The states with the highest rates of HIV diagnoses in 2022 included Georgia, Louisiana, and Florida. However, the states with the highest number of people with HIV were Texas, California, and Florida. In Texas, there were around 4,896 people diagnosed with HIV. HIV/AIDS diagnoses In 2022, there were an estimated 38,043 new HIV diagnoses in the United States, a slight increase compared to the year before. Men account for the majority of these new diagnoses. There are currently around 1.2 million people living with HIV in the United States. Deaths from HIV The death rate from HIV has decreased significantly over the past few decades. In 2023, there were only 1.3 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 19.2 per 100,000 population in 2022, compared to just three deaths per 100,000 among the white population.

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

The average for 2022 based on 135 countries was 1.66 percent. The highest value was in Swaziland: 25.9 percent and the lowest value was in Afghanistan: 0.1 percent. The indicator is available from 1990 to 2022. Below is a chart for all countries where data are available.

In 2024, the number of diagnosed HIV cases in Mexico amounted to approximately 19,000. That year, the State of Mexico, Veracruz, and Mexico City were the federative entities with the highest number of people diagnosed with the human immunodeficiency virus (HIV), with more than 1,000 patients each. Moreover, most registered HIV cases in the Latin American country between 1984 and 2023 corresponded to men. People living with HIV in Latin America In the last few years, the number of people living with HIV in Latin America has been increasing. According to recent estimates, the number of individuals living with this condition rose from around 1.6 million in 2013 to almost 2.2 million by 2022. From a country perspective, Brazil and Mexico were the Latin American nations where most people were living with the disease, reaching approximately 990,000 and 370,000 patients, respectively. ART is more costly in Latin America HIV is commonly treated through antiretroviral therapy (ART), a drug-based treatment aimed at reducing the viral load in the blood to help control the development of the disease while improving the health of those infected. Although the share of deaths among people living with HIV due to causes unrelated to AIDS increased globally since 2010, there are still inequalities in the access to ART therapy. As of 2022, Latin America and the Caribbean recorded the highest average price per person for HIV antiretroviral therapy compared to other regions worldwide.

Spatial analysis at different levels can help understand spatial variation of human immunodeficiency virus (HIV) infection, disease drivers, and targeted interventions. Combining spatial analysis and the evaluation of the determinants of the HIV burden in Southern African countries is essential for a better understanding of the disease dynamics in high-burden settings.The study countries were selected based on the availability of demographic and health surveys (DHS) and corresponding geographic coordinates. We used multivariable regression to evaluate the determinants of HIV burden and assessed the presence and nature of HIV spatial autocorrelation in six Southern African countries.The overall prevalence of HIV for each country varied between 11.3% in Zambia and 22.4% in South Africa. The HIV prevalence rate was higher among female respondents in all six countries. There were reductions in prevalence estimates in most countries yearly from 2011 to 2020. The hotspot cluster findings show that the major cities in each country are the key sites of high HIV burden. Compared with female respondents, the odds of being HIV positive were lesser among the male respondents. The probability of HIV infection was higher among those who had sexually transmitted infections (STI) in the last 12 months, divorced and widowed individuals, and women aged 25 years and older.Our research findings show that analysis of survey data could provide reasonable estimates of the wide-ranging spatial structure of the HIV epidemic in Southern African countries. Key determinants such as individuals who are divorced, middle-aged women, and people who recently treated STIs, should be the focus of HIV prevention and control interventions. The spatial distribution of high-burden areas for HIV in the selected countries was more pronounced in the major cities. Interventions should also be focused on locations identified as hotspot clusters.

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.

As of 2023, South Africa was the country with the highest number of people living with HIV in Africa. At that time, around 7.7 million people in South Africa were HIV positive. In Mozambique, the country with the second-highest number of HIV-positive people in Africa, around 2.4 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 Lesotho and South Africa. However, South Africa had the highest total number of new HIV infections in 2023, with around 150,000 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 fourth leading cause of death in Africa, accounting for around 5.6 percent of all deaths. In 2023, South Africa and Nigeria were the countries with the highest number of AIDS-related deaths worldwide with 50,000 and 45,000 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 95 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 77 percent of people who are HIV positive in South Africa receiving ART, and only 31 percent in the Congo.

