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;

Dataset Overview

The dataset provides a comprehensive look at HIV/AIDS adult prevalence rates, the number of people living with HIV, and annual deaths across different countries. It is based on publicly available data sources such as the CIA World Factbook, UNAIDS AIDS Info, and other global health organizations. The dataset primarily focuses on adult HIV prevalence (ages 15–49) and includes estimates from recent years (e.g., 2023–2024).

Data Science Applications

This dataset can be used for: - Epidemiological Analysis: Understanding the regional distribution of HIV/AIDS and identifying high-prevalence areas. - Predictive Modeling: Developing machine learning models to predict HIV prevalence trends or identify risk factors. - Resource Allocation: Informing policymakers about regions requiring urgent intervention or resource allocation. - Health Outcome Monitoring: Tracking progress in combating HIV/AIDS over time. - Social Determinants Research: Analyzing the relationship between socio-economic factors and HIV prevalence.

Column Descriptors

1. Country/Region: The geographical area being analyzed.
2. Adult Prevalence (%): Percentage of adults aged 15–49 living with HIV.
3. Number of People with HIV/AIDS: Absolute count of individuals living with HIV in the region.
4. Annual Deaths from HIV/AIDS: Number of deaths attributed to HIV/AIDS annually.
5. Year of Estimate: The year when the data was collected or estimated.

Ethically Mined Data

The dataset is ethically sourced from publicly available and credible platforms such as the CIA World Factbook, UNAIDS, and WHO. These organizations ensure transparency and ethical standards in data collection, protecting individual privacy while providing aggregate statistics for research purposes.

Acknowledgments

1. Data Source Platforms:
   • CIA World Factbook
   • UNAIDS AIDS Info
   • WHO Global Health Observatory
2. Dataset Visualization Image:
   • Created using DALL-E 3 for illustrative purposes.
3. Research Support:
   • Contributions from platforms like ResearchGate, NIMH, and others for insights into data science applications in HIV research.

This dataset serves as a valuable tool for researchers, policymakers, and public health professionals in addressing the global challenge of HIV/AIDS.

Context

In the time of epidemics, what is the status of HIV AIDS across the world, where does each country stands, is it getting any better. The data set should be helpful to explore much more about above mentioned factors.

Content

The data set contains data on

1. No. of people living with HIV AIDS
2. No. of deaths due to HIV AIDS
3. No. of cases among adults (19-45)
4. Prevention of mother-to-child transmission estimates
5. ART (Anti Retro-viral Therapy) coverage among people living with HIV estimates
6. ART (Anti Retro-viral Therapy) coverage among children estimates

Acknowledgements / Data Source

• WHO : https://www.who.int/hiv/data/en/
• UNESCO : https://data.unicef.org/resources/dataset/hiv-aids-statistical-tables/

Collection methodology

https://github.com/imdevskp/hiv_aids_who_unesco_data_cleaning

Cover Photo

Photo by Anna Shvets from Pexels https://www.pexels.com/photo/red-ribbon-on-white-surface-3900425/

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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/].

This data set contains Quarterly Results and yearly Targets by Operating Unit, Sub-National Units 1–2, PSNU Prioritization, Coarse Age and Sex for Fiscal Years 2016 – 2020 and the following subset of Testing and Treatment indicators: HTS_TST (People receiving testing and counseling services), HTS_TST_POS (People newly testing positive for HIV), TX_CURR (People currently receiving ART), TX_NEW (People newly enrolled in ART), TX_PVLS (Viral Load Documented) and TX_RET (People who have remained in treatment 12 months after ART initiation). Data can be downloaded as a compressed (zip) file, which contains text files in csv (comma separated values) format. For indicator definitions, please consult the latest MER Indicator Reference Guide.For additional PEPFAR data, please visit data.pepfar.gov. Unless otherwise noted, the content, data, documentation, code, and related materials on data.pepfar.gov is public domain and made available with a Creative Commons CC0 1.0 Universal dedication and license-free (per US Code 17 USC § 105). Citation of data.pepfar.gov as a source of the data is appreciated.

