The AIDS Public Information Data Set (APIDS) for years 1981-2002 on CDC WONDER online database contains counts of AIDS (Acquired Immune Deficiency Syndrome) cases reported by state and local health departments, by demographics; location (region and selected metropolitan areas); case-definition; month/year and quarter-year of diagnosis, report, and death (if applicable); and HIV exposure group (risk factors for AIDS). Data are produced by the US Department of Health and Human Services (US DHHS), Public Health Service (PHS), Centers for Disease Control and Prevention (CDC), National Center for HIV, STD and TB Prevention (NCHSTP), Division of HIV/AIDS Prevention (DHP).

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.

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

The Medical Monitoring Project (MMP) is an HIV surveillance system that provides national estimates of HIV-related behaviors and clinical outcomes. When first implemented, MMP excluded persons living with HIV not receiving HIV care. This analysis will describe new case-surveillance-based methods to identify and recruit persons living with HIV who are out of care and at elevated risk for mortality and ongoing HIV transmission. Stratified random samples of all persons living with HIV were selected from the National HIV Surveillance System in five public health jurisdictions from 2012–2014. Sampled persons were located and contacted through seven different data sources and five methods of contact to collect interviews and medical record abstractions. Data were weighted for non-response and case reporting delay. The modified sampling methodology yielded 1159 interviews (adjusted response rate, 44.5%) and matching medical record abstractions for 1087 (93.8%). Of persons with both interview and medical record data, 264 (24.3%) would not have been included using prior MMP methods. Significant predictors were identified for successful contact (e.g., retention in care, adjusted Odds Ratio [aOR] 5.02; 95% Confidence Interval [CI] 1.98–12.73), interview (e.g. moving out of jurisdiction, aOR 0.24; 95% CI: 0.12–0.46) and case reporting delay (e.g. rural residence, aOR 3.18; 95% CI: 2.09–4.85). Case-surveillance-based sampling resulted in a comparable response rate to existing MMP methods while providing information on an important new population. These methods have since been adopted by the nationally representative MMP surveillance system, offering a model for public health program, research and surveillance endeavors seeking inclusion of all persons living with HIV.

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.

NAHDAP acquires, preserves and disseminates data relevant to drug addiction and HIV research. By preserving and making available an easily accessible library of electronic data on drug addiction and HIV infection in the United States, NAHDAP offers scholars the opportunity to conduct secondary analysis on major issues of social and behavioral sciences and public policy.

HIV/AIDS deaths in the U.S. have dropped significantly in recent years. In 1995, the death rate from HIV per 100,000 people was ****. That number has since decreased to *** per 100,000 as of 2023. The reduction in the HIV death rate in the U.S. can be attributed to an increase in access to HIV medications. HIV/AIDS in the U.S. Human immunodeficiency virus (HIV) and acquired immune deficiency syndrome (AIDS) cause a systemic viral infection that damages the immune system. AIDS is a syndrome that is caused by HIV. AIDS is when the immune system is severely weakened by HIV and the body can no longer fight off infections. Among all U.S. states, Georgia, followed by Florida and Louisiana, had the highest rates of new HIV diagnoses in 2022. HIV/AIDS treatments in the U.S. HIV/AIDS treatments include antiretroviral medications to reduce the levels of HIV within the body. The largest funders for HIV/AIDS medications and research are the National Institutes of Health (NIH) and the Ryan White Program. The top HIV drug worldwide, based on revenue generated in 2023 was Biktarvy. Around the world, access to antiretroviral treatment has increased dramatically in recent years, a huge step in reducing the number of HIV-related deaths. There is currently no cure for HIV.

Users can customize data to gather information on the health care use of people living with HIV. Background HIVnet is an interactive data tool from the HIV Research Network at the Agency for Healthcare Research and Quality. It provides researchers, policy makers and public health practitioners with information regarding the health care use of people with HIV. HIVnet focuses on outpatient and inpatient care patterns in large HIV health practices. User Functionality Users begin their query by selecting the statistics of interest, which are grouped into the follow ing categories: inpatient admissions; outpatient visits; inpatient costs; outpatient costs; total costs. Then users can determine how they want their data to be compared (by age, gender/sex, race/ethnicity, risk group, CD4 count, viral load count, antiretroviral therapy prescription). The resulting graph or chart can be saved or downloaded. Data Notes The data used for HIVnet cannot be used to be nationally representative as the sample was taken from specific health practices that cater to a large number of people with HIV. To protect the confidentiality of the participants, users are not able to gather information on geographical region. Whenever a chart is generated, the year of the data used is provided.

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.