Certain subpopulations like female sex workers (FSW), men who have sex with men (MSM), and people who inject drugs (PWID) often have higher prevalence of HIV/AIDS and are difficult to map directly due to stigma, discrimination, and criminalization. Fine-scale mapping of those populations contributes to the progress toward reducing the inequalities and ending the AIDS epidemic. In 2016 and 2017, the PLACE surveys were conducted at 3290 venues in 20 out of the total 28 districts in Malawi to estimate the FSW sizes. These venues represent a presence-only dataset where, instead of knowing both where people live and do not live (presence–absence data), only information about visited locations is available. In this study, we develop a Bayesian model for presence-only data and utilize the PLACE data to estimate the FSW size and uncertainty interval at a1.5×1.5-km resolution for all of Malawi. The estimates can also be aggregated to any desirable level (city/district/region) for implementing targeted HIV prevention and treatment programs in FSW communities, which have been successful in lowering the incidence of HIV and other sexually transmitted infections. Supplementary materials for this article, including a standardized description of the materials available for reproducing the work, are available as an online supplement.

Rate ratios of the association between municipality homicide rates and municipality HIV rates for women.

BackgroundWashington DC has a high burden of HIV with a 2.0% HIV prevalence. The city is a national and international hub potentially containing a broad diversity of HIV variants; yet few sequences from DC are available on GenBank to assess the evolutionary history of HIV in the US capital. Towards this general goal, here we analyze extensive sequence data and investigate HIV diversity, phylodynamics, and drug resistant mutations (DRM) in DC.MethodsMolecular HIV-1 sequences were collected from participants infected through 2015 as part of the DC Cohort, a longitudinal observational study of HIV+ patients receiving care at 13 DC clinics. Sequences were paired with Cohort demographic, risk, and clinical data and analyzed using maximum likelihood, Bayesian and coalescent approaches of phylogenetic, network and population genetic inference. We analyzed 601 sequences from 223 participants for int (~864 bp) and 2,810 sequences from 1,659 participants for PR/RT (~1497 bp).ResultsNinety-nine and 94% of the int and PR/RT sequences, respectively, were identified as subtype B, with 14 non-B subtypes also detected. Phylodynamic analyses of US born infected individuals showed that HIV population size varied little over time with no significant decline in diversity. Phylogenetic analyses grouped 13.5% of the int sequences into 14 clusters of 2 or 3 sequences, and 39.0% of the PR/RT sequences into 203 clusters of 2–32 sequences. Network analyses grouped 3.6% of the int sequences into 4 clusters of 2 sequences, and 10.6% of the PR/RT sequences into 76 clusters of 2–7 sequences. All network clusters were detected in our phylogenetic analyses. Higher proportions of clustered sequences were found in zip codes where HIV prevalence is highest (r = 0.607; P

Human immunodeficiency virus (HIV) is the virus that causes acquired immune deficiency syndrome (AIDS): a condition that damages the immune system, making it incapable to defeat diseases. In 2023, Lombardy and Lazio were the Italian regions with the highest number of newly diagnosed HIV infections, with *** and *** cases, respectively. HIV in Italy In Italy, the number of new HIV cases fluctuated over time and, since 2016, is constantly decreasing until 2020 to then increase again. HIV has always been more common among males than females, and the most affected age group was the one consisting of people who were 30 to 39 years old, both among men and women. As a matter of fact, in 2023, *** males and *** females in their *** were newly diagnosed with HIV. HIV in Europe A similar trend of the one observed in Italy can be observed in Europe. Indeed, new HIV diagnosis in Europe have been increasing again since 2020, and in 2022 new cases of HIV among males totaled **** thousand, while among females they reached almost *** thousand, the highest figure since 2013.