Human Immunodeficiency Virus (HIV) remains a significant public health concern, with adults being at greater risk. Thus, understanding the dynamics of HIV transmission is crucial for effective prevention and control strategies, hence the need for a continuous clinical survey of the patients’ records of diagnosis and treatment for HIV. The data include the quarterly records of 138 adults diagnosed with HIV at Osun State University Teaching Hospital, Nigeria which involves the number of adults tested positive and negative for each of the endogenous variables discussed below. Information was sought using a convenient sampling method, which entails careful selection of individual records based on availability. The data was grouped into quarterly records of the diagnosed adults, with an average age ranging between 26 years and 52 years, and spread between the years 2008 and 2021. The records comprise 72 Females and 66 Males while the presence of each symptom is coded as 1 and the absence coded as 0. The endogenous variables observed in the clinical records of the surveyed patients are Fever (F), Diarrhea (D), Abdominal pain (AP), Skin rash (SR), Mouth sour (MS), Cellulitis (C), Coughing with sputum (CS), Loss of appetite (LA), Genital infections (GI), Medical fitness (MF), Headache (H), Catarrh (CA), Weight Loss (WL), Excessive Sweat (ES), Mouth Sour (MS), and Body weakness (BW). The impacts of these aforementioned factors would be examined on the spread of HIV. The clinical survey revealed that 77 individuals (55.80%) did not experience fever, while 61 (44.20%) did. Diarrhea was reported by 39 participants (28.26%), leaving 99 (71.74%) without this symptom. Abdominal pain and cellulitis were both reported by only 4 individuals (2.90%), with 134 participants (97.10%) indicating no occurrences of these symptoms. In terms of medical fitness, 110 individuals (79.71%) reported no fitness issues, whereas 28 (20.29%) reported having some. Cough with sputum affected 50 participants (36.23%), while 88 (63.77%) did not report this symptom. Headaches were almost universally absent, with 137 individuals (99.28%) not experiencing any. Catarrh was present in 14 participants (10.14%), with 124 (89.86%) reporting no instances. Loss of appetite was reported by 5 individuals (3.62%), and skin rashes were observed in 28 participants (20.29%). Weight loss affected 49 individuals (35.51%), and excessive sweating was reported by 137 participants (99.28%). Mouth soreness was noted in 27 participants (19.57%), while genital infections were reported by 6 individuals (4.35%). Body weakness was reported by 49 participants (35.51%). In the age distribution, 56 individuals (40.58%) fall into the young adult’s category while 82 individuals (59.42%) are categorized as older adults. Notably, all participants in the study were confirmed to be HIV positive, emphasizing a focused analysis of this group’s health characteristics.

This dataset provides detailed insights into the prevalence of HIV/AIDS among adults (ages 15–49) across various countries and regions. The data is primarily sourced from the CIA World Factbook and the UNAIDS AIDSinfo platform and reflects the most recent available estimates as of 2022–2024.

What’s Included:

Country/Region – The name of each nation or area.

Adult Prevalence of HIV/AIDS (%) – The percentage of adults estimated to be living with HIV.

Number of People with HIV/AIDS – Estimated count of people infected in each country.

Annual Deaths from HIV/AIDS – Estimated number of HIV/AIDS-related deaths per year.

Year of Estimate – The year the data was reported or estimated.

Key Highlights:

Global Prevalence: Around 0.7% of the global population was living with HIV in 2022, affecting nearly 39 million people.

Hotspots: The epidemic is most severe in Southern Africa, with countries like Eswatini, Botswana, Lesotho, and Zimbabwe reporting adult prevalence rates above 20%.

