100+ datasets found
  1. 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;

  2. d

    HIV/AIDS Diagnoses by Neighborhood, Sex, and Race/Ethnicity

    • catalog.data.gov
    • data.cityofnewyork.us
    Updated Mar 18, 2023
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    data.cityofnewyork.us (2023). HIV/AIDS Diagnoses by Neighborhood, Sex, and Race/Ethnicity [Dataset]. https://catalog.data.gov/dataset/hiv-aids-diagnoses-by-neighborhood-sex-and-race-ethnicity
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    Dataset updated
    Mar 18, 2023
    Dataset provided by
    data.cityofnewyork.us
    Description

    These data were reported to the NYC DOHMH by March 31, 2021 This dataset includes data on new diagnoses of HIV and AIDS in NYC for the calendar years 2016 through 2020. Reported cases and case rates (per 100,000 population) are stratified by United Hospital Fund (UHF) neighborhood, sex, and race/ethnicity. Note: - Cells marked "NA" cannot be calculated because of cell suppression or 0 denominator.

  3. 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
    United States, Chicago, Illinois
    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.

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

    • hub.arcgis.com
    • data-sccphd.opendata.arcgis.com
    Updated Feb 9, 2018
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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://hub.arcgis.com/datasets/fa1d3bf2cb324e31b105e6ceaf45d77e
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    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

  5. H

    HIV/AIDS Statistics and Surveillance

    • dataverse.harvard.edu
    Updated Apr 6, 2011
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    Harvard Dataverse (2011). HIV/AIDS Statistics and Surveillance [Dataset]. http://doi.org/10.7910/DVN/8RFRHG
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    CroissantCroissant is a format for machine-learning datasets. Learn more about this at mlcommons.org/croissant.
    Dataset updated
    Apr 6, 2011
    Dataset provided by
    Harvard Dataverse
    License

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

    Description

    Users can access population data related to the screening, prevalence, and incidence of HIV and AIDS in the United States. Background The HIV/AIDS Statistics and Surveillance data is maintained by the Centers for Disease Control. Annual reports, fact sheets, slide sets, and basic statistics are available in a variety of formats. Fact sheets are available for a variety of subgroups including but not limited to examining HIV prevalence among different races, ages, and sexual orientations. Slide sets looking at HIV and AIDS prevalence among different groups and different regions are also available. The HIV Surveillance Report is available on an annual basis. User functionality Data is presented in report or fact sheet format and can be downloaded in PDF or HTML formats. Slide sets are available in PDF or PowerPoint format. Basic statistics and other information is avaible in HTML format. Data Notes The data sources are clearly referenced for each report, chart, and fact sheet. The most recent data is from 2009. Reports are published annually in the late summer or early fall

  6. w

    HIV/AIDS Indicator Survey 2005 - Guyana

    • microdata.worldbank.org
    • catalog.ihsn.org
    • +1more
    Updated Jun 16, 2017
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    Ministry of Health (2017). HIV/AIDS Indicator Survey 2005 - Guyana [Dataset]. https://microdata.worldbank.org/index.php/catalog/2850
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    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

  7. 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.

  8. o

    HIV prevalence - Dataset - openAFRICA

    • open.africa
    Updated Aug 17, 2019
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    (2019). HIV prevalence - Dataset - openAFRICA [Dataset]. https://open.africa/dataset/hiv-prevalence-by-age-and-sex
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    Dataset updated
    Aug 17, 2019
    Description

    Much of the information on national HIV prevalence in Tanzania derives from surveillance of HIV in special populations, such as women attending antenatal clinics and blood donors. For example, Mainland Tanzania currently maintains a network of 134 antenatal care (ANC) sites from which HIV prevalence estimates are generated. However, these surveillance data do not provide an estimate of the HIV prevalence among the general population. HIV prevalence is higher among individuals who are employed (6 percent) than among those who are not employed (3 percent) and is higher in urban areas than in rural areas (7percent and 4 percent, respectively). In Mainland Tanzania, HIV prevalence is markedly higher than in Zanzibar (5 percent versus 1 percent). Differentials by region are large. Among regions on the Mainland,Njombe has the highest prevalence estimate (15 percent), followed by Iringa and Mbeya (9 percent each);Manyara and Tanga have the lowest prevalence (2 percent). Among the five regions that comprise Zanzibar, all have HIV prevalence estimates at 1 percent or below. Consistent with the overall national estimate among men and women, HIV prevalence is higher among women than men in nearly all regions of Tanzania.

