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;

Infection with HIV (human immunodeficiency virus) can lead to AIDS (acquired immunodeficiency syndrome). AIDS results in a gradual and persistent decline and failure of the immune system, resulting in a heightened risk of life-threatening infection and cancers.

In the majority of cases, HIV is a sexually transmitted infection. However, HIV can also be transmitted from mother to child, during pregnancy or childbirth, or through breastfeeding. Non-sexual transmission can also occur by sharing injection equipment such as needles.

Other research and writing on HIV/AIDS on Our World in Data:

Antiretroviral therapy has saved millions of lives from AIDS and could save more See all interactive charts on HIV/AIDS ↓

HIV/AIDS is one of the world's most fatal infectious disease More than three-quarters of a million people die from HIV/AIDS each year; in some countries, it's the leading cause of death HIV/AIDS is one of the world's most fatal infectious diseases – particularly across Sub-Saharan Africa, where the disease has had a massive impact on health outcomes and life expectancy in recent decades.

The Global Burden of Disease is a major global study on the causes of death and disease published in the medical journal The Lancet.1 These estimates of the annual number of deaths by cause are shown here. This chart shows the global total but can be explored for any country or region using the "Change country" button.

Since the People Living with HIV Stigma Index was launched in 2008, shifts in the HIV epidemic, growth in the evidence base on how different populations are affected by stigma, and changes in the global response to HIV — particularly given the recommendation of early initiation of treatment — have highlighted the need to update and strengthen the Stigma Index as a measurement and advocacy tool. In October 2015, with support from USAID/PEPFAR, Project SOAR established a small working group (SWG) with representatives from the Global Network of People Living with HIV (GNP+), the International Community of Women Living with HIV (ICW), the Joint United Nations Programme on HIV/AIDS (UNAIDS), USAID, and several experts within and external to SOAR. The SWG outlined a process for evaluating and updating the Stigma Index that would be transparent and incorporate as many perspectives as possible in the process. The updated draft survey was then formally pilot-tested before being finalized and disseminated in late 2017.

Description: This data set contains the responses from a purposive sample of 10 473 respondents who were all living with HIV and who were older than 15 years linked to either an organisation for PLHIV or attending health facilities and NGOs for the purposes of accessing support or care related to HIV and AIDS, with the purpose to measure self-reported stigma and discrimination experienced by PLHIV nationally. The data set for dissemination contains 377 variables and 10 473 cases which represented 100% response rate. Abstract: The People Living with HIV (PLHIV) Stigma Index is a joint initiative of several organizations who have worked together since 2005 to develop this survey. These include the Global Network of People Living with HIV/AIDS (GNP+),the International Community of Women Living with HIV/AIDS (ICW),the International Planned Parenthood Federation (IPPF) and UNAIDS. To date, nearly 50 countries from all parts of the world have undertaken national surveys using the People Living with HIV Stigma Index (see The People Living with HIV Stigma Index, 2012). Three NGOs belonging to the South African National AIDS Council (SANAC) PLHIV sector, namely, the National Association of People Living with HIV and AIDS (NAPWA), the Treatment Action Campaign (TAC), and the Positive Women's Network, together with the Human Sciences Research Council (HSRC); and the Joint United Nations Programme on HIV/AIDS (UNAIDS), and the SANAC Secretariat undertook this, the first National Stigma Index among PLHIV in 18 districts across South Africa (two per province) over 13 weeks (starting from the 2nd week of September 2014 until the 2nd week of December 2014). The purpose of the PLHIV Stigma Index survey was to measure self-reported stigma and discrimination experienced by PLHIV nationally and ultimately to also inform the development and implementation of national policies and programmes that protect the rights of PLHIV. The process involved PLHIV interviewing other PLHIV regarding experiences of stigma and discrimination. This process is not only an integral part of the Stigma Index but also meant to be an empowering one for PLHIV. TB-related stigma was also investigated in this study. The study reported that significant minorities of PLHIV have experienced physical violence, exclusion from family activities, denial of health care, or lost their jobs or income because of their HIV status. In addition, PLHIV also have internalised HIV and AIDS stigma with many of them reporting that they feel ashamed of being HIV-positive. Various recommendations were made in terms of interventions to reduce some of the stigma and discrimination found among PLHIV in South Africa. These recommendations focused on the Intra-personal, Inter-personal and social level. In addition recommendations were directed at both structural and sector-based interventions. Face-to-face interview The study used purposive sampling to involve PLHIV aged 15 years and older. All respondents were linked to an organisation for PLHIV or attending health facilities and NGOs for the purpose of accessing support or care related to HIV. The study used purposive sampling to involve PLHIV aged 15 years and older. All respondents were linked to an organisation for PLHIV or attending health facilities and NGOs for the purpose of accessing support or care related to HIV. A sample of 10 473 respondents, all of whom self-reported a HIV-positive status was achieved.