High Burden Countries:

South Africa: 17.3% prevalence, approximately 9.2 million infected

Tanzania: approximately 7.49 million

Mozambique: approximately 2.48 million

Nigeria: approximately 2.45 million (1.3% prevalence)

Notes:

Data may vary in accuracy and is subject to ongoing updates and verification.

Some entries include a dash ("-") where data was not published or available.

Countries with over 1% adult prevalence are categorized under Generalized HIV Epidemics (GHEs) by UNAIDS.

BackgroundIn 2015, there were approximately 40,000 new HIV diagnoses in the United States. Pre-exposure prophylaxis (PrEP) is an effective strategy that reduces the risk of HIV acquisition; however, uptake among those who can benefit from it has lagged. In this study, we 1) compared the characteristics of patients who were prescribed PrEP with individuals newly diagnosed with HIV infection, 2) identified the specialties of practitioners prescribing PrEP, 3) identified metropolitan statistical areas (MSAs) within the US where there is relatively low uptake of PrEP, and 4) reported median amounts paid by patients and third-party payors for PrEP.Methods and findingsWe analyzed prescription drug claims for individuals prescribed PrEP in the Integrated Dataverse (IDV) from Symphony Health for the period of September 2015 to August 2016 to describe PrEP patients, prescribers, relative uptake, and payment methods in the US. Data were available for 75,839 individuals prescribed PrEP, and findings were extrapolated to approximately 101,000 individuals, which is less than 10% of the 1.1 million adults for whom PrEP was indicated. Compared to individuals with newly diagnosed HIV infection, PrEP patients were more likely to be non-Hispanic white (45% versus 26.2%), older (25% versus 19% at ages 35–44), male (94% versus 81%), and not reside in the South (30% versus 52% reside in the South).Using a ratio of the number of PrEP patients within an MSA to the number of newly diagnosed individuals with HIV infection, we found MSAs with relatively low uptake of PrEP were concentrated in the South. Of the approximately 24,000 providers who prescribed PrEP, two-thirds reported primary care as their specialty. Compared to the types of payment methods that people living with diagnosed HIV (PLWH) used to pay for their antiretroviral treatment in 2015 to 2016 reported in the Centers for Disease Control and Prevention (CDC) HIV Surveillance Special Report, PrEP patients were more likely to have used commercial health insurance (80% versus 35%) and less likely to have used public healthcare coverage or a publicly sponsored assistance program to pay for PrEP (12% versus 45% for Medicaid). Third-party payors covered 95% of the costs of PrEP. Overall, we estimated the median annual per patient out-of-pocket spending on PrEP was approximately US$72. Limitations of this study include missing information on prescription claims of patients not included in the database, and for those included, some patients were missing information on patient diagnosis, race/ethnicity, educational attainment, and income (34%–36%).ConclusionsOur findings indicate that in 2015–2016, many individuals in the US who could benefit from being on PrEP were not receiving this HIV prevention medication, and those prescribed PrEP had a significantly different distribution of characteristics from the broader population that is at risk for acquiring HIV. PrEP patients were more likely to pay for PrEP using commercial or private insurance, whereas PLWH were more likely to pay for their antiretroviral treatment using publicly sponsored programs. Addressing the affordability of PrEP and otherwise promoting its use among those with indications for PrEP represents an important opportunity to help end the HIV epidemic.