  9. Dataset from Testing a Secondary Prevention Intervention for HIV-Positive...

    • data.niaid.nih.gov
    Updated Feb 7, 2025
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    National Institute of Child Health and Human Development (NICHD) (2025). Dataset from Testing a Secondary Prevention Intervention for HIV-Positive Black Young Men Who Have Sex with Men [Dataset]. http://doi.org/10.25934/PR00009675
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    Dataset updated
    Feb 7, 2025
    Authors
    National Institute of Child Health and Human Development (NICHD)
    Area covered
    United States
    Variables measured
    HIV infection
    Description

    This study sought to construct and modify a culturally-based secondary prevention intervention targeted toward HIV-positive black young men who have sex with men. The feasibility and acceptability of the intervention were explored in Trial 1 and Trial 2; the potential efficacy of the intervention was assessed in Trial 2. Primary outcomes examined were health promotion behaviors (i.e., treatment adherence, sexual risk reduction, reduction in substance use behaviors, and HIV status disclosure). Psychosocial factors (i.e., self-esteem, critical consciousness, and socio-political awareness) were examined as secondary outcomes.

  10. U

    United States US: Incidence of HIV: per 1,000 Uninfected Population

    • ceicdata.com
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    CEICdata.com, United States US: Incidence of HIV: per 1,000 Uninfected Population [Dataset]. https://www.ceicdata.com/en/united-states/social-health-statistics/us-incidence-of-hiv-per-1000-uninfected-population
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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, 2010 - Dec 1, 2019
    Area covered
    United States
    Description

    United States US: Incidence of HIV: per 1,000 Uninfected Population data was reported at 0.110 Ratio in 2019. This stayed constant from the previous number of 0.110 Ratio for 2018. United States US: Incidence of HIV: per 1,000 Uninfected Population data is updated yearly, averaging 0.120 Ratio from Dec 2010 (Median) to 2019, with 10 observations. The data reached an all-time high of 0.130 Ratio in 2012 and a record low of 0.110 Ratio in 2019. United States US: Incidence of HIV: per 1,000 Uninfected Population data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Social: Health Statistics. Number of new HIV infections among uninfected populations expressed per 1,000 uninfected population in the year before the period.;UNAIDS estimates.;Weighted average;This is the Sustainable Development Goal indicator 3.3.1 [https://unstats.un.org/sdgs/metadata/].

  11. HIV-1 Transmission during Early Infection in Men Who Have Sex with Men: A...

    • plos.figshare.com
    • datasetcatalog.nlm.nih.gov
    txt
    Updated May 31, 2023
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    Erik M. Volz; Edward Ionides; Ethan O. Romero-Severson; Mary-Grace Brandt; Eve Mokotoff; James S. Koopman (2023). HIV-1 Transmission during Early Infection in Men Who Have Sex with Men: A Phylodynamic Analysis [Dataset]. http://doi.org/10.1371/journal.pmed.1001568
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    txtAvailable download formats
    Dataset updated
    May 31, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Erik M. Volz; Edward Ionides; Ethan O. Romero-Severson; Mary-Grace Brandt; Eve Mokotoff; James S. Koopman
    License

