As of 2024, South Africa was the country with the highest number of people living with HIV in Africa. At that time, around 7.8 million people in South Africa were HIV positive. In Mozambique, the country with the second-highest number of HIV-positive people in Africa, around 2.5 million people were living with HIV. Which country in Africa has the highest prevalence of HIV? Although South Africa has the highest total number of people living with HIV in Africa, it does not have the highest prevalence of HIV on the continent. Eswatini currently has the highest prevalence of HIV in Africa and worldwide, with almost 26 percent of the population living with HIV. South Africa has the third-highest prevalence, with around 18 percent of the population HIV positive. Eswatini also has the highest rate of new HIV infections per 1,000 population worldwide, followed by South Africa and Mozambique. However, South Africa had the highest total number of new HIV infections in 2024, with around 170,000 people newly infected with HIV that year. Deaths from HIV in Africa Thanks to advances in treatment and awareness, HIV/AIDS no longer contributes to a significant amount of death in many countries. However, the disease is still the eighth leading cause of death in Africa, accounting for around 4.6 percent of all deaths. In 2024, South Africa and Mozambique were the countries with the highest number of AIDS-related deaths worldwide, with 53,000 and 44,000 such deaths, respectively. Although not every country in the leading 25 for AIDS-related deaths is found in Africa, African countries account for the majority of countries on the list. Fortunately, HIV treatment has become more accessible in Africa over the years, and now up to 94 percent of people living with HIV in Eswatini are receiving antiretroviral therapy (ART). Access to ART does vary from country to country, however, with around 81 percent of people who are HIV positive in South Africa receiving ART and only 34 percent in the Congo.

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

In 2022, approximately *** million people were living with HIV in India. However, there has been a constant decrease in the number of people living with HIV (PLHIV) since 2003, and from 2008 onward, there have been less than ***** million PLHIV yearly.

HIV risk-groups

India’s HIV epidemic is the third-largest in the world. However, this is primarily concentrated among key populations who are at a higher risk of contracting the disease. One of the main drivers of this is unprotected sex among female sex workers and their clients, partners, and spouses. Injecting drugs are also becoming one of the common ways through which HIV can be transmitted due to the reuse of needles. In addition, the prevalence of HIV is higher among men than women. This can be attributed to the increase in the share of men who have sex with men, migrant workers, and drug use injections.

Sex-workers

While prostitution is considered legal in India, all activities associated with running brothels or sex trafficking are prohibited. As a result, there is severe police activity targeting sex workers, with routine raids in areas with brothels justified by related laws. A recent study in Andhra Pradesh suggested a positive correlation between police abuse and an increased risk of HIV along with inconsistency in the usage of condoms. It is not uncommon that stigma and discrimination against sex-workers limit their access to decent healthcare in India.

Statistics relating to HIV infection

Dataset refers to the Statistics Relating to Notification of HIV Aids Cases and Deaths in Mauritius for the year 2000 to 2023

In 2024, some *** percent of the total global adult population aged between 15 and 49 years was infected with HIV. This statistic reflects the HIV prevalence among the global adult population from 1990 to 2024.

In 2024, South Africa and Mozambique had the highest number of deaths due to AIDS worldwide, with around ** thousand and ** thousand such deaths, respectively. African countries account for eight of the top 10 countries with the highest number of AIDS-related deaths worldwide. AIDS-related deaths worldwide have been gradually declining over the past decade, decreasing from *** million deaths in 2010 to *** thousand deaths in 2024. HIV/AIDS HIV (human immunodeficiency virus) is an infectious sexually transmitted disease that is transmitted via exposure to infected semen, blood, vaginal and anal fluids and breast milk. HIV weakens the human immune system, resulting in the affected person being unable to fight off opportunistic infections. The top 15 countries worldwide with the highest prevalence of new HIV infections as of 2024 were all African. HIV treatment Although there is currently no effective cure for HIV, death can be prevented by taking HIV antiretroviral therapy (ART). Access to antiretroviral therapy worldwide has significantly increased in the past decade. As of 2024, around **** million people with HIV worldwide were receiving ART. The countries with the highest percentage of HIV-infected children who were receiving ART were Eswatini, Kenya, and Lesotho.

