Ryan White-funded medical care providers near a specific complete address, city and state, state and county, or ZIP code. Search results are sorted by distance away and include the Ryan White HIV/AIDS facility name, address, approximate distance from the search point, telephone number, website address, and a link for driving directions. HRSA's Ryan White program funds an array of grants at the state and local levels in areas where most needed. These grants provide medical and support services to more than a half million people who otherwise would be unable to afford care.

  17. I

    Data for Spatial Accessibility to HIV (Human Immunodeficiency Virus)...

    • databank.illinois.edu
    Updated Aug 9, 2022
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    Jeon-Young Kang; Bita Fayaz Farkhad; Man-pui Sally Chan; Alexander Michels; Dolores Albarracin; Shaowen Wang (2022). Data for Spatial Accessibility to HIV (Human Immunodeficiency Virus) Testing, Treatment, and Prevention Services in Illinois and Chicago, USA [Dataset]. http://doi.org/10.13012/B2IDB-9096476_V1
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    Dataset updated
    Aug 9, 2022
    Authors
    Jeon-Young Kang; Bita Fayaz Farkhad; Man-pui Sally Chan; Alexander Michels; Dolores Albarracin; Shaowen Wang
    License

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

    Area covered
    Illinois, Chicago, United States
    Dataset funded by
    U.S. National Science Foundation (NSF)
    U.S. National Institutes of Health (NIH)
    Description

    This dataset helps to investigate the Spatial Accessibility to HIV Testing, Treatment, and Prevention Services in Illinois and Chicago, USA. The main components are: population data, healthcare data, GTFS feeds, and road network data. The core components are: 1) GTFS which contains GTFS (General Transit Feed Specification) data which is provided by Chicago Transit Authority (CTA) from Google's GTFS feeds. Documentation defines the format and structure of the files that comprise a GTFS dataset: https://developers.google.com/transit/gtfs/reference?csw=1. 2) HealthCare contains shapefiles describing HIV healthcare providers in Chicago and Illinois respectively. The services come from Locator.HIV.gov. 3) PopData contains population data for Chicago and Illinois respectively. Data come from The American Community Survey and AIDSVu. AIDSVu (https://map.aidsvu.org/map) provides data on PLWH in Chicago at the census tract level for the year 2017 and in the State of Illinois at the county level for the year 2016. The American Community Survey (ACS) provided the number of people aged 15 to 64 at the census tract level for the year 2017 and at the county level for the year 2016. The ACS provides annually updated information on demographic and socio economic characteristics of people and housing in the U.S. 4) RoadNetwork contains the road networks for Chicago and Illinois respectively from OpenStreetMap using the Python osmnx package. The abstract for our paper is: Accomplishing the goals outlined in “Ending the HIV (Human Immunodeficiency Virus) Epidemic: A Plan for America Initiative” will require properly estimating and increasing access to HIV testing, treatment, and prevention services. In this research, a computational spatial method for estimating access was applied to measure distance to services from all points of a city or state while considering the size of the population in need for services as well as both driving and public transportation. Specifically, this study employed the enhanced two-step floating catchment area (E2SFCA) method to measure spatial accessibility to HIV testing, treatment (i.e., Ryan White HIV/AIDS program), and prevention (i.e., Pre-Exposure Prophylaxis [PrEP]) services. The method considered the spatial location of MSM (Men Who have Sex with Men), PLWH (People Living with HIV), and the general adult population 15-64 depending on what HIV services the U.S. Centers for Disease Control (CDC) recommends for each group. The study delineated service- and population-specific accessibility maps, demonstrating the method’s utility by analyzing data corresponding to the city of Chicago and the state of Illinois. Findings indicated health disparities in the south and the northwest of Chicago and particular areas in Illinois, as well as unique health disparities for public transportation compared to driving. The methodology details and computer code are shared for use in research and public policy.