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

    Description

    BackgroundConventional epidemiological surveillance of infectious diseases is focused on characterization of incident infections and estimation of the number of prevalent infections. Advances in methods for the analysis of the population-level genetic variation of viruses can potentially provide information about donors, not just recipients, of infection. Genetic sequences from many viruses are increasingly abundant, especially HIV, which is routinely sequenced for surveillance of drug resistance mutations. We conducted a phylodynamic analysis of HIV genetic sequence data and surveillance data from a US population of men who have sex with men (MSM) and estimated incidence and transmission rates by stage of infection.Methods and FindingsWe analyzed 662 HIV-1 subtype B sequences collected between October 14, 2004, and February 24, 2012, from MSM in the Detroit metropolitan area, Michigan. These sequences were cross-referenced with a database of 30,200 patients diagnosed with HIV infection in the state of Michigan, which includes clinical information that is informative about the recency of infection at the time of diagnosis. These data were analyzed using recently developed population genetic methods that have enabled the estimation of transmission rates from the population-level genetic diversity of the virus. We found that genetic data are highly informative about HIV donors in ways that standard surveillance data are not. Genetic data are especially informative about the stage of infection of donors at the point of transmission. We estimate that 44.7% (95% CI, 42.2%–46.4%) of transmissions occur during the first year of infection.ConclusionsIn this study, almost half of transmissions occurred within the first year of HIV infection in MSM. Our conclusions may be sensitive to un-modeled intra-host evolutionary dynamics, un-modeled sexual risk behavior, and uncertainty in the stage of infected hosts at the time of sampling. The intensity of transmission during early infection may have significance for public health interventions based on early treatment of newly diagnosed individuals.Please see later in the article for the Editors' Summary

  12. 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.""

  13. w

    Dataset of incidence of HIV and population of countries in Central America

    • workwithdata.com
    Updated May 8, 2025
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    Work With Data (2025). Dataset of incidence of HIV and population of countries in Central America [Dataset]. https://www.workwithdata.com/datasets/countries?col=country%2Chiv_incidence%2Cpopulation&f=1&fcol0=region&fop0=%3D&fval0=Central+America
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    Dataset updated
    May 8, 2025
    Dataset authored and provided by
    Work With Data
    License

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

    Area covered
    Central America
    Description

    This dataset is about countries in Central America. It has 8 rows. It features 3 columns: incidence of HIV, and population.

  14. Population size, HIV prevalence, and antiretroviral therapy coverage among...

    • zenodo.org
    • data.niaid.nih.gov
    Updated Mar 20, 2024
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    Oliver Stevens; Oliver Stevens; Rebecca Anderson; Rebecca Anderson (2024). Population size, HIV prevalence, and antiretroviral therapy coverage among key populations in sub-Saharan Africa: collation and synthesis of survey data 2010-2023 [Dataset]. http://doi.org/10.5281/zenodo.10838438
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    Dataset updated
    Mar 20, 2024
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Oliver Stevens; Oliver Stevens; Rebecca Anderson; Rebecca Anderson
    License

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

    Time period covered
    Mar 19, 2024
    Area covered
    Sub-Saharan Africa
    Description

    This dataset contains surveillance study estimates for population size, HIV prevalence, and ART coverage among female sex workers (FSW), men who have sex with men (MSM), people who inject drugs (PWID), and transgender men and women (TGM/W) from 2010-2023. It was created to support the UNAIDS Estimates Key Population Workbook for use by HIV estimates teams in sub-Saharan Africa. Key population surveillance reports, including Ministry of Health-led biobehavioural surveys, mapping studies, and academic studies were used to populate the database.

    The dataset was populated using existing key population size estimate databases including:


    and was additionally supplemented by a literature review of peer-reviewed and grey literature sources.

  15. l

    Persons Living with Diagnosed HIV

    • data.lacounty.gov
    • geohub.lacity.org
    • +3more
    Updated Jan 8, 2024
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    County of Los Angeles (2024). Persons Living with Diagnosed HIV [Dataset]. https://data.lacounty.gov/datasets/persons-living-with-diagnosed-hiv
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    Dataset updated
    Jan 8, 2024
    Dataset authored and provided by
    County of Los Angeles
    Area covered
    Description

    This indicator provides information about the rate of persons living with HIV (persons per 100,000 population).Human immunodeficiency virus (HIV) infection remains a significant public health concern, with more than 59,000 Los Angeles County residents estimated to be currently living with HIV. Certain communities, such as low-income communities, communities of color, and sexual and gender minority communities, bear a disproportionate burden of this epidemic. The Ending the HIV Epidemic national initiative strives to eliminate the US HIV epidemic by 2030, focusing on four key strategies: Diagnose, Treat, Prevent, and Respond. Achieving this goal requires a collaborative effort involving cities, community organizations, faith-based institutions, healthcare professionals, and businesses. Together, they can create an environment that promotes prevention, reduces stigma, and empowers individuals to safeguard themselves and their partners from HIV. Stakeholders can advance health equity by focusing on the most affected communities and sub-populations.For more information about the Community Health Profiles Data Initiative, please see the initiative homepage.

