This data set includes tables on persons living with HIV/AIDS, newly diagnosed HIV cases and all cause deaths in HIV/AIDS cases by gender, age, race/ethnicity and transmission category. In all tables, cases are reported as of December 31 of the given year, as reported by January 9, 2019, to allow a minimum of 12 months reporting delay. Gender is determined by both current gender and sex at birth variables; transgender values are assigned when current gender is identified as "Transgender" or when a discrepancy is identified between a person's sex at birth and their current gender (e.g., cases where sex at birth is "Male" and current gender is "Female" will become Transgender: Male to Female.) Prior to 2003, Asian and Native Hawaiian/Pacific Islanders were classified as one combined group. In order to present these race/ethnicities separately, living cases recorded under this combined classification were split and redistributed according to their expected proportional population representation estimated from post-2003 data.

In 2022, among first-time HIV cases in Canada where race and/or ethnicity was reported, the highest share among males was among white individuals, at 34.6 percent. Among females, the highest share was reported by Indigenous females, at 41.7 percent. This statistic shows the distribution of first-time HIV diagnoses in 2022 in Canada, by race and/or ethnicity reported and gender.

As of 2023, only around six percent of male and eight percent of female high school students in the United States reported ever being tested for HIV. This graph presents the percentage of high school students in the United States who were ever tested for HIV as of 2023, by gender and race/ethnicity.

Descriptive statistics Descriptive statistics for the dependent and independent variables of this study were presented in Table 1. Out of 3314 undergraduate students in the sample, 2583 (77.9%) expressed their willingness to accept a free HIV test. More than two thirds (66.9%) of these subjects were females and the majority of respondents (94.5%) were Han. Of college students in this sample, nearly two fifths (37.4%) lived in the local city less than one year and about one third (31.0%) were freshmen. Nearly one half (48.2%) of our participants were medical students. To our surprise, 15.2% reported their sexual orientation is non-heterosexual and 55.9% spent less than one thousand Yuan on their monthly living expenses. HIV/AIDS-related knowledge was lacking with only 39.1% of participants answering more than 10 out of twelve questions correctly. Furthermore, stigma and discrimination towards people living with HIV/AIDS were serious, since the number of correct responses that nearly half (45.5%) of the respondents responded to the 24 specific situations was no more than eighteen. The majority of college students mentioned at least one free HIV testing site and also recognized the necessity to provide a free HIV test in the local university (78.8% and 88.7%, respectively). Beyond our expectation, more than half (56.2%) of college students were ignorant of the "Four Frees and One Care" policy. Despite the fact that 18.9% of college students reported having had sexual behavior, only 49.5% perceived the risk of HIV infection. Bivariable analysis The results of the bivariable analysis were shown in Table 1. Those who expressed greater willingness to accept a free HIV test tended to be medical students, higher levels of HIV-related knowledge, lower levels of stigma and discrimination, awareness of the "Four Frees and One Care" policy, knowledge of free HIV testing centers, recognition of the necessity to provide a free HIV test in the local university, and higher perception of the risk of HIV infection. No significant differences were reported between willingness and unwillingness in gender, race, grade, length of time, sexual orientation, monthly living expense, and history of sexual behavior. Multivariable logistic regression analysis The stepwise multiple logistic regression model predicting willingness to accept a free HIV test was shown in Table 2. When all seven significant variables were included into the logistic regression model, only four variables (i.e., stigma and discrimination towards people living with HIV/AIDS, knowledge of free HIV testing centers, recognition of the necessity to provide a free HIV test in the local university, perceived risk of HIV infection) remained statistically significantly related to willingness to participate in a free HIV test, while three variables including major, HIV-related knowledge, and awareness of the “Four Frees and One Care” policy lost their statistical significance, as indicated in Table 2. Among all these four significant predictors, the odds ratio(OR) was the highest for recognition of the necessity to provide a free HIV test in the local university. The college students having recognized the necessity were more likely to express their willingness to accept to a free HIV test (OR=2.20, 95CI=1.73--2.80, P<0.001) than those having not recognized the necessity. The odds of willingness were 1.41 times (95CI=1.17--1.68, P<0.001) of respondents who had lower levels of stigma and discrimination towards people living with HIV/AIDS, compared to that of those with high levels of stigma and discrimination. In addition, being more knowledgeable about free HIV testing centers (OR = 1.44, 95%CI=1.17--1.77, P<0.001) and having higher HIV risk perception (OR =1.64, 95%CI=1.37--1.95, P<0.001) were significantly associated with greater willingness to use VCT service.

The states with the highest rates of HIV diagnoses in 2021 included Georgia, Louisiana, and Florida. However, the states with the highest number of people with HIV were California, Texas, and Florida. In California, there were around 4,399 people diagnosed with HIV. HIV/AIDS diagnoses The number of diagnoses of HIV/AIDS in the United States has continued to decrease in recent years. In 2021, there were an estimated 35,769 HIV diagnoses in the U.S. down from 38,433 diagnoses in the year 2017. In total, since the beginning of the epidemic in 1981 there have been around 1.25 million diagnoses in the United States. Deaths from HIV Similarly, the death rate from HIV has also decreased significantly over the past few decades. In 2019, there were only 1.4 deaths from HIV per 100,000 population, the lowest rate since the epidemic began. However, the death rate varies greatly depending on race or ethnicity, with the death rate from HIV for African Americans reaching 19.1 per 100,000 population in 2020.