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:

UNAIDS Key Population Atlas

US Centers for Disease Control and Prevention surveillance database

Global Fund against HIV/AIDS, TB, and Malaria surveillance database

Global.HIV database

Systematic review databases among MSM (Stannah et al, 2019 and Stannah et al., 2023) and PWID (Degenhardt et al., 2023)

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

The data can be explored in this web application and the accompanying manuscript can be found here

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).

Every year, UNAIDS releases updated estimates of the number of people living with HIV and AIDS and the mortality impact of the epidemic, while WHO releases data on the number of people on treatment and the number needing treatment. This dataset, from CGD senior fellow Mead Over and Owen McCarthy, is a compilation of selected variables from these published sources as well as from the World Bank Development Indicators and the International Monetary Fund’s estimates of economic quantities such as Gross Domestic Product and central government health expenditures. The data are in the format developed by the Stata statistical software corporation and are intended for use with the AIDSCost package for the purpose of projecting the future budgetary cost of scaling up AIDS treatment. Instructions on how to download, access, and use the AIDSCost package are included in the users' manual. The authors encourage comments on their blog or as an e-mail to them, which will be considered for posting. (CGD’s HIV/AIDS Monitor Initiative provides access to data on past AIDS funding PEPFAR, the World Bank and the Global Fund.)

Description: This data set contains responses from individuals who are 12 to 14 years old who self-reported on the indicators related to HIV/AIDS behaviour and testing. The respondents' biographical data, school attendance, questions on media, communication and norms, knowledge and perceptions of HIV and AIDS, home environment, care and protection at school, sexual debut, attitudes and knowledge towards sexual roles, health questions, male circumcision, crime and social norms were included. The data set contains 227 variables and 2273 cases. Refer to the user guide for information regarding guidance relating to data analysis. Subsequent to the dissemination of version 1 of the Child 12-14 data set the skip patterns for the Child data set was corrected, Version 2 of the data set is disseminated as: Human Sciences Research Council. South African National HIV Prevalence, HIV Incidence, Behaviour and Communication Survey (SABSSM) 2012: Child 12-14 years - All provinces. [Data set]. SABSSM 2012 Child 12-14. Version 2.0. Pretoria South Africa: Human Sciences Research Council [producer] 2012, Human Sciences Research Council [distributor] 2016. http://dx.doi.org/doi:10.14749/1518167762. Abstract: 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 fourth 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 2008 survey, making it the fourth national-level repeat survey. The 2002 and 2005 surveys included individuals aged 2+ years living in South Africa while 2008 and 2012 survey included individuals of all ages living in South Africa, including infants less than 2 years of age. The 2008 study included only four people per household, while in 2012 all members of the households participated. 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 surveys provide the nationally representative HIV incidence estimates showing changes over time. The 2012 study key objectives were: to determine the proportion of PLHIV who are on Antiretroviral treatment (ART) in South Africa; to determine the prevalence and incidence of HIV infection in South Africa in relation to social and behavioural determinants; to determine the proportion of males in South Africa who are circumcised; to investigate the link between social values, and cultural determinants and HIV infection in South Africa; to determine the extent to which mother-child pairs include HIV-negative mothers and HIV-positive infants; to describe trends in HIV prevalence, HIV incidence, and risk behaviour in South Africa over the period 2002 to 2012 collect data on the health conditions of South Africans; and contribute to the analysis of the impact of HIV/AIDS on society. In 2012, of the 15000 selected households or visiting points, 11079 agreed to participate in the survey, 42950 individuals (all household members were included) were eligible to be interviewed, and 38431 individuals completed the interview. Of the 38431 eligible individuals, 28997 agreed to provide a blood specimen for HIV testing and were anonymously linked to the behavioural questionnaires. The household response rate was 87.2% , the individual response rate was 89.5% and the overall response rate for HIV testing was 67.5% Clinical measurements Face-to-face interview Focus group Observation South African population. This project used the updated 2007-2011 HSRC's master sample. Aerial photographs drawn from Google Earth were utilised to ensure that the most up-to-date information was available sample. the master sample is defined as a selection, for the purpose of repeated community or household surveys, of a probability sample of census enumeration areas throughout South Africa that are representative of the country's provincial, settlement and racial diversity. The sampling frame that was used in the design of the Master Sample was the 2001 census Enumerator Areas (EAs) from Statistics South Africa (Stats SA). The target population for this study were all people in South Africa, excluding persons in so-called special institutions (e.g. hospitals, military camps, old age homes, schools and university hostels). The EAs were used as the Primary Sampling Units (PSUs) and the Secondary Sampling Units (SSUs) were the visiting points (VPs) or households (HHs). The Ultimate Sampling Units (USUs) were the individuals eligible to be selected for the survey. Any member of the household "who slept here last night", including visitors was an eligible household member for the interview. This sampling approach was used in the 2001 census and is a standard demographic household survey procedure. The sample was designed with two main explicit strata, the provinces and the geography types (geotype) of the EA. In the 2001 census, the four geotypes were urban formal, urban informal, rural formal (including commercial farms) and tribal areas (rural informal) (i.e. the deep rural areas). In the formal urban areas, race was used as a third stratification variable. What this means is that 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 invited to participate in the study. 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 2012 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 38 431 interviewed participants composed of 29.7% children (0-14 years), 19.3% youths (15-24 years), 35.6% adults (25-49 years), and 15.4% adults (50+ 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 (70.3%) than males (64.2%) were tested for HIV. The 15-24 year's age group was the most compliant (71.6%), and less than 2 years the least (51.6%). The highest testing response rate was found in rural formal settlements (80.8%) and the least in urban formal areas (59.7%).