  16. e

    Belgian HIV-AIDS Pre-Exposure Prophylaxis database

    • data.europa.eu
    Updated Sep 21, 2022
    + more versions
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    healthdata.be (2022). Belgian HIV-AIDS Pre-Exposure Prophylaxis database [Dataset]. https://data.europa.eu/data/datasets/b2d745ea-5490-45b7-b54f-8f7439b268ac?locale=en
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    Dataset updated
    Sep 21, 2022
    Dataset provided by
    healthdata.be
    Area covered
    Belgium
    Description

    PrEP is the use of an antiretroviral medication by people who are uninfected to prevent the acquisition of HIV. The efficacy of PrEP has been shown in a number of randomised controlled trials including iPREX, Partners PrEP, PROUD and ANRS-IPERGAY. In 2015, the European Centre for Disease Prevention and Control (ECDC) recommended that European Union (EU) and European Economic Area (EEA) countries should consider integrating PrEP into their existing HIV prevention package for those most at risk of HIV infection, starting with men who have sex with men (MSM). This was followed by the World Health Organization (WHO) recommendations that PrEP should be offered as an additional prevention option to all people at substantial risk of HIV infection as part of combination prevention approaches. As a result, several countries in the EU/EEA have either implemented PrEP or are considering options for implementation.

    Since the 1st of June 2017, PrEP is nationally available in Belgium and reimbursed for people who are at increased risk for HIV acquisition. Belgium is one of the countries in Europe reporting a high HIV incidence, with 8.1 new HIV infections per 100 000 inhabitants in 2019.The epidemic mainly affects two populations: men who have sex with men (MSM) and Sub-Saharan African migrants, most of whom have acquired HIV through unprotected heterosexual contacts. A recent study suggests that ongoing clustered transmission in Belgium is almost exclusively driven by MSM.

    As the national PrEP program is brought to scale, the need for a robust monitoring system emerges. An effective PrEP program is one in which people in greatest need of HIV prevention are appropriately identified, offered PrEP, and then continue to receive continued support to use PrEP as needed. Monitoring PrEP program implementation is therefore important to (1) track progress in uptake and coverage among the eligible population, (2) estimate impact on the HIV epidemic, and (3) inform the strategic planning of the program (e.g. cost, resources, supply of commodities).

  17. f

    Data from: Prevalence and correlates of lifetime and recent HIV testing...

    • datasetcatalog.nlm.nih.gov
    • figshare.unimelb.edu.au
    Updated Jan 9, 2019
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    Hill, Adam O (2019). Prevalence and correlates of lifetime and recent HIV testing among men who have sex with men (MSM) who use mobile geo-social networking applications in Greater Tokyo Data Set [Dataset]. https://datasetcatalog.nlm.nih.gov/dataset?q=0000192679
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    Dataset updated
    Jan 9, 2019
    Authors
    Hill, Adam O
    Description

    Data set for Prevalence and correlates of lifetime and recent HIV testing among men who have sex with men (MSM) who use mobile geo-social networking applications in Greater Tokyo.

  18. f

    Molecular epidemiology of HIV-1 infection among men who have sex with men in...

    • plos.figshare.com
    • datasetcatalog.nlm.nih.gov
    docx
    Updated Jun 4, 2023
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    Wei-You Li; Marcelo Chen; Szu-Wei Huang; I-An Jen; Sheng-Fan Wang; Jyh-Yuan Yang; Yen-Hsu Chen; Yi-Ming Arthur Chen (2023). Molecular epidemiology of HIV-1 infection among men who have sex with men in Taiwan from 2013 to 2015 [Dataset]. http://doi.org/10.1371/journal.pone.0202622
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    docxAvailable download formats
    Dataset updated
    Jun 4, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Wei-You Li; Marcelo Chen; Szu-Wei Huang; I-An Jen; Sheng-Fan Wang; Jyh-Yuan Yang; Yen-Hsu Chen; Yi-Ming Arthur Chen
    License