  18. Indicator 3.3.1: Number of new HIV infections per 1 000 uninfected...

    • ttmay-sdgs.hub.arcgis.com
    • sdgs.amerigeoss.org
    • +2more
    Updated Sep 9, 2021
    + more versions
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    UN DESA Statistics Division (2021). Indicator 3.3.1: Number of new HIV infections per 1 000 uninfected population by sex and age (per 1 000 uninfected population) [Dataset]. https://ttmay-sdgs.hub.arcgis.com/datasets/undesa::indicator-3-3-1-number-of-new-hiv-infections-per-1-000-uninfected-population-by-sex-and-age-per-1-000-uninfected-population
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    Dataset updated
    Sep 9, 2021
    Dataset provided by
    United Nations Department of Economic and Social Affairshttps://www.un.org/en/desa
    Authors
    UN DESA Statistics Division
    Area covered
    Description

    Series Name: Number of new HIV infections per 1 000 uninfected population by sex and age (per 1 000 uninfected population)Series Code: SH_HIV_INCDRelease Version: 2021.Q2.G.03 This dataset is the part of the Global SDG Indicator Database compiled through the UN System in preparation for the Secretary-General's annual report on Progress towards the Sustainable Development Goals.Indicator 3.3.1: Number of new HIV infections per 1,000 uninfected population, by sex, age and key populationsTarget 3.3: By 2030, end the epidemics of AIDS, tuberculosis, malaria and neglected tropical diseases and combat hepatitis, water-borne diseases and other communicable diseasesGoal 3: Ensure healthy lives and promote well-being for all at all agesFor more information on the compilation methodology of this dataset, see https://unstats.un.org/sdgs/metadata/

  19. f

    Sample Characteristics and Adult HIV Prevalence.

    • figshare.com
    xls
    Updated Jun 11, 2023
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    Susan E. Short; Rachel E. Goldberg (2023). Sample Characteristics and Adult HIV Prevalence. [Dataset]. http://doi.org/10.1371/journal.pone.0142580.t001
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    xlsAvailable download formats
    Dataset updated
    Jun 11, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Susan E. Short; Rachel E. Goldberg
    License

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

    Description

    Source: Demographic and Health Surveys (DHS)* Respondent present on the day of interview, consented to HIV serostatus testing, and tested during their DHS/AIS interview. Percent tested as reported in Demographic patterns of HIV testing uptake in sub-Saharan Africa: DHS Comparative Reports 30. [42] and DHS Country Reports.** HIV prevalence as available from the HIV/AIDS Survey Indicators Database (accessed at http://hivdata.dhsprogram.com/ on July 17, 2015)Sample Characteristics and Adult HIV Prevalence.

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    HIV/AIDS Indicator Survey 2005 - Guyana

    • microdata.worldbank.org
    • catalog.ihsn.org
    Updated Jun 16, 2017
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    Guyana Responsible Parenthood Association (2017). HIV/AIDS Indicator Survey 2005 - Guyana [Dataset]. https://microdata.worldbank.org/index.php/catalog/2850
    Explore at:
    Dataset updated
    Jun 16, 2017
    Dataset provided by
    Guyana Responsible Parenthood Association
    Ministry of Health
    Time period covered
    2005
    Area covered
    Guyana
    Description

    Abstract

    The 2005 Guyana HIV/AIDS Indicator Survey (GAIS) is the first household-based, comprehensive survey on HIV/AIDS to be carried out in Guyana. The 2005 GAIS was implemented by the Guyana Responsible Parenthood Association (GRPA) for the Ministry of Health (MoH). ORC Macro of Calverton, Maryland provided technical assistance to the project through its contract with the U.S. Agency for International Development (USAID) under the MEASURE DHS program. Funding to cover technical assistance by ORC Macro and for local costs was provided in their entirety by USAID/Washington and USAID/Guyana.