This collection consists of geospatial data layers and summary data at the country and country sub-division levels that are part of USAID's Demographic Health Survey Spatial Data Repository. This collection includes geographically-linked health and demographic data from the DHS Program and the U.S. Census Bureau for mapping in a geographic information system (GIS). The data includes indicators related to: fertility, family planning, maternal and child health, gender, HIV/AIDS, literacy, malaria, nutrition, and sanitation. Each set of files is associated with a specific health survey for a given year for over 90 different countries that were part of the following surveys:Demographic Health Survey (DHS)Malaria Indicator Survey (MIS)Service Provisions Assessment (SPA)Other qualitative surveys (OTH)Individual files are named with identifiers that indicate: country, survey year, survey, and in some cases the name of a variable or indicator. A list of the two-letter country codes is included in a CSV file.Datasets are subdivided into the following folders:Survey boundaries: polygon shapefiles of administrative subdivision boundaries for countries used in specific surveys. Indicator data: polygon shapefiles and geodatabases of countries and subdivisions with 25 of the most common health indicators collected in the DHS. Estimates generated from survey data.Modeled surfaces: geospatial raster files that represent gridded population and health indicators generated from survey data, for several countries.Geospatial covariates: CSV files that link survey cluster locations to ancillary data (known as covariates) that contain data on topics including population, climate, and environmental factors.Population estimates: spreadsheets and polygon shapefiles for countries and subdivisions with 5-year age/sex group population estimates and projections for 2000-2020 from the US Census Bureau, for designated countries in the PEPFAR program.Workshop materials: a tutorial with sample data for learning how to map health data using DHS SDR datasets with QGIS. Documentation that is specific to each dataset is included in the subfolders, and a methodological summary for all of the datasets is included in the root folder as an HTML file. File-level metadata is available for most files. Countries for which data included in the repository include: Afghanistan, Albania, Angola, Armenia, Azerbaijan, Bangladesh, Benin, Bolivia, Botswana, Brazil, Burkina Faso, Burundi, Cape Verde, Cambodia, Cameroon, Central African Republic, Chad, Colombia, Comoros, Congo, Congo (Democratic Republic of the), Cote d'Ivoire, Dominican Republic, Ecuador, Egypt, El Salvador, Equatorial Guinea, Eritrea, Eswatini (Swaziland), Ethiopia, Gabon, Gambia, Ghana, Guatemala, Guinea, Guyana, Haiti, Honduras, India, Indonesia, Jordan, Kazakhstan, Kenya, Kyrgyzstan, Lesotho, Liberia, Madagascar, Malawi, Maldives, Mali, Mauritania, Mexico, Moldova, Morocco, Mozambique, Myanmar, Namibia, Nepal, Nicaragua, Niger, Nigeria, Pakistan, Papua New Guinea, Paraguay, Peru, Philippines, Russia, Rwanda, Samoa, Sao Tome and Principe, Senegal, Sierra Leone, South Africa, Sri Lanka, Sudan, Tajikistan, Tanzania, Thailand, Timor-Leste, Togo, Trinidad and Tobago, Tunisia, Turkey, Turkmenistan, Uganda, Ukraine, Uzbekistan, Viet Nam, Yemen, Zambia, Zimbabwe

Source: https://en.wikipedia.org/wiki/HIV_adult_prevalence_rate This dataset provides detailed insights into the prevalence of HIV/AIDS among adults (ages 15–49) across various countries and regions 🌐. The data is primarily sourced from the CIA World Factbook and UNAIDS AIDS info platform, and reflects the most recent available estimates as of 2022–2024 📅.

📌 What's Included: Country/Region 🗺️ – The name of each nation or area.

Adult Prevalence of HIV/AIDS (%) 🔬 – The percentage of adults estimated to be living with HIV.

Number of People with HIV/AIDS 👥 – Estimated count of people infected in each country.

Annual Deaths from HIV/AIDS ⚰️ – Estimated number of HIV/AIDS-related deaths per year.

Year of Estimate 📆 – The year the data was reported or estimated.

📈 Key Highlights: Global Prevalence: Around 0.7% of the global population was living with HIV in 2022, affecting nearly 39 million people.

Hotspots: The epidemic is most severe in Southern Africa, with countries like Eswatini, Botswana, Lesotho, and Zimbabwe reporting adult prevalence rates above 20% 🔥.

High Burden Countries:

🇿🇦 South Africa: 17.3% prevalence, ~9.2 million infected.

🇹🇿 Tanzania: ~7.49 million.

🇲🇿 Mozambique: ~2.48 million.

🇳🇬 Nigeria: ~2.45 million (1.3% prevalence).