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

    Area covered
    Taiwan
    Description

    Men who have sex with men (MSM) is the major risk population of HIV-1 infection in Taiwan, and its surveillance has become critical in HIV-1 prevention. We recruited MSM subjects from 17 high-risk venues and 4 community centers in northern and southern Taiwan for anonymous HIV-1 screening during 2013–2015. Blood samples were obtained for genotyping and phylogenetic analysis, and a questionnaire survey covering demographic variables and social behavior was conducted. In total, 4,675 subjects were enrolled, yielding a HIV-1 prevalence rate of 4.3% (201/4675). Eight risk factors including subjects who did not always use condoms (OR = 1.509, p = 0.0123), those who used oil-based lubricants (OR = 1.413, p = 0.0409), and those who used recreational drugs (OR = 2.182, p = < .0001) had a higher risk of HIV-1 infection. The annual prevalence and incidence of HIV-1 showed a downward trend from 2013 to 2015 (6.56%, 5.97 per 100 person-years in 2013; 4.53%, 3.97 per 100 person-years in 2014; 1.84%, 2.08 per 100 person-years in 2015). Factors such as always using condoms, water-based lubricant use, correct knowledge of lubricating substitutes, and recreational drug use were significantly associated with the trend of incidence. Phylogenetic tree analysis showed that the cross-regional and international interaction of the local MSM population may have facilitated transmission of HIV. This survey of high-risk venues showed decreased prevalence and incidence of HIV-1 infection in Taiwan from 2013 to 2015, and this may be related to changes in behavioral patterns. Moreover, cross-regional interaction and recreational drug use need to be considered in future surveillance.

  19. f

    Dispersion of the HIV-1 Epidemic in Men Who Have Sex with Men in the...

    • plos.figshare.com
    • figshare.com
    pdf
    Updated Jun 1, 2023
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    Daniela Bezemer; Anne Cori; Oliver Ratmann; Ard van Sighem; Hillegonda S. Hermanides; Bas E. Dutilh; Luuk Gras; Nuno Rodrigues Faria; Rob van den Hengel; Ashley J. Duits; Peter Reiss; Frank de Wolf; Christophe Fraser (2023). Dispersion of the HIV-1 Epidemic in Men Who Have Sex with Men in the Netherlands: A Combined Mathematical Model and Phylogenetic Analysis [Dataset]. http://doi.org/10.1371/journal.pmed.1001898
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    pdfAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    PLOS Medicine
    Authors
    Daniela Bezemer; Anne Cori; Oliver Ratmann; Ard van Sighem; Hillegonda S. Hermanides; Bas E. Dutilh; Luuk Gras; Nuno Rodrigues Faria; Rob van den Hengel; Ashley J. Duits; Peter Reiss; Frank de Wolf; Christophe Fraser
    License