    The 2005 GAIS is a nationally representative sample survey of women and men age 15-49 initiated by MoH with the purpose of obtaining national baseline data for indicators on knowledge/awareness, attitudes, and behavior regarding HIV/AIDS. The survey data can be effectively used to calculate valuable indicators of the President’s Emergency Plan for AIDS Relief (PEPFAR), the Joint United Nations Program on HIV/AIDS (UNAIDS), the United Nations General Assembly Special Session (UNGASS), the United Nations Children Fund (UNICEF) Orphan and Vulnerable Children unit (OVC), and the World Health Organization (WHO), among others. The overall goal of the survey was to provide program managers and policymakers involved in HIV/AIDS programs with information needed to monitor and evaluate existing programs; and to effectively plan and implement future interventions, including resource mobilization and allocation, for combating the HIV/AIDS epidemic in Guyana.

    Other objectives of the 2005 GAIS include the support of dissemination and utilization of the results in planning, managing and improving family planning and health services in the country; and enhancing the survey capabilities of the institutions involved in order to facilitate the implementation of surveys of this type in the future.

    The 2005 GAIS sampled over 3,000 households and completed interviews with 2,425 eligible women and 1,875 eligible men. In addition to the data on HIV/AIDS indicators, data on the characteristics of households and its members, malaria, infant and child mortality, tuberculosis, fertility, and family planning were also collected.

    Geographic coverage

    National

    Analysis unit

    • Individuals;
    • Households.

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    The primary objective of the 2005 GAIS is to provide estimates with acceptable precision for important population characteristics such as HIV/AIDS related knowledge, attitudes, and behavior. The population to be covered by the 2005 GAIS was defined as the universe of all women and men age 15-49 in Guyana.

    The major domains to be distinguished in the tabulation of important characteristics for the eligible population are: • Guyana as a whole • The urban area and the rural area each as a separate major domain • Georgetown and the remainder urban areas.

    Administratively, Guyana is divided into 10 major regions. For census purposes, each region is further subdivided in enumeration districts (EDs). Each ED is classified as either urban or rural. There is a list of EDs that contains the number of households and population for each ED from the 2002 census. The list of EDs is grouped by administrative units as townships. The available demarcated cartographic material for each ED from the last census makes an adequate sample frame for the 2005 GAIS.

    The sampling design had two stages with enumeration districts (EDs) as the primary sampling units (PSUs) and households as the secondary sampling units (SSUs). The standard design for the GAIS called for the selection of 120 EDs. Twenty-five households were selected by systematic random sampling from a full list of households from each of the selected enumeration districts for a total of 3,000 households. All women and men 15-49 years of age in the sample households were eligible to be interviewed with the individual questionnaire.

    The database for the recently completed 2002 Census was used as a sampling frame to select the sampling units. In the census frame, EDs are grouped by urban-rural location within the ten administrative regions and they are also ordered in each administrative unit in serpentine fashion. Therefore, this stratification and ordering will be also reflected in the 2005 GAIS sample.

    Based on response rates from other surveys in Guyana, around 3,000 interviews of women and somewhat fewer of men expected to be completed in the 3,000 households selected.

    Several allocation schemes were considered for the sample of clusters for each urban-rural domain. One option was to allocate clusters to urban and rural areas proportionally to the population in the area. According to the census, the urban population represents only 29 percent of the population of the country. In this case, around 35 clusters out of the 120 would have been allocated to the urban area. Options to obtain the best allocation by region were also examined. It should be emphasized that optimality is not guaranteed at the regional level but the power for analysis is increased in the urban area of Georgetown by departing from proportionality. Upon further analysis of the different options, the selection of an equal number of clusters in each major domain (60 urban and 60 rural) was recommended for the 2005 GAIS. As a result of the nonproportionalallocation of the number of EDs for the urban-rural and regional domains, the household sample for the 2005 GAIS is not a self-weighted sample.

    The 2005 GAIS sample of households was selected using a stratified two-stage cluster design consisting of 120 clusters. The first stage-units (primary sampling units or PSUs) are the enumeration areas used for the 2002 Population and Housing Census. The number of EDs (clusters) in each domain area was calculated dividing its total allocated number of households by the sample take (25 households for selection per ED). In each major domain, clusters are selected systematically with probability proportional to size.