Abstract

The 2005 Vietnam Population and AIDS Indicator Survey (VPAIS) was designed with the objective of obtaining national and sub-national information about program indicators of knowledge, attitudes and sexual behavior related to HIV/AIDS. Data collection took place from 17 September 2005 until mid-December 2005.

The VPAIS was implemented by the General Statistical Office (GSO) in collaboration with the National Institute of Hygiene and Epidemiology (NIHE). ORC Macro provided financial and technical assistance for the survey through the USAID-funded MEASURE DHS program. Financial support was provided by the Government of Vietnam, the United States President’s Emergency Plan for AIDS Relief, the United States Agency for International Development (USAID), and the United States Centers for Disease Control and Prevention/Global AIDS Program (CDC/GAP).

The survey obtained information on sexual behavior, and knowledge, attitudes, and behavior regarding HIV/AIDS. In addition, in Hai Phong province, the survey also collected blood samples from survey respondents in order to estimate the prevalence of HIV. The overall goal of the survey was to provide program managers and policymakers involved in HIV/AIDS programs with strategic information needed to effectively plan, implement and evaluate future interventions.

The information is also intended to assist policymakers and program implementers to monitor and evaluate existing programs and to design new strategies for combating the HIV/AIDS epidemic in Vietnam. The survey data will also be used to calculate indicators developed by the United Nations General Assembly Special Session on HIV/AIDS (UNGASS), UNAIDS, WHO, USAID, the United States President’s Emergency Plan for AIDS Relief, and the HIV/AIDS National Response.

The specific objectives of the 2005 VPAIS were: • to obtain information on sexual behavior. • to obtain accurate information on behavioral indicators related to HIV/AIDS and other sexually transmitted infections. • to obtain accurate information on HIV/AIDS program indicators. • to obtain accurate estimates of the magnitude and variation in HIV prevalence in Hai Phong Province.

Geographic coverage

National coverage

Analysis unit

• Household
• Women age 15-49
• Men age 15-49

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling frame for the 2005 Vietnam Population and AIDS Indicator Survey (VPAIS) was the master sample used by the General Statistical Office (GSO) for its annual Population Change Survey (PCS 2005). The master sample itself was constructed in 2004 from the 1999 Population and Housing Census. As was true for the VNDHS 1997 and the VNDHS 2002 the VPAIS 2005 is a nationally representative sample of the entire population of Vietnam.

The survey utilized a two-stage sample design. In the first stage, 251 clusters were selected from the master sample. In the second stage, a fixed number of households were systematically selected within each cluster, 22 households in urban areas and 28 in rural areas.

The total sample of 251 clusters is comprised of 97 urban and 154 rural clusters. HIV/AIDS programs have focused efforts in the four provinces of Hai Phong, Ha Noi, Quang Ninh and Ho Chi Minh City; therefore, it was determined that the sample should be selected to allow for representative estimates of these four provinces in addition to the national estimates. The selected clusters were allocated as follows: 35 clusters in Hai Phong province where blood samples were collected to estimate HIV prevalence; 22 clusters in each of the other three targeted provinces of Ha Noi, Quang Ninh and Ho Chi Minh City; and the remaining 150 clusters from the other 60 provinces throughout the country.

Prior to the VPAIS fieldwork, GSO conducted a listing operation in each of the selected clusters. All households residing in the sample points were systematically listed by teams of enumerators, using listing forms specially designed for this activity, and also drew sketch maps of each cluster. A total of 6,446 households were selected. The VPAIS collected data representative of: • the entire country, at the national level • for urban and rural areas • for three regions (North, Central and South), see Appendix for classification of regions. • for four target provinces: Ha Noi, Hai Phong, Quang Ninh and Ho Chi Minh City.

All women and men aged 15-49 years who were either permanent residents of the sampled households or visitors present in the household during the night before the survey were eligible to be interviewed in the survey. All women and men in the sample points of Hai Phong who were interviewed were asked to voluntarily give a blood sample for HIV testing. For youths aged 15-17, blood samples were drawn only after first obtaining consent from their parents or guardians.