⚠️ Notes: Data may vary in accuracy and is subject to ongoing updates and verification 🔍.

Some entries include a dash ("-") where data was not published or available ❌.

Countries with over 1% adult prevalence are categorized under Generalized HIV Epidemics (GHEs) by UNAIDS 🚨.

📚 Data Sources: CIA World Factbook 🌐

UNAIDS AIDS Info 💉

Wikipedia 🧠 (used as a collection and compilation point, not primary source)

https://en.wikipedia.org/wiki/HIV_adult_prevalence_rate

United States US: Incidence of HIV: % of Uninfected Population Aged 15-49 data was reported at 0.020 % in 2014. This stayed constant from the previous number of 0.020 % for 2013. United States US: Incidence of HIV: % of Uninfected Population Aged 15-49 data is updated yearly, averaging 0.030 % from Dec 2008 (Median) to 2014, with 7 observations. The data reached an all-time high of 0.030 % in 2012 and a record low of 0.020 % in 2014. United States US: Incidence of HIV: % of Uninfected 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. Number of new HIV infections among uninfected populations ages 15-49 expressed per 100 uninfected population in the year before the period.; ; UNAIDS estimates.; Weighted Average;

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.

Source: The World Bank Last Updated: 10/26/2023 Database: World Development Indicators Series: Prevalence of HIV, total (% of population ages 15-49) Adults (ages 15+) and children (ages 0-14) newly infected with HIV Adults (ages 15-49) newly infected with HIV Antiretroviral therapy coverage (% of people living with HIV) Antiretroviral therapy coverage for PMTCT (% of pregnant women living with HIV) Children (0-14) living with HIV Children (ages 0-14) newly infected with HIV Incidence of HIV, ages 15-24 (per 1,000 uninfected population ages 15-24) Incidence of HIV, ages 15-49 (per 1,000 uninfected population ages 15-49) Incidence of HIV, all (per 1,000 uninfected population) Prevalence of HIV, female (% ages 15-24) Prevalence of HIV, male (% ages 15-24) Women's share of population ages 15+ living with HIV (%) Young people (ages 15-24) newly infected with HIV

https://datacatalog.worldbank.org/public-licenses#cc-by

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.

The Sexually Transmitted Disease (STD) Morbidity online databases on CDC WONDER contain case reports reported from the 50 United States and D.C., Puerto Rico, Virgin Islands and Guam. The online databases report the number of cases and disease incidence rates by year, state, disease, age, sex of patient, type of STD, and area of report. Data are produced by the U.S. Department of Health and Human Services, Public Health Service, Centers for Disease Control and Prevention (CDC), National Center for HIV/AIDS, viral Hepatitis, STD and TB Prevention (NCHHSTP).

IntroductionTransgender and gender non-binary (TGNB) individuals are disproportionally affected by HIV and face high rates of discrimination and stigmatization, resulting in limited access to HIV prevention services. Pre-exposure prophylaxis (PrEP) is highly efficacious for reducing the risk of HIV transmission. However, little research is available regarding PrEP awareness and utilization among TGNB adolescents and young adults (AYA).MethodsTGNB AYA ages 15–24 years old were recruited between December 2021 and November 2022 for participation in a one-time, anonymous online survey study to assess PrEP awareness and perceptions, as well as barriers to its use. Participants were recruited from seven academic centers offering gender-affirming care to TGNB AYA across the United States.ResultsOf the 156 TGNB AYA individuals who completed the survey, most (67%) were aware of PrEP; however, few (7%) had been prescribed PrEP. Many (60%) had not spoken to a medical provider and, even if the medication was free and obtained confidentially, most participants did not plan to take PrEP due to low perceived HIV risk, lack of PrEP knowledge, and concern about interactions between their hormone therapy and PrEP.DiscussionThese findings underscore the need for broad PrEP educational efforts for both TGNB AYA and their providers to improve knowledge, identify potential PrEP candidates among TGNB AYA and improve access by addressing identified barriers.