    The sampling procedures are more fully described in "Guyana HIV/AIDS Indicator Survey 2005 - Final Report" pp.135-138.

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    Two types of questionnaires were used in the survey, namely: the Household Questionnaire and the Individual Questionnaire. The contents of these questionnaires were based on model questionnaires developed by the MEASURE DHS program. In consultation with USAID/Guyana, MoH, GRPA, and other government agencies and local organizations, the model questionnaires were modified to reflect issues relevant to HIV/AIDS in Guyana. The questionnaires were finalized around mid-May.

    The Household Questionnaire was used to list all the usual members and visitors in the selected households. For each person listed, information was collected on sex, age, education, and relationship to the head of the household. An important purpose of the Household Questionnaire was to identify women and men who were eligible for the individual interview.

    The Household Questionnaire also collected non-income proxy indicators about the household's dwelling unit, such as the source of water; type of toilet facilities; materials used for the floor, roof and walls of the house; and ownership of various durable goods and land. As part of the Malaria Module, questions were included on ownership and use of mosquito bednets.

    The Individual Questionnaire was used to collect information from women and men age 15-49 years and covered the following topics: • Background characteristics (age, education, media exposure, employment, etc.) • Reproductive history (number of births and—for women—a birth history, birth registration, current pregnancy, and current family planning use) • Marriage and sexual activity • Husband’s background • Knowledge about HIV/AIDS and exposure to specific HIV-related mass media programs • Attitudes toward people living with HIV/AIDS • Knowledge and experience with HIV testing • Knowledge and symptoms of other sexually transmitted infections (STIs) • The malaria module and questions on tuberculosis

    Cleaning operations

    The processing of the GAIS questionnaires began in mid-July 2005, shortly after the beginning of fieldwork and during the first visit of the ORC Macro data processing specialist. Questionnaires for completed clusters (enumeration districts) were periodically submitted to GRPA offices in Georgetown, where they were edited by data processing personnel who had been trained specifically for this task. The concurrent processing of the data—standard for surveys participating in the DHS program—allowed GRPA to produce field-check tables to monitor response rates and other variables, and advise field teams of any problems that were detected during data entry. All data were entered twice, allowing 100 percent verification. Data processing, including data entry, data editing, and tabulations, was done using CSPro, a program developed by ORC Macro, the U.S. Bureau of Census, and SERPRO for processing surveys and censuses. The data entry and editing of the questionnaires was completed during a second visit by the ORC Macro specialist in mid-September. At this time, a clean data set was produced and basic tables with the basic HIV/AIDS indicators were run. The tables included in the current report were completed by the end of November 2005.

    Response rate

    • From a total of 3,055 households in the sample, 2,800 were occupied. Among these households, interviews were completed in 2,608, for a response rate of 93 percent. • A total of 2,776 eligible women were identified and

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California Department of Public Health (2024). HIV/AIDS Cases [Dataset]. https://catalog.data.gov/dataset/hiv-aids-cases-5805c

HIV/AIDS Cases

Explore at:
Dataset updated
Nov 27, 2024
Dataset provided by
California Department of Public Health
Description

This data set includes tables on persons living with HIV/AIDS, newly diagnosed HIV cases and all cause deaths in HIV/AIDS cases by gender, age, race/ethnicity and transmission category. In all tables, cases are reported as of December 31 of the given year, as reported by January 9, 2019, to allow a minimum of 12 months reporting delay. Gender is determined by both current gender and sex at birth variables; transgender values are assigned when current gender is identified as "Transgender" or when a discrepancy is identified between a person's sex at birth and their current gender (e.g., cases where sex at birth is "Male" and current gender is "Female" will become Transgender: Male to Female.) Prior to 2003, Asian and Native Hawaiian/Pacific Islanders were classified as one combined group. In order to present these race/ethnicities separately, living cases recorded under this combined classification were split and redistributed according to their expected proportional population representation estimated from post-2003 data.

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