(Refer Appendix A of the final survey report for details of sample implementation)

Mode of data collection

Face-to-face [f2f]

Research instrument

Two questionnaires were used in the survey, the Household Questionnaire and the Individual Questionnaire for women and men aged 15-49. The content of these questionnaires was based on the model AIDS Indicator Survey (AIS) questionnaires developed by the MEASURE DHS program implemented by ORC Macro.

In consultation with government agencies and local and international organizations, the GSO and NIHE modified the model questionnaires to reflect issues in HIV/AIDS relevant to Vietnam. These questionnaires were then translated from English into Vietnamese. The questionnaires were further refined after the pretest.

The Household Questionnaire was used to list all the usual members and visitors in the selected households. Some basic information was collected on the characteristics of each person listed, including age, sex, relationship to the head of the household, education, basic material needs, survivorship and residence of biological parents of children under the age of 18 years and birth registration of children under the age of 5 years. The main purpose of the Household Questionnaire was to identify women and men who were eligible for the individual interview. The Household Questionnaire also collected information on characteristics of the household’s dwelling unit, such as the source of drinking water, type of toilet facilities, type of material used in the flooring of the house, and ownership of various durable goods, in order to allow for the calculation of a wealth index. The Household Questionnaire also collected information regarding ownership and use of mosquito nets.

The Individual Questionnaire was used to collect information from all women and men aged 15-49 years.

All questionnaires were administered in a face-to-face interview. Because cultural norms in Vietnam restrict open discussion of sexual behavior, there is concern that this technique may contribute to potential under-reporting of sexual activity, especially outside of marriage.

All aspects of VPAIS data collection were pre-tested in July 2005. In total, 24 interviewers (12 men and 12 women) were involved in this task. They were trained for thirteen days (including three days of fieldwork practice) and then proceeded to conduct the survey in the various urban and rural districts of Ha Noi. In total, 240 individual interviews were completed during the pretest. The lessons learnt from the pretest were used to finalize the survey instruments and logistical arrangements for the survey and blood collection.

Cleaning operations

The data processing of the VPAIS questionnaire began shortly after the fieldwork commenced. The first stage of data editing was done by the field editors, who checked the questionnaires for completeness and consistency. Supervisors also reviewed the questionnaires in the field. The completed questionnaires were then sent periodically to the GSO in Ha Noi by mail for data processing.

The office editing staff first checked that questionnaires of all households and eligible respondents had been received from the field. The data were then entered and edited using CSPro, a software package developed collaboratively between the U.S. Census Bureau, ORC Macro, and SerPRO to process complex surveys. All data were entered twice (100 percent verification). The concurrent processing of the data was a distinct advantage for data quality, as VPAIS staff was able to advise field teams of errors detected during data entry. The data entry and editing phases of the survey were completed by the end of December 2005.

Response rate

A total of 6,446 households were selected in the sample, of which 6,346 (98 percent) were found to be occupied at the time of the fieldwork. Occupied households include dwellings in which the household was present but no competent respondent was home, the household was present but refused the interview, and dwellings that were not found. Of occupied households, 6,337 were interviewed, yielding a household response rate close to 100 percent.

All women and men aged 15-49 years who were either permanent residents of the sampled households or visitors present in the household during the night before the survey were eligible to be interviewed in the survey. Within interviewed households, a total of 7,369 women aged 15-49 were identified as eligible for interview, of whom 7,289 were interviewed, yielding a response rate to the Individual interview of 99 percent among women. The high response rate was also achieved in male interviews. Among the 6,788 men aged 15-49 identified as eligible for interview, 6,707 were successfully interviewed, yielding a response rate of 99 percent.

Sampling error

^ Pooled estimate, weighted by male population aged ≥ 18 years in city.§ Weighted by population in city and inverse degree. CI, confidence interval.Prevalence of HIV infection among men who have sex with men in Colombia by study site.

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

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.