Global Network of People Living with HIV (GNP+) Activity File

Malawi MW: Antiretroviral Therapy Coverage: % of People Living with HIV data was reported at 71.000 % in 2017. This records an increase from the previous number of 66.000 % for 2016. Malawi MW: Antiretroviral Therapy Coverage: % of People Living with HIV data is updated yearly, averaging 20.500 % from Dec 2000 (Median) to 2017, with 18 observations. The data reached an all-time high of 71.000 % in 2017 and a record low of 0.000 % in 2003. Malawi MW: Antiretroviral Therapy Coverage: % of People Living with HIV data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Malawi – Table MW.World Bank.WDI: Health Statistics. Antiretroviral therapy coverage indicates the percentage of all people living with HIV who are receiving antiretroviral therapy.; ; UNAIDS estimates.; Weighted average;

Nigeria NG: Antiretroviral Therapy Coverage: % of People Living with HIV data was reported at 33.000 % in 2017. This records an increase from the previous number of 31.000 % for 2016. Nigeria NG: Antiretroviral Therapy Coverage: % of People Living with HIV data is updated yearly, averaging 9.000 % from Dec 2000 (Median) to 2017, with 18 observations. The data reached an all-time high of 33.000 % in 2017 and a record low of 0.000 % in 2002. Nigeria NG: Antiretroviral Therapy Coverage: % of People Living with HIV data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Nigeria – Table NG.World Bank.WDI: Health Statistics. Antiretroviral therapy coverage indicates the percentage of all people living with HIV who are receiving antiretroviral therapy.; ; UNAIDS estimates.; Weighted average;

Djibouti DJ: Antiretroviral Therapy Coverage: % of People Living with HIV data was reported at 27.000 % in 2017. This records an increase from the previous number of 24.000 % for 2016. Djibouti DJ: Antiretroviral Therapy Coverage: % of People Living with HIV data is updated yearly, averaging 8.500 % from Dec 2000 (Median) to 2017, with 18 observations. The data reached an all-time high of 27.000 % in 2017 and a record low of 0.000 % in 2002. Djibouti DJ: Antiretroviral Therapy Coverage: % of People Living with HIV data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Djibouti – Table DJ.World Bank.WDI: Health Statistics. Antiretroviral therapy coverage indicates the percentage of all people living with HIV who are receiving antiretroviral therapy.; ; UNAIDS estimates.; Weighted average;

Death rate of a population adjusted to a standard age distribution. As most causes of death vary significantly with people's age and sex, the use of standardised death rates improves comparability over time and between countries, as they aim at measuring death rates independently of different age structures of populations. The standardised death rates used here are calculated on the basis of a standard European population (defined by the World Health Organization). Detailed data for 65 causes of death are available in the database (under the heading 'Data').