Background“Data to Care” (D2C) is a strategy which relies on a combination of public health surveillance data supplemented by clinic data to support continuity of HIV care. The Cooperative Re-Engagement Controlled Trial (CoRECT) was a CDC-sponsored randomized controlled trial of a D2C model, which provided an opportunity to examine the process of implementing an intervention for people with HIV (PWH) who are out-of-care across three public health department jurisdictions. Using the EPIS (Exploration, Preparation, Implementation, Sustainment) framework, we aimed to retrospectively describe the implementation process for each site to provide insights and guidance to inform future D2C activities implemented by public health agencies and their clinical and community partners.MethodsAfter completion of CoRECT, the three (Connecticut, Massachusetts, Philadelphia) trial sites reviewed study protocols and held iterative discussions to describe and compare their processes regarding case identification, interactions with partnering clinics and patients, and sustainability. The EPIS framework provided a structure for comparing key organizational and operational practices and was applied to the entire implementation process.ResultsThe trial sites varied in their implementation processes and the specific elements of the intervention. Factors including prior D2C experience, data management and analytic infrastructure, staff capacity, and relationships with clinic partners informed intervention development and implementation. Additionally, this review identified key lessons learned including to: (1) explore new supplemental sources for public health surveillance data; (2) work with stakeholders representing core functions/components in the early stages of the intervention design process; (3) build flexibility into all components of the follow-up activities; and (4) integrate data sharing, project management, and follow-up activities within existing DPH organizational structure.ConclusionThe CoRECT study provides a general blueprint and lessons learned for implementing a D2C intervention for re-engagement in HIV care. Interventions should be tailored to local operational and structural factors, and responsive to evolving clinical and public health practices.

This data set provides an estimate of the number of people living with Human Immunodeficiency Virus (HIV) Disease at the end of each year for 2012 through 2016 and the number of these persons who have injection drug use identified as the primary risk for having acquired the infection. The data sets also provides the number of new diagnoses of HIV Disease by county among all persons and among those with injection drug identified as the primary risk. These data are derived through HIV surveillance activities of the Pennsylvania Department of Health. Laboratories and providers are required to report HIV test results for all individuals with a result that indicates the presence of HIV infection. These include detectable viral load results and CD4 results below 200 cells. These data are reported electronically to the Pennsylvania National Electronic Disease Surveillance System. The most recent patient address information obtained from all reports (both HIV and non-HIV reports) is used to identify last known county of residence in 2016. Cases are also matched to lists that identify individuals who have been reported to be living outside of Pennsylvania by the US Centers for Disease Control and Prevention (CDC) to remove cases that are presumed to have moved from Pennsylvania. Address data for Philadelphia County cases are extracted from the Pennsylvania enhanced HIV/AIDS Reporting System.

IDU: use of non-prescribed injection drugs (e.g., heroin, fentanyl, cocaine, etc.)

HIV Disease: Confirmed infection with the Human Immunodeficiency Virus (HIV). Acquired Immunodeficiency Syndrome (AIDS) is a stage of HIV Disease marked by a low CD4 count and/or certain co-morbid conditions.

Background: To optimally allocate limited health resources in responding to the HIV epidemic, South Africa has undertaken to generate local epidemiological profiles identifying high disease burden areas. Central to achieving this, is the need for readily available quality health data linked to both large and small geographic areas. South Africa has relied on national population-based surveys: the Household HIV Survey and the National Antenatal Sentinel HIV and Syphilis Prevalence Survey (ANC) amongst others for such data for informing policy decisions. However, these surveys are conducted approximately every 2 and 3 years creating a gap in data and evidence required for policy. At subnational levels, timely decisions are required with frequent course corrections in the interim. Routinely collected HIV testing data at public health facilities have the potential to provide this much needed information, as a proxy measure of HIV prevalence in the population, when survey data is not available. The South African District health information system (DHIS) contains aggregated routine health data from public health facilities which is used in this article.Methods: Using spatial interpolation methods we combine three “types” of data: (1) 2015 gridded high-resolution population data, (2) age-structure data as defined in South Africa mid-year population estimates, 2015; and (3) georeferenced health facilities HIV-testing data from DHIS for individuals (15–49 years old) who tested in health care facilities in the district in 2015 to delineate high HIV disease burden areas using density surface of either HIV positivity and/or number of people living with HIV (PLHIV). For validation, we extracted interpolated values at the facility locations and compared with the real observed values calculating the residuals. Lower residuals means the Inverse Weighted Distance (IDW) interpolator provided reliable prediction at unknown locations. Results were adjusted to provincial published HIV estimates and aggregated to municipalities. Uncertainty measures map at municipalities is provided. Data on major cities and roads networks was only included for orientation and better visualization of the high burden areas.Results: Results shows the HIV burden at local municipality level, with high disease burden in municipalities in eThekwini, iLembe and uMngundgudlovu; and around major cities and national routes.Conclusion: The methods provide accurate estimates of the local HIV burden at the municipality level. Areas with high population density have high numbers of PLHIV. The analysis puts into the hand of decision makers a tool that they can use to generate evidence for HIV programming. The method allows decision makers to routinely update and use facility level data in understanding the local epidemic.

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.""