Abstract

The National Family Health Surveys (NFHS) programme, initiated in the early 1990s, has emerged as a nationally important source of data on population, health, and nutrition for India and its states. The 2005-06 National Family Health Survey (NFHS-3), the third in the series of these national surveys, was preceded by NFHS-1 in 1992-93 and NFHS-2 in 1998-99. Like NFHS-1 and NFHS-2, NFHS-3 was designed to provide estimates of important indicators on family welfare, maternal and child health, and nutrition. In addition, NFHS-3 provides information on several new and emerging issues, including family life education, safe injections, perinatal mortality, adolescent reproductive health, high-risk sexual behaviour, tuberculosis, and malaria. Further, unlike the earlier surveys in which only ever-married women age 15-49 were eligible for individual interviews, NFHS-3 interviewed all women age 15-49 and all men age 15-54. Information on nutritional status, including the prevalence of anaemia, is provided in NFHS3 for women age 15-49, men age 15-54, and young children.

A special feature of NFHS-3 is the inclusion of testing of the adult population for HIV. NFHS-3 is the first nationwide community-based survey in India to provide an estimate of HIV prevalence in the general population. Specifically, NFHS-3 provides estimates of HIV prevalence among women age 15-49 and men age 15-54 for all of India, and separately for Uttar Pradesh and for Andhra Pradesh, Karnataka, Maharashtra, Manipur, and Tamil Nadu, five out of the six states classified by the National AIDS Control Organization (NACO) as high HIV prevalence states. No estimate of HIV prevalence is being provided for Nagaland, the sixth high HIV prevalence state, due to strong local opposition to the collection of blood samples.

NFHS-3 covered all 29 states in India, which comprise more than 99 percent of India's population. NFHS-3 is designed to provide estimates of key indicators for India as a whole and, with the exception of HIV prevalence, for all 29 states by urban-rural residence. Additionally, NFHS-3 provides estimates for the slum and non-slum populations of eight cities, namely Chennai, Delhi, Hyderabad, Indore, Kolkata, Meerut, Mumbai, and Nagpur. NFHS-3 was conducted under the stewardship of the Ministry of Health and Family Welfare (MOHFW), Government of India, and is the result of the collaborative efforts of a large number of organizations. The International Institute for Population Sciences (IIPS), Mumbai, was designated by MOHFW as the nodal agency for the project. Funding for NFHS-3 was provided by the United States Agency for International Development (USAID), DFID, the Bill and Melinda Gates Foundation, UNICEF, UNFPA, and MOHFW. Macro International, USA, provided technical assistance at all stages of the NFHS-3 project. NACO and the National AIDS Research Institute (NARI) provided technical assistance for the HIV component of NFHS-3. Eighteen Research Organizations, including six Population Research Centres, shouldered the responsibility of conducting the survey in the different states of India and producing electronic data files.

The survey used a uniform sample design, questionnaires (translated into 18 Indian languages), field procedures, and procedures for biomarker measurements throughout the country to facilitate comparability across the states and to ensure the highest possible data quality. The contents of the questionnaires were decided through an extensive collaborative process in early 2005. Based on provisional data, two national-level fact sheets and 29 state fact sheets that provide estimates of more than 50 key indicators of population, health, family welfare, and nutrition have already been released. The basic objective of releasing fact sheets within a very short period after the completion of data collection was to provide immediate feedback to planners and programme managers on key process indicators.

Geographic coverage

• National (29 states )
• Regional (for HIV Prevalence : Andhra Pradesh, Karnataka, Maharashtra, Manipur, and Tamil Nadu)
• Local (population and health indicators for slum and non-slum populations for eight cities, namely Chennai, Delhi, Hyderabad, Indore, Kolkata, Meerut, Mumbai, and Nagpur)

Analysis unit

• Household
• Women age 15-49
• Men age 15-59

Universe

The population covered by the 2005 DHS is defined as the universe of all ever-married women age 15-49, NFHS-3 included never married women age 15-49 and both ever-married and never married men age 15-54 as eligible respondents.

Kind of data

Sample survey data

Sampling procedure

SAMPLE SIZE

Since a large number of the key indicators to be estimated from NFHS-3 refer to ever-married women in the reproductive ages of 15-49, the target sample size for each state in NFHS-3 was estimated in terms of the number of ever-married women in the reproductive ages to be interviewed.