Mali ML: Antiretroviral Therapy Coverage: % of People Living with HIV data was reported at 32.000 % in 2017. This records an increase from the previous number of 29.000 % for 2016. Mali ML: Antiretroviral Therapy Coverage: % of People Living with HIV data is updated yearly, averaging 17.500 % from Dec 2000 (Median) to 2017, with 18 observations. The data reached an all-time high of 32.000 % in 2017 and a record low of 0.000 % in 2002. Mali ML: Antiretroviral Therapy Coverage: % of People Living with HIV data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mali – Table ML.World Bank.WDI: Health Statistics. Antiretroviral therapy coverage indicates the percentage of all people living with HIV who are receiving antiretroviral therapy.; ; UNAIDS estimates.; Weighted average;

Description: The SABSSM 2005 (SABSSM II) survey had four questionnaires (Visiting point, 2 to 11 years old, 12 to 14 year old and 15+ years olds). In the combined data set, three individual data sets were combined together: the guardian data (2 to 11 years old), the child data (12 to 14 year old) and youth and adult (15+ years old). In combining these data sets, only questions that were common to all the data sets were combined together to create a composite data file that could be used to analyze data. The data file included demographic variables, HIV test results and sexual behavioural variables for those aged 15 years and above. The data set contains 31 variables and 23275 cases. Abstract: 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 second in a series of household surveys conducted by the Human Sciences Research Council (HSRC), that allow for tracking of HIV and associated determinants over time using the same methodology used in the 2002 survey, thus making it the first national-level repeat survey. The interval of three years 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 HIV prevalence and incidence as well as viral load in the population; Gather data to inform modelling of the epidemic; Identify risky behaviours that predispose the South African population to HIV infection; examine social, behavioural and cultural determinants of HIV; explore the reach of HIV/AIDS communication and the relationship of communication to response; assess the relationship between mental health and HIV/AIDS and establish a baseline; assess public perceptions of South Africans with respect to the provision of anti-retroviral (ARV) therapy for prevention of mother-to-child transmission and for treating people living with HIV/AIDS; understand public perceptions regarding aspects of HIV vaccines; and investigate the extent of the use of hormonal contraception and its relationship to HIV infection. In the 10 584 valid visiting points that agreed to participate in the survey, 24 236 individuals were eligible for interviews and 23 275 completed the interview. Of the 24 236 individuals, 15 851 agreed to HIV testing and were anonymously linked to the behavioural interviews. The household response rate was 84.1 % and the overall response rate for HIV testing was 55 %. Clinical measurements Face-to-face interview Focus group Observation South African population, 2 years and older from urban formal, urban informal, rural formal (farms), rural informal (tribal area) settlements. This project used the HSRC's master sample (HSRC 2002). A master sample is defined as a selection, for the purpose of repeated community or household surveys, of a probability sample of census enumeration areas throughout South Africa that are representative of the country's provincial, settlement and racial diversity. The sampling frame that was used in the design of the Master Sample was the 2001 census Enumerator Areas (EAs) from Statistics South Africa (Stats SA). The target population for this study were all people in South Africa, excluding persons in so called 'special institutions' (e.g. hospitals, military camps, old age homes, schools and university hostels). The EAs were used as the Primary Sampling Units (PSUs) and the Secondary Sampling Units (SSUs) were the visiting points (VPs) or households (HHs). The Ultimate Sampling Units (USUs) were the individuals eligible to be selected for the survey. Any member of the household 'who slept here last night', including visitors was an eligible household member for the interview. This sampling approach was used in the 2001 census and is a standard demographic household survey procedure. The sample was designed with two main explicit strata, the provinces and the geography types (geotype) of the EA. In the 2001 census, the four geotypes were urban formal, urban informal, rural formal (including commercial farms) and tribal areas (rural informal) (i.e. the deep rural areas). In the formal urban areas, race was used as a third stratification variable. What this means is that 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 proceeded with the interview. All people in the households, resident at the visiting point aged 2 years and older were initially listed, after which the eligible individual was randomly selected in each of the following three age groups 2-11, 12-14 and 15 years and older. 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 2-11 years, parents/guardians were interviewed but DBS specimens were obtained from the children. The sample size estimate for the 2005 survey was guided by (1) the requirement for measuring change over time and to be able to detect a change in HIV prevalence of 5 % points in each of the main reporting domains, and (2) the requirement of an acceptable precision of estimates per reporting domain, say a precision less than ±4% with a design effect of 2 units. Overall, a total of 23 275 participants composed of 6 866 children (2-14 years), 5 708 youths (15-24 years) and 10 687 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 (68.3%) than males (62.2%) were tested for HIV. The 25+ years age group was the most compliant (71.3%), and 2-14 years the least (54.6%). The highest response rates were found in rural formal locality types (74.5%) and the lowest in urban formal locality types (61.7%).