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

In the combined data set five individual data sets were combined, guardians for both infants younger than 2 years and children 2 to 11 years, children 12 to 14 years, youths and adults 15 years and older. The data set contains information on: biographical data, media, communication and norms, knowledge and perceptions of HIV/AIDS, male circumcision, sexual debut, partners and partner characteristics, condoms, vulnerability, HIV testing, alcohol and substance use, general perceptions about government, health and violence in the community. The data set contains 810 variables and 23369 cases. Subsequent to the dissemination of version 1 of this data set it was discovered that the data of the following variables were missing: rq240a - rq240f. This was corrected and additionally two variables without descriptions were removed from the data set. A new data set is disseminated as version 2. South Africa continues to have the largest number of people living with HIV/AIDS in the World. This study intends to understand the determinants that lead South Africans to be vulnerable and susceptible to HIV. This is the third in a series of household surveys conducted by Human Sciences Research Council (HSRC), that allow for tracking of HIV and associated determinants over time using a slightly same methodology used in 2002 and 2005 survey, making it the third national-level repeat survey. The 2002 and 2005 surveys included individuals aged 2+ years living in South Africa while 2008 survey included individuals of all ages living in South Africa, including infants younger than 2 years of age. The interval of three years since 2002 allows for an exploration of shifts over time against a complex of demographic and other variables, as well as allowing for investigation of the new areas. The survey provides the first nationally representative HIV incidence estimates. The study key objectives were to: determine the prevalence of HIV infection in South Africa; examine the incidence of HIV infection in South Africa; assess the relationship between behavioural factors and HIV infection in South Africa; describe trends in HIV prevalence, HIV incidence, and risk behaviour in South Africa over the period 2002-2008; investigate the link between social, values, and cultural determinants and HIV infection in South Africa; assess the type and frequency of exposure to major national behavioural change communication programmes and assess their relationship to HIV prevention, AIDS treatment, care, and support; describe male circumcision practices in South Africa and assess its acceptability as a method of HIV prevention; collect data on the health conditions of South Africans; and contribute to the analysis of the impact of HIV/AIDS on society. In the 13440 valid households or visiting points, 10856 agreed to participate in the survey, 23369 individuals (no more than 4 per household, including infants under 2 years) were eligible to be interviewed, and 20826 individuals completed the interview. Of the 23369 eligible individuals, 15031 agreed to provide a blood specimen for HIV testing and were anonymously linked to the behavioural questionnaires. the household response rate was 80.8%, the individual response rate was 89.1% and the overall response rate for HIV testing was 64.3%. Clinical measurements#|#Face-to-face interview#|#Focus group#|#Observation South African population, all ages from urban formal, urban informal, rural formal (farms), rural informal (tribal area) settlements. As in previous surveys, a multi-stage disproportionate, stratified sampling approach was used. A total of 1 000 census enumeration areas (EAs) from the 2001 population census were selected from a database of 86 000 EAs and mapped in 2007 using aerial photography to create a new updated Master Sample as a basis for sampling visiting points/households. The selection of EAs was stratified by province and locality type. Locality types were identified as urban formal, urban informal, rural formal (including commercial farms), and rural informal. In the formal urban areas, race was also used as a third stratification variable (based on the predominant race group in the selected EA at the time of the 2001 census). The allocation of EAs to different stratification categories was disproportionate; that means, over-sampling or over-allocation of EAs was done, for example, in areas that were dominated by Indian, coloured or white race groups to ensure that the minimum required sample size in those smaller race groups was obtained. The Master Sample was designed to allow reporting of results (i.e. reporting domain) at a provincial, geotype and race level. A reporting domain is defined as that domain at which estimates of a population characteristic or variable should be of an