The initial target sample size was 4,000 completed interviews with ever-married women in states with a 2001 population of more than 30 million, 3,000 completed interviews with ever-married women in states with a 2001 population between 5 and 30 million, and 1,500 completed interviews with ever-married women in states with a population of less than 5 million. In addition, because of sample-size adjustments required to meet the need for HIV prevalence estimates for the high HIV prevalence states and Uttar Pradesh and for slum and non-slum estimates in eight selected cities, the sample size in some states was higher than that fixed by the above criteria. The target sample was increased for Andhra Pradesh, Karnataka, Maharashtra, Manipur, Nagaland, Tamil Nadu, and Uttar Pradesh to permit the calculation of reliable HIV prevalence estimates for each of these states. The sample size in Andhra Pradesh, Delhi, Maharashtra, Tamil Nadu, Madhya Pradesh, and West Bengal was increased to allow separate estimates for slum and non-slum populations in the cities of Chennai, Delhi, Hyderabad, Indore, Kolkata, Mumbai, Meerut, and Nagpur.

The target sample size for HIV tests was estimated on the basis of the assumed HIV prevalence rate, the design effect of the sample, and the acceptable level of precision. With an assumed level of HIV prevalence of 1.25 percent and a 15 percent relative standard error, the estimated sample size was 6,400 HIV tests each for men and women in each of the high HIV prevalence states. At the national level, the assumed level of HIV prevalence of less than 1 percent (0.92 percent) and less than a 5 percent relative standard error yielded a target of 125,000 HIV tests at the national level.

Blood was collected for HIV testing from all consenting ever-married and never married women age 15-49 and men age 15-54 in all sample households in Andhra Pradesh, Karnataka, Maharashtra, Manipur, Tamil Nadu, and Uttar Pradesh. All women age 15-49 and men age 15-54 in the sample households were eligible for interviewing in all of these states plus Nagaland. In the remaining 22 states, all ever-married and never married women age 15-49 in sample households were eligible to be interviewed. In those 22 states, men age 15-54 were eligible to be interviewed in only a subsample of households. HIV tests for women and men were carried out in only a subsample of the households that were selected for men's interviews in those 22 states. The reason for this sample design is that the required number of HIV tests is determined by the need to calculate HIV prevalence at the national level and for some states, whereas the number of individual interviews is determined by the need to provide state level estimates for attitudinal and behavioural indicators in every state. For statistical reasons, it is not possible to estimate HIV prevalence in every state from NFHS-3 as the number of tests required for estimating HIV prevalence reliably in low HIV prevalence states would have been very large.

SAMPLE DESIGN

The urban and rural samples within each state were drawn separately and, to the extent possible, unless oversampling was required to permit separate estimates for urban slum and non-slum areas, the sample within each state was allocated proportionally to the size of the state's urban and rural populations. A uniform sample design was adopted in all states. In each state, the rural sample was selected in two stages, with the selection of Primary Sampling Units (PSUs), which are villages, with probability proportional to population size (PPS) at the first stage, followed by the random selection of households within each PSU in the second stage. In urban areas, a three-stage procedure was followed. In the first stage, wards were selected with PPS sampling. In the next stage, one census enumeration block (CEB) was randomly selected from each sample ward. In the final stage, households were randomly selected within each selected CEB.

SAMPLE SELECTION IN RURAL AREAS

In rural areas, the 2001 Census list of villages served as the sampling frame. The list was stratified by a number of variables. The first level of stratification was geographic, with districts being subdivided into contiguous regions. Within each of these regions, villages were further stratified using selected variables from the following list: village size, percentage of males working in the nonagricultural sector, percentage of the population belonging to scheduled castes or scheduled tribes, and female literacy. In addition to these variables, an external estimate of HIV prevalence, i.e., 'High', 'Medium' or 'Low', as estimated for all the districts in high HIV prevalence states, was used for stratification in high HIV prevalence states. Female literacy was used for implicit stratification (i.e., villages were