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

    Area covered
    Netherlands
    Description

    BackgroundThe HIV-1 subtype B epidemic amongst men who have sex with men (MSM) is resurgent in many countries despite the widespread use of effective combination antiretroviral therapy (cART). In this combined mathematical and phylogenetic study of observational data, we aimed to find out the extent to which the resurgent epidemic is the result of newly introduced strains or of growth of already circulating strains.Methods and FindingsAs of November 2011, the ATHENA observational HIV cohort of all patients in care in the Netherlands since 1996 included HIV-1 subtype B polymerase sequences from 5,852 patients. Patients who were diagnosed between 1981 and 1995 were included in the cohort if they were still alive in 1996. The ten most similar sequences to each ATHENA sequence were selected from the Los Alamos HIV Sequence Database, and a phylogenetic tree was created of a total of 8,320 sequences. Large transmission clusters that included ≥10 ATHENA sequences were selected, with a local support value ≥ 0.9 and median pairwise patristic distance below the fifth percentile of distances in the whole tree. Time-varying reproduction numbers of the large MSM-majority clusters were estimated through mathematical modeling. We identified 106 large transmission clusters, including 3,061 (52%) ATHENA and 652 Los Alamos sequences. Half of the HIV sequences from MSM registered in the cohort in the Netherlands (2,128 of 4,288) were included in 91 large MSM-majority clusters. Strikingly, at least 54 (59%) of these 91 MSM-majority clusters were already circulating before 1996, when cART was introduced, and have persisted to the present. Overall, 1,226 (35%) of the 3,460 diagnoses among MSM since 1996 were found in these 54 long-standing clusters. The reproduction numbers of all large MSM-majority clusters were around the epidemic threshold value of one over the whole study period. A tendency towards higher numbers was visible in recent years, especially in the more recently introduced clusters. The mean age of MSM at diagnosis increased by 0.45 years/year within clusters, but new clusters appeared with lower mean age. Major strengths of this study are the high proportion of HIV-positive MSM with a sequence in this study and the combined application of phylogenetic and modeling approaches. Main limitations are the assumption that the sampled population is representative of the overall HIV-positive population and the assumption that the diagnosis interval distribution is similar between clusters.ConclusionsThe resurgent HIV epidemic amongst MSM in the Netherlands is driven by several large, persistent, self-sustaining, and, in many cases, growing sub-epidemics shifting towards new generations of MSM. Many of the sub-epidemics have been present since the early epidemic, to which new sub-epidemics are being added.

  20. f

    Understanding Racial HIV/STI Disparities in Black and White Men Who Have Sex...

    • plos.figshare.com
    • datasetcatalog.nlm.nih.gov
    pdf
    Updated Jun 1, 2023
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    Patrick S. Sullivan; John Peterson; Eli S. Rosenberg; Colleen F. Kelley; Hannah Cooper; Adam Vaughan; Laura F. Salazar; Paula Frew; Gina Wingood; Ralph DiClemente; Carlos del Rio; Mark Mulligan; Travis H. Sanchez (2023). Understanding Racial HIV/STI Disparities in Black and White Men Who Have Sex with Men: A Multilevel Approach [Dataset]. http://doi.org/10.1371/journal.pone.0090514
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    pdfAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Patrick S. Sullivan; John Peterson; Eli S. Rosenberg; Colleen F. Kelley; Hannah Cooper; Adam Vaughan; Laura F. Salazar; Paula Frew; Gina Wingood; Ralph DiClemente; Carlos del Rio; Mark Mulligan; Travis H. Sanchez
    License

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

    Description

    BackgroundThe reasons for black/white disparities in HIV epidemics among men who have sex with men have puzzled researchers for decades. Understanding reasons for these disparities requires looking beyond individual-level behavioral risk to a more comprehensive framework.Methods and FindingsFrom July 2010-Decemeber 2012, 803 men (454 black, 349 white) were recruited through venue-based and online sampling; consenting men were provided HIV and STI testing, completed a behavioral survey and a sex partner inventory, and provided place of residence for geocoding. HIV prevalence was higher among black (43%) versus white (13% MSM (prevalence ratio (PR) 3.3, 95% confidence interval (CI): 2.5–4.4). Among HIV-positive men, the median CD4 count was significantly lower for black (490 cells/µL) than white (577 cells/µL) MSM; there was no difference in the HIV RNA viral load by race. Black men were younger, more likely to be bisexual and unemployed, had less educational attainment, and reported fewer male sex partners, fewer unprotected anal sex partners, and less non-injection drug use. Black MSM were significantly more likely than white MSM to have rectal chlamydia and gonorrhea, were more likely to have racially concordant partnerships, more likely to have casual (one-time) partners, and less likely to discuss serostatus with partners. The census tracts where black MSM lived had higher rates of poverty and unemployment, and lower median income. They also had lower proportions of male-male households, lower male to female sex ratios, and lower HIV diagnosis rates.ConclusionsAmong black and white MSM in Atlanta, disparities in HIV and STI prevalence by race are comparable to those observed nationally. We identified differences between black and white MSM at the individual, dyadic/sexual network, and community levels. The reasons for black/white disparities in HIV prevalence in Atlanta are complex, and will likely require a multilevel framework to understand comprehensively.

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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

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

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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;

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