acceptable precision for the presentation of survey results. A visiting point is defined as a separate (non-vacant) residential stand, address, structure, and flat in a block of flats or homestead. The 2001 estimate of visiting points was used as the Measure of Size (MOS) in the drawing of the sample. A maximum of four visits were made to each VP to optimise response. Fieldworkers enumerated household members, using a random number generator to select the respondent and then preceded with the interview. All people in the households, resident at the visiting point were initially listed, after which the eligible individual was randomly selected in each of the following three age groups: under 2 years, 2-14 years, 15-24 years and 25+ years. These individuals constituted the USUs of this study. Having completed the sample design, the sample was drawn with 1 000 PSUs or EAs being selected throughout South Africa. These PSUs were allocated to each of the explicit strata. With a view to obtaining an approximately self-weighting sample of visiting points (i.e. SSUs), (a) the EAs were drawn with probability proportional to the size of the EA using the 2001 estimate of the number of visiting points in the EA database as a measure of size (MOS) and (b) to draw an equal number of visiting points (i.e. SSUs) from each drawn EA. An acceptable precision of estimates per reporting domain requires that a sample of sufficient size be drawn from each of the reporting domains. Consequently, a cluster of 15 VP was systematically selected on the aerial photography produced for each of the EAs in the master sample. Since it is not possible to determine on an aerial photograph whether a 'dwelling unit' is indeed a residential structure or whether it was occupied (i.e. people sleeping there), it was decided to form clusters of 15 dwelling units per PSU, allowing on average for one invalid dwelling unit in the cluster of 15 dwelling units. Previous experience at Statistics SA indicated a sample size of 10 households per PSU to be very efficient, balancing cost and efficiency. The VP questionnaire was administered by the fieldworker, and in follow-up, participant selection was made by the supervisor. Participants aged 12 years and older who consented were all interviewed and also asked to provide dried blood spots (DBS) specimens for HIV testing. In case of 0-11 years, parents/guardians were interviewed but DBS specimens were obtained from the children. The sample size estimate for the 2008 survey was guided by the (1) requirement for measuring change over time in order to detect a change in HIV prevalence of 5 percentage points in each of the main reporting domains, namely gender, age-group, race, locality type, and province (5% level of significance, 80% power, two-sided test), and (2) the requirement of an acceptable precision of estimates per reporting domain; that is, to be able to estimate HIV prevalence in each of the main reporting domains with a precision level of less than 4%, which is equivalent to the expected width of the 95% confidence interval (z-score at the 95% level for two-sided test). A design effect of 2 was assumed. Overall, a total of 20826 interviewed participants composed of 4981 children (0-14 years), 5344 youths (15-24 years) and 10501 adults (25+ years) were interviewed. The sample was designed with the view to enable reporting of the results on province level, on geography type area and on race of the respondent. The total sample size was limited by financial constraints, but based on other HSRC experience in sample surveys it was decided to aim at obtaining a minimum of 1 200 households per race group. The number of respondents per household for the study was expected to vary between one and three (one respondent in each of the three age groups). More females (68.9%) than males (62.02%) were tested for HIV. The 25+ years age group was the most compliant (68.8%), and 2-14 years the least (58.9%). The highest testing response rate was found in urban informal settlements (72.5%) and the lowest in urban formal areas (62.8%).

United States US: Newly Infected with HIV: Adults (Aged 15+) and Children (Aged 0-14) data was reported at 39,000.000 Number in 2015. This stayed constant from the previous number of 39,000.000 Number for 2014. United States US: Newly Infected with HIV: Adults (Aged 15+) and Children (Aged 0-14) data is updated yearly, averaging 40,500.000 Number from Dec 2008 (Median) to 2015, with 8 observations. The data reached an all-time high of 44,000.000 Number in 2009 and a record low of 39,000.000 Number in 2015. United States US: Newly Infected with HIV: Adults (Aged 15+) and Children (Aged 0-14) 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. Number of adults (ages 15+) and children (ages 0-14) newly infected with HIV.; ; UNAIDS estimates.; ;