BackgroundMobile HIV screening may facilitate early HIV diagnosis. Our objective was to examine the cost-effectiveness of adding a mobile screening unit to current medical facility-based HIV testing in Cape Town, South Africa.Methods and FindingsWe used the Cost Effectiveness of Preventing AIDS Complications International (CEPAC-I) computer simulation model to evaluate two HIV screening strategies in Cape Town: 1) medical facility-based testing (the current standard of care) and 2) addition of a mobile HIV-testing unit intervention in the same community. Baseline input parameters were derived from a Cape Town-based mobile unit that tested 18,870 individuals over 2 years: prevalence of previously undiagnosed HIV (6.6%), mean CD4 count at diagnosis (males 423/µL, females 516/µL), CD4 count-dependent linkage to care rates (males 31%–58%, females 49%–58%), mobile unit intervention cost (includes acquisition, operation and HIV test costs, $29.30 per negative result and $31.30 per positive result). We conducted extensive sensitivity analyses to evaluate input uncertainty. Model outcomes included site of HIV diagnosis, life expectancy, medical costs, and the incremental cost-effectiveness ratio (ICER) of the intervention compared to medical facility-based testing. We considered the intervention to be “very cost-effective” when the ICER was less than South Africa's annual per capita Gross Domestic Product (GDP) ($8,200 in 2012). We projected that, with medical facility-based testing, the discounted (undiscounted) HIV-infected population life expectancy was 132.2 (197.7) months; this increased to 140.7 (211.7) months with the addition of the mobile unit. The ICER for the mobile unit was $2,400/year of life saved (YLS). Results were most sensitive to the previously undiagnosed HIV prevalence, linkage to care rates, and frequency of HIV testing at medical facilities.ConclusionThe addition of mobile HIV screening to current testing programs can improve survival and be very cost-effective in South Africa and other resource-limited settings, and should be a priority.

ObjectiveMen who have sex with men (MSM) and heterosexuals are the populations with the fastest growing HIV infection rates in China. We characterize the epidemic growth and age patterns between these two routes from 2004 to 2015 in Chongqing and Shenzhen, China.Design and methodsData were downloaded from the National HIV/ AIDS Comprehensive Response Information Management System. For the new HIV diagnoses of heterosexuals and MSM in both cities, we estimated the growth rates by fitting different sub-exponential models. Heat maps are used to show their age patterns. We used histograms to compare these patterns by birth cohort.ResultsThe MSM epidemics grew significantly in both cities. Chongqing experienced quadratic growth in HIV reported cases with an estimated growth rate of 0.086 per week and a “deceleration rate” of 0.673. HIV reported cases of MSM in Shenzhen grew even more drastically with a growth rate of 0.033 per week and “deceleration rate” of 0.794. The new infections are mainly affecting the ages of 18 to 30 in Chongqing and ages of 20 to 35 in Shenzhen. They peaked in early 1990’s and mid-1990’s birth cohorts in Chongqing and Shenzhen respectively. The HIV epidemic among heterosexuals grew rapidly in both cities. The growth rates were estimated as 0.02 and 0.028 in Chongqing and Shenzhen respectively whereas the “deceleration rates” were 0.878 and 0.790 in these two places. It affected mostly aged 18 to 75 in males and 18 to 65 in females in Chongqing and aged 18 to 45 in males and 18 to 50 in females in Shenzhen in 2015. In Chongqing, the heterosexual female epidemics display two peaks in HIV diagnoses in the birth cohorts of early 1950’s and early 1980’s, with heterosexual male epidemics peaked in early 1940’s and early 1960’s. The heterosexual male and female epidemics display higher rates in the birth cohort 1940-1960, than the birth cohort 1960-1990. It peaked in birth cohorts of 1950’s and 1980’s in Shenzhen.ConclusionsWe revealed striking differences in epidemic growth and age patterns of the HIV epidemics in these two cities. Our results may be used to inform age-targeted public health policies to curb their epidemic growth.