Georgia GE: Antiretroviral Therapy Coverage: % of People Living with HIV data was reported at 39.000 % in 2017. This records an increase from the previous number of 36.000 % for 2016. Georgia GE: Antiretroviral Therapy Coverage: % of People Living with HIV data is updated yearly, averaging 11.500 % from Dec 2000 (Median) to 2017, with 18 observations. The data reached an all-time high of 39.000 % in 2017 and a record low of 0.000 % in 2003. Georgia GE: Antiretroviral Therapy Coverage: % of People Living with HIV data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Georgia – Table GE.World Bank.WDI: Health Statistics. Antiretroviral therapy coverage indicates the percentage of all people living with HIV who are receiving antiretroviral therapy.; ; UNAIDS estimates.; Weighted average;

Jordan JO: Antiretroviral Therapy Coverage: % of People Living with HIV data was reported at 55.000 % in 2016. This records an increase from the previous number of 50.000 % for 2015. Jordan JO: Antiretroviral Therapy Coverage: % of People Living with HIV data is updated yearly, averaging 37.000 % from Dec 2000 (Median) to 2016, with 17 observations. The data reached an all-time high of 55.000 % in 2016 and a record low of 0.000 % in 2003. Jordan JO: Antiretroviral Therapy Coverage: % of People Living with HIV data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Jordan – Table JO.World Bank.WDI: Health Statistics. Antiretroviral therapy coverage indicates the percentage of all people living with HIV who are receiving antiretroviral therapy.; ; UNAIDS estimates.; Weighted average;

Users can access data related to international women’s health as well as data on population and families, education, work, power and decision making, violence against women, poverty, and environment. Background World’s Women Reports are prepared by the Statistics Division of the United Nations Department for Economic and Social Affairs (UNDESA). Reports are produced in five year intervals and began in 1990. A major theme of the reports is comparing women’s situation globally to that of men in a variety of fields. Health data is available related to life expectancy, cause of death, chronic disease, HIV/AIDS, prenatal care, maternal morbidity, reproductive health, contraceptive use, induced abortion, mortality of children under 5, and immunization. User functionality Users can download full text or specific chapter versions of the reports in color and black and white. A limited number of graphs are available for download directly from the website. Topics include obesity and underweight children. Data Notes The report and data tables are available for download in PDF format. The next report is scheduled to be released in 2015. The most recent report was released in 2010.

In 2021, 1.9 million people in Nigeria were living with HIV. Women were the most affected group, counting 1.1 thousand individuals. Also, children up to age 14 who were HIV positive equaled 170 thousand.

The 2007-2008 Tanzania HIV/AIDS and Malaria Indicator Survey is the eight national survey to be carried out as part of the Demographic and Health Surveys project in Tanzania. It is the second comprehensive survey on HIV/AIDS carried out in Tanzania. The results of the 2007-08 Tanzania HIV?AIDS Malaria Indicators Survey are intended to provide information to assist policymakers and Programme implementer's to monitor and evaluate existing Programmes and to design new strategies for combating the HIV/AIDS epidemic in Tanzania. The survey data will also be used as inputs in population projections and to calculate indicators developed by the United Nations General Assembly Special Session (UNGASS), the UNAIDS Programme, and the World Health Organization (WHO).