This data set shows the planned funding allocations for HIV medical and support services in the Austin area from the Ryan White HIV/AIDS Program Part A. The HIV Planning Council, a City of Austin Board/Commission is the responsible body for the allocation of Ryan White HIV/AIDS Program Part A funding. This program provides grant funding from the Health Resources and Services Administration (HRSA) for medical and support services to the Austin Area. Allocation Plans are developed using data including but not limited to: epidemiological overview and demographic information for people living with HIV (PLWH), service utilization data, needs assessment data, and expenditure trends. Allocation Plans are developed based on a maximum amount of funds that can be applied as dictated by HRSA for each grant year. Actual awarded Ryan White Part A amounts may differ from the plan. The HIV Planning Council sets alternative funding scenario plans to adapt the Allocation Plan to the actual amount of Part A funds awarded. The HIV Planning Council can re-allocate awarded funds at any time during the grant year to reflect changes in service needs or the ability to expend funds in each service category. Minority AIDS Initiative (MAI) funding is a subset of Ryan White Part A which funds services for populations disproportionately affected by HIV.

Among all countries worldwide those in sub-Saharan Africa have the highest rates of HIV. The countries with the highest rates of HIV include Eswatini, South Africa, and Lesotho. In 2024, Eswatini had the highest prevalence of HIV with a rate of around ** percent. Other countries, such as Zimbabwe, have significantly decreased their HIV prevalence. Community-based HIV services are considered crucial to the prevention and treatment of HIV. HIV Worldwide The human immunodeficiency virus (HIV) is a viral infection that is transmitted via exposure to infected semen, blood, vaginal and anal fluids, and breast milk. HIV destroys the human immune system, rendering the host unable to fight off secondary infections. Globally, the number of people living with HIV has generally increased over the past two decades. However, the number of HIV-related deaths has decreased significantly in recent years. Despite being a serious illness that affects millions of people, medication exists that effectively manages the progression of the virus in the body. These medications are called antiretroviral drugs. HIV Treatment Generally, global access to antiretroviral treatment has increased. However, despite being available worldwide, not all adults have access to antiretroviral drugs. There are many different antiretroviral drugs available on the market. As of 2024, ********, an antiretroviral marketed by Gilead, was the leading HIV treatment based on revenue.

ABSTRACT Objectives: to identify the socio-spatial determinants associated with the incidence of infection by the human immunodeficiency virus (HIV) described in national and international literature. Methods: integrative literature review that included original articles indexed in the LILACS, PUBMED, CINAHL, and Scopus databases, from 2015 to 2019. The synthesis of the articles was done in a descriptive manner in two categories according to the type of approach. Results: 13 articles were selected, with a predominance of ecological studies. Regions with deficient access to health services, high population density, higher rates of poverty, intense migratory flow, border areas, as well as precarious socioeconomic conditions, and risk behaviors are associated with higher rates of infection. Final Considerations: the influence of regional inequalities on the incidence of HIV infection is revealed, confirming the relevance of spatial analysis techniques for mapping the distribution of diseases and identifying risk areas.

This is the replication kit for "Evidence and Lessons on the Health Impacts of Public Health Funding from the Fight against HIV/AIDS". HIV/AIDS has been one of the largest public health crises in recent history, and the U.S. federal government has spent hundreds of billions of dollars fighting the disease. This study examines the impact of the large amounts of federal funding allocated to U.S. cities to combat HIV/AIDS through the Ryan White CARE Act's first title. The findings indicate that the cost to avoid an HIV/AIDS death through the program is roughly $334,000, that the program has saved approximately 57,000 lives through 2018, and that funding disparities are responsible for the uneven progress in combating HIV/AIDS across the United States.

The number of HIV cases in Sweden fluctuated during the provided time interval, and amounted to *** cases in 2024. The highest number of cases were in 2014 and 2018 when they amounted to ***. In 2022, *** new cases of HIV were diagnosed in Sweden, which is a higher number than for its neighboring countries Denmark, Norway and Finland. The most common disease group HIV is primarily spread through sexual contact or through blood contact, and in Sweden in 2023, the most common ages among the transmitted was individuals from 30 to 39 years, and there were more transmissions among men than women.   Increase in other sexually transmitted diseases The spread of HIV in Sweden is today limited, to a large extent because of rapid diagnosis and efficient treatment to basically all transmitted. Furthermore, the long-term increase of chlamydia that has been going on for years seems to have stopped, and the number of chlamydia cases are decreasing. However, the spread of other sexually transmitting diseases have an opposite trend. The number of syphilis infection cases has been increasing since 2014, and according to Folkhälsomyndigheten (the Public Health Agency of Sweden), it is especially worrying that the previously low spread of gonorrhea is also increasing.

The Chicago Department of Public Health (CDPH) Division of STD/HIV/AIDS Public Policy and Programs works in partnership with communities to advance the prevention and treatment of HIV and sexually transmitted infections (STIs). CDPH maintains drop-in STI Specialty Clinics & HIV Early Intervention Services in South Austin, Englewood, Roseland, Lakeview and West Town that diagnose and treat STIs and provide information about condom use and other STI prevention methods. These clinics are offered at no cost, and on a first-come, first-serve basis. This metric tracks the percent of patients served by the STI Specialty Clinics per month out of the total number of people who seek care. The monthly performance goal is to serve 100% of those seeking care. For more information about City STI/HIV/AIDS Services, see http://www.cityofchicago.org/city/en/depts/cdph/provdrs/sti_hiv_aids.html