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).

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

BackgroundAcquired ImmunoDeficiency Syndrome (AIDS) related illnesses are the leading cause of death in the developing world. However; there is limited evidence regarding the incidence of mortality among admitted HIV patients in Ethiopia.ObjectiveTo determine the incidence of mortality and its predictors among admitted HIV/AIDS patients in selected tertiary care hospitals in Ethiopia.MethodsA prospective cohort study involving 136 admitted HIV/AIDS patients from April 1 to August 31, 2018 was conducted in selected tertiary care hospitals in Ethiopia. Data were collected on socio-demographic, clinical characteristics, and drug related variables. Kaplan-Meier and Cox regression were used to compare survival experience of the patients and identify independent predictors of mortality. Hazard ratio was used as a measure of strength of association and p-value of

1The group frequencies may not sum to total due to missing values.2P-values are from Chi-square test for categorical variables and non-parametric test for continuous variables.

Background By 1990, 94 percent of the acquired immunodeficiency syndrome (AIDS) cases in Romania were in children less than 13 years of age. The majority of the cases were identified in the city of Constanta. The purpose of this paper was to describe the current burden of pediatric human immunodeficiency virus (HIV) infection in the Constanta county. Methods A cross-sectional study was designed to address the primary objective. Between April 1999 and March 2000, all living cases of pediatric HIV infection in the Constanta county were identified from records at the HIV hospital clinic which serves the Constanta county. Standard demographic, social, clinical, treatment and hospitalization data were collected for each study subject. Data were analyzed according to cross-sectional study design methodology. Results Of the 762 subjects, the majority were seven to 11 years of age, lived with their parents and attended school. Only 70% of the fathers and 13% of the mothers were employed. Horizontal transmission accounted for 90% of the cases. Most of the children had moderate to severe disease as indicated by their AIDS-defining signs; 40% had AIDS. Less than half of the children were receiving antiretroviral therapy (ART). ART and children of mothers with a high school or greater education were independent predictors of long-term non-progression of HIV disease. Conclusions This cross-sectional study demonstrated that ten years after the HIV epidemic was identified in Romania, it remains a health and economic burden. The infected children are very ill, but ART is not available for all. The proportion with vertical transmission has increased from an estimated four % to nine %. Our findings support the need to get HIV therapy to economically challenged countries such as Romania.

Additional file 4. PLHIV estimates using the ECDC HIV modelling tool, Spectrum AIDS Impact Model (with CSAVR incidence) and Spectrum AIDS Impact Model (with ECDC modelling tool incidence).

Based on 2014 Kenya's HIV/AIDS profile data by County This assesses the HIV/AIDS situation in Kenya's 47 counties with regards to adults and children living with the disease, new infections, gender specific infection rates, homes with orphans and their financial situation.

Ratio: Percent of cases simultaneously diagnosed with HIV and AIDS.

Definition: Number of cases simultaneously diagnosed with HIV and AIDS among all of those diagnosed with HIV / AIDS.

Data Source: Division of HIV/AIDS, STD, and TB Services, New Jersey Department of Health

Geographic coverage

The survey was conducted in two local communities in the Free State province, one urban (Welkom) and one rural (Qwaqwa), in which the HIV/AIDS epidemic is particularly rife. Welkom and Qwaqwa are situated in the Lejweleputswa and Thabo Mofutsanyane districts of the Free State province.

Analysis unit

Households

Universe

All memebers of the Household

Kind of data

Sample survey data [ssd]

Sampling procedure

The household impact of HIV/AIDS was assessed by means of a cohort study of households affected by the disease. The survey was conducted in two local communities in the Free State province, one urban (Welkom) and one rural (Qwaqwa), in which the HIV/AIDS epidemic is particularly rife. Welkom and Qwaqwa are situated in the Lejweleputswa and Thabo Mofutsanyane districts of the Free State province.