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 3...

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 3...

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.

Notes: Statistical significance for categorical variables was determined using chi-squared or Fisher’s exact tests and continuous variables assessed using Kruskal-Wallis or Student’s t-tests. Variables with missing data were calculated on available data. Variables in bold indicate that the comparison was statistical significant.

This statistic shows the estimated number of homeless people with HIV/AIDS in the United States in 2022, by sheltered status. In that year, there were an estimated 2,075 homeless people with HIV/AIDS living in transitional housing in the U.S.

Demographics, comorbidities and laboratory parameters, stratified by CKD.

Background: The once-daily, single-tablet regimen darunavir/cobicistat/emtricitabine/tenofovir alafenamide (D/C/F/TAF) 800/150/200/10 mg is approved for the treatment of HIV-1 infection. The 48-week efficacy and safety of D/C/F/TAF versus darunavir/cobicistat + emtricitabine/tenofovir disoproxil fumarate (control) in treatment-naïve adults were demonstrated in the phase 3 AMBER study. Objective: To describe AMBER outcomes across patient subgroups based on demographic and clinical characteristics at baseline. Methods: AMBER patients had viral load (VL) ≥1000 copies/mL, CD4+ cell count >50 cells/µL, and genotypic susceptibility to darunavir, emtricitabine, and tenofovir. Primary endpoint was the proportion of patients with virologic response (VL 50 years), gender, race (black/non-black), baseline VL (≤/>100,000 copies/mL), baseline CD4+ cell count ( Results: For the 725 AMBER patients (D/C/F/TAF: 362; control: 363), virologic response rates at week 48 were similar with D/C/F/TAF (91%) and control (88%), and this was consistent across all subgroups. Adverse event rates were similar in both arms, although numerically higher among patients >50 years and women, relative to their comparator groups, regardless of treatment arm (notably, sample sizes were small for patients >50 years and women). Improvements in eGFRcystC and stable bone mineral density were observed with D/C/F/TAF overall, and results were generally consistent across subgroups. Conclusions: For treatment-naïve patients in AMBER, initiating therapy with the D/C/F/TAF single-tablet regimen was an effective and well-tolerated option, regardless of demographic or clinical characteristics. Trial registration:ClinicalTrials.gov identifier: NCT02431247.

Description: In the combined data set four individual data sets were combined, guardians for children to 11 years, children 12 to 14 years, youths and adults 15 years and older and individual's information from the visiting point data set. 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 917 variables and 44029 cases. Subsequent to the dissemination of version 1 of the Combined data set the skip patterns for the Adult and Child data sets were corrected and updated in the Combined data set which is disseminated as Version 2.

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%

In 2024, around 13 percent of the total deaths in South Africa were acquired immunodeficiency virus (AIDS) related. This represented a slight decrease of 0.1 percentage points compared to 2023. Since 2002, the share of AIDS-related deaths increased until 2006, reaching 40.3 percent, before declining significantly. However, the number of deaths is likely to see an increase following the United States of America's decision to cut aid funding.

This statistic indicates the percentage of U.S. adults aged 20 and over that have used prescription sleep aids in the last 30 days between 2005 and 2010 based on gender and ethnicity. Women were more likely than men to use prescription sleep aid with 5.0 percent of those surveyed, using sleep aids. In non-Hispanic black individuals, 2.5 percent reported using prescription sleep aids. Sleep aids are used to maintain or prompt sleep through the suppression of activities within the central nervous system. The pharmaceutical industry has witnessed an increase in sleep aid prescriptions in the United States.

In 2024, the estimated number of deaths from AIDS in South Africa reached 68,406. This was slightly higher compared to the previous year, when the AIDS related deaths in the country amounted to 68,382. From 2006 onwards (except in 2016), the number of AIDS-related deaths dropped annually.

Baseline demographics and viral load characteristics of 55 HIV-1C infected individuals.

Association between socio-demographics, risk behaviours and HIV status of injection drug users in Kampala Uganda.

The values indicate the median and 95% confidence intervals. *Due to the longitudinal and archival nature of this dataset, the limit of detection with respect to viral load has changed but has ranged from

For those born in 2023, the average life expectancy at birth across Africa was 61 years for men and 65 years for women. The average life expectancy globally was 70 years for men and 75 years for women in mid-2023.

Additional information on life expectancy in Africa

With the exception of North Africa where life expectancy is around the worldwide average for men and women, life expectancy across all African regions paints a bleak picture. Comparison of life expectancy by continent shows the gap in average life expectancy between Africa and other continent regions. Africa trails Latin America and the Caribbean, the continent with the second lowest average life expectancy, by 10 years for men and 12 years for women.

Life expectancy in Africa is the lowest globally Moreover, countries from across the African regions dominate the list of countries with the lowest life expectancy worldwide. Nigeria and Lesotho had the lowest life expectancy for those born in 2023 for men and women, respectively. However there is reason for hope despite the low life expectancy rates in many African countries. The Human Development index rating in Sub-Saharan Africa has increased dramatically from 0.43 to 0.55 between 2000 and 2021, demonstrating an improvement in quality of life and as a result greater access to vital services that allow people to live longer lives. One such improvement has been successful efforts to reduce the rate of aids infection and research into combating its effects. The number of new HIV infections across Africa has decreased from around 1.3 million in 2015 to 760,000 in 2022.