Gender, violence, and migration structurally impact health. The Venezuelan humanitarian crisis comprises the largest transnational migration in the history of the Americas. Colombia, a post-conflict country, is the primary recipient of Venezuelans. The Colombian context imposes high levels of violence on women across migration phases. There is little information on the relationship between violence and HIV risk in the region and how it impacts these groups. Evidence on how to approach the HIV response related to Venezuela’s humanitarian crisis is lacking. Our study seeks to 1) understand how violence is associated with newly reported HIV/AIDS case rates for women in Colombian municipalities; and 2) describe how social violence impacts HIV risk, treatment, and prevention for Venezuelan migrant and refugee women undergoing transnational migration and resettlement in Colombia. We conducted a concurrent mixed-methods design. We used negative binomial models to explore associations between social violence proxied by Homicide Rates (HR) at the municipality level (n = 84). The also conducted 54 semi-structured interviews with Venezuelan migrant and refugee women and key informants in two Colombian cities to expand and describe contextual vulnerabilities to HIV risk, prevention and care related to violence. We found that newly reported HIV cases in women were 25% higher for every increase of 18 homicides per 100,000, after adjusting for covariates. Upon resettlement, participants cited armed actors’ control, lack of government accountability, gender-based violence and stigmatization of HIV as sources of increased HIV risk for VMRW. These factors impose barriers to testing, treatment and care. Social violence in Colombian municipalities is associated with an increase in newly reported HIV/AIDS case rates in women. Violence hinders Venezuelan migrant and refugee women’s access and engagement in available HIV prevention and treatment interventions.

BackgroundYunnan has the greatest share of reported human immunodeficiency virus (HIV)/acquired immunodeficiency syndrome (AIDS) cases in China. In recent years, HIV prevalence and incidence remained stubbornly high in men who have sex with men (MSM). To follow the dynamics of the HIV-1 epidemic among MSM, HIV-1 genetic characteristics and genetic transmission networks were investigated.MethodsBlood samples from 190 newly diagnosed HIV-1 cases among MSM were continuously collected at fixed sites from January 2013 to December 2015 in Kunming City, Yunnan Province. Partial gag, pol and env genes were sequenced and used for phylogenetic and genotypic drug resistance analyses. The genetic characteristics of the predominant HIV-1 strains were analyzed by the Bayesian Markov Chain Monte Carlo (MCMC) method. The genetic transmission networks were identified with a genetic distance of 0.03 substitutions/site and 90% bootstrap support.ResultsAmong the 190 HIV-1 positive MSM reported during 2013–2105, various genotypes were identified, including CRF01_AE (45.3%), CRF07_BC (35.8%), unique recombinant forms (URFs) (11.6%), CRF08_BC (3.2%), CRF55_01B (2.1%), subtype B (1.6%) and CRF59_01B (0.5%). The effective population sizes (EPS) for CRF01_AE and CRF07_BC increased exponentially from approximately 2001–2010 and 2005–2009, respectively. Genetic transmission networks were constructed with 308 pol sequences from MSM diagnosed during 2010–2015. Of the 308 MSM, 109 (35.4%) were identified in 38 distinct clusters. Having multiple male partners was associated with a high probability of identification in the genetic transmission networks. Of the 38 clusters, 27 (71.1%) contained individuals diagnosed in different years. Of the 109 individuals in the networks, 26 (23.9%) had ≥2 potential transmission partners (≥2 links). The proportion of MSM with ≥2 links was higher among those diagnosed from 2010–2012. The constituent ratios of their potential transmission partners by areas showed no significant difference among MSM from Kunming, other cities in Yunnan and other provinces. Additionally, surveillance drug resistance mutations (SDRMs) were identified in 5% of individuals.ConclusionThis study revealed the various HIV-a genotypes circulating among MSM in Kunming. MSM with more partners were more easily detected in transmission networks, and early-diagnosed MSM remained active in transmission networks. These findings suggested that the routine interventions should be combined with HIV testing and linkage to care and early antiretroviral therapy among HIV-positive MSM.