Affected households were sampled purposively via NGOs and other organizations involved in AIDS counselling and care and at baseline included at least one person known to be HIV-positive or known to have died from AIDS in the past six months. Informed consent was obtained from the infected individual(s) or their caregivers (in the case of minors). In order to explore the socio-economic impact on affected households of repeated occurrences of HIV/AIDS-related morbidity or mortality, a distinction is made between affected households in general and affected households that have experienced morbidity or mortality more frequently. Non-affected households represent households living in close proximity to affected households. These households at baseline did not include persons suffering from tuberculosis or pneumonia. The incidence of morbidity and mortality is considerably higher in affected households.

Affected households were sampled purposively via NGOs and other organizations involved in AIDS counselling and care and at baseline included at least one person known to be HIV-positive or known to have died from AIDS in the past six months. Informed consent was obtained from the infected individual(s) or their caregivers (in the case of minors). In order to explore the socio-economic impact on affected households of repeated occurrences of HIV/AIDS-related morbidity or mortality, a distinction is made between affected households in general and affected households that have experienced morbidity or mortality more frequently. Non-affected households represent households living in close proximity to affected households. These households at baseline did not include persons suffering from tuberculosis or pneumonia. The incidence of morbidity and mortality is considerably higher in affected households.

Mode of data collection

Face-to-face [f2f]

Research instrument

Household Questionnaire

Response rate

During the first wave of interviews a total of 404 interviews were conducted. During the second wave of data collection, interviews were conducted with 385 households, which translates into an attrition rate of 4.7% (19 households). During wave III, a total of 354 households were interviewed, with 31 households not being reinterviewed (7.7% of the original sample). In wave IV, 55 new households wererecruited into the study, with particular emphasis on an effort to recruit child-headed households into the survey insofar as the sample to date did not include any such households. During waves IV, V and VI a total of 3, 13 and 9 households respectively could not be re-interviewed.

The payment of a minimal participation fee (R150 per household per survey visit) to those households interviewed in each wave, following the interview and distributed in the form of food parcels, contributed to ensuring sustainability of the sample over the three-year period. The dataset includes data for 331 households interviewed in each of the six rounds of interviews. In almost 90 percent of cases the reasons for attrition are related to migration, given that this study did not intend to follow those households that move outside of the two immediate study areas, i.e. Welkom and Qwaqwa. In the majority of cases, attrition can be ascribed to the failure to establish the current whereabouts of the particular household during follow-up, while in a third of cases it could be established that the household had moved to another country, another province, or another town in the Free State province. Less than ten percent of households had refused to participate in subsequent waves. The reasons for attrition in the original sample illustrate the manner in which migration and the disintegration of households, which are important effects of the epidemic, can act to erode the sample population.

This data set contains EIIHA populations who received services funded by Ryan White Part A Grant. EIIHA is Early Identification of Individuals with HIV/AIDS (EIIHA) The special populations (EIIHA) with HIV are: Black MSM = Black men and Black transgender women who have sex with men. Latinx MSM = Latinx men and Latinx Transgender women who have sex with men. Black Women - Black women Transgender - Transgender men and women. These populations have the biggest disparities of people living with HIV. Other data is the number of clients and units used in each service category in the Ryan White Part A, a grant that provides services for those with HIV.

The North Carolina Screening and Tracing of Active Transmission Program. The STAT cases are inclusive of CHAVI-001 cases.* Center for HIV/AIDS Vaccine Immunology 001 Study: Acute HIV Infection Prospective Cohort Study.^ 932 partners were named by Index AHI cases during the STAT investigation. Index AHI cases refused to provide detailed demographic information for the STAT Program for a total of 276 partners, leaving 656 with detailed demographic information.@ One partner identified in CHAVI-001 was missing gender.# Missing Race not included in table.Demographics of Index AHI and Named Partners.

Description: The data set contains the data of the parents or guardians of children aged 0 to 11 years. Some of the questions included were the child's biographical data, health status and health questions, male circumcision, education of the child on life issues, infant and child feeding practices as well as school attendance and immunisation records. The data set contains 275 variables and 9667 cases. Refer to the user guide for information regarding guidance relating to data analysis. 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% From the total of 38431 (89.5%) individuals who completed the interview, 2295 (5.3%) refused to be interviewed, 2224(5.2%) were absent from the household and 2224 (5.2%) were classified as missing/other. 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%).

Description: This data set contains information on adults aged 25 years and older: 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 516 variables and 10501 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 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%.