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.

In 2022, the states with the highest number of HIV diagnoses were Texas, California, and Florida. That year, there were a total of around 37,601 HIV diagnoses in the United States. Of these, 4,896 were diagnosed in Texas. HIV infections have been decreasing globally for many years. In the year 2000, there were 2.8 million new infections worldwide, but this number had decreased to around 1.3 million new infections by 2023. The number of people living with HIV remains fairly steady, but the number of those that have died due to AIDS has reached some of its lowest peaks in a decade. Currently, there is no functional cure for HIV or AIDS, but improvements in therapies and treatments have enabled those living with HIV to have a much improved quality of life.

United States US: Prevalence of HIV: Total: % of Population Aged 15-49 data was reported at 0.500 % in 2014. This stayed constant from the previous number of 0.500 % for 2013. United States US: Prevalence of HIV: Total: % of Population Aged 15-49 data is updated yearly, averaging 0.500 % from Dec 2008 (Median) to 2014, with 7 observations. The data reached an all-time high of 0.500 % in 2014 and a record low of 0.500 % in 2014. United States US: Prevalence of HIV: Total: % of Population Aged 15-49 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s USA – Table US.World Bank: Health Statistics. Prevalence of HIV refers to the percentage of people ages 15-49 who are infected with HIV.; ; UNAIDS estimates.; Weighted Average;

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.

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, Lesotho, and South Africa. In 2023, 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 in recent years. However, despite being available worldwide, not all adults have access to antiretroviral drugs. Europe and North America have the highest rates of antiretroviral use among people living with HIV. 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.

According to Cognitive Market Research, the global HIV Diagnostics market size is USD 4158.2 million in 2024. It will expand at a compound annual growth rate (CAGR) of 10.90% from 2024 to 2031. North America held the major market share for more than 40% of the global revenue with a market size of USD 1663.28 million in 2024 and will grow at a compound annual growth rate (CAGR) of 9.1% from 2024 to 2031. Europe accounted for a market share of over 30% of the global revenue with a market size of USD 1247.46 million. Asia Pacific held a market share of around 23% of the global revenue with a market size of USD 956.39 million in 2024 and will grow at a compound annual growth rate (CAGR) of 12.9% from 2024 to 2031. Latin America had a market share of more than 5% of the global revenue with a market size of USD 207.91 million in 2024 and will grow at a compound annual growth rate (CAGR) of 10.3% from 2024 to 2031. Middle East and Africa had a market share of around 2% of the global revenue and was estimated at a market size of USD 83.16 million in 2024 and will grow at a compound annual growth rate (CAGR) of 10.6% from 2024 to 2031. Consumables held the highest HIV Diagnostics market revenue share in 2024. Market Dynamics of HIV Diagnostics Market Key Drivers for HIV Diagnostics Market Increasing Prevalence of Sexually Transmitted Disease to Increase the Demand Globally Throughout the many decades of the HIV pandemic, the number of infected individuals is continually rising. The socioeconomic variables driving this continuous increase also suggest that preventative measures have not been successful. Even though many of these infections are preventable, there are an estimated 20 million new cases of STDs in the US each year, and the rate is still rising. Moreover, there are over 1.2 million HIV-positive individuals residing in the United States. Attempts to encourage testing and screening for sexually transmitted infections can ascertain an individual's likelihood of acquiring one and help those who already have one receive treatment, so enhancing their health and lowering the danger of HIV spreading to others. Approximately 38.4 million people worldwide were HIV positive in 2021. Among these, women and girls made up nearly 54%. Rising Initiatives by Global Agencies to Propel Market Growth HIV is among the world's most important public health concerns. As a result, there is a global commitment to stopping new HIV infections and giving everyone on the planet access to HIV therapy. WHO recommends testing for HIV to anyone who might be at risk. The World Bank was a leader in global financing for HIV/AIDS in the early phases of the pandemic and has contributed US$4.6 billion to programs related to the illness since 1989. Because of assistance from the Bank—more precisely, through the International Development Association—for 1,500 counseling and testing centers, about 7 million people have had HIV tests. Restraint Factor for the HIV Diagnostics Market Lack of Healthcare Infrastructure and Awareness to Limit the Sales A proper infrastructure for healthcare delivery is lacking in many areas, especially in poor nations, which makes it difficult to provide diagnostic services. This covers concerns with the supply chain, inadequate laboratory facilities, and skilled staff. It might be particularly difficult to access diagnostic services in rural and isolated places due to a lack of healthcare facilities and inadequate transportation infrastructure. Furthermore, HIV diagnosis rates are lower in the developing Asia-Pacific, Middle East, and African regions. These areas require a sufficient number of diagnostic facilities. Additionally, the diagnosis process needs to be explained to the majority of patients, which restricts market growth in these areas. Impact of Covid-19 on the HIV Diagnostics Market The COVID-19 pandemic has had a significant impact on the HIV diagnostics market, both in terms of challenges and opportunities. There was a decrease in HIV testing and diagnostic services during the pandemic as a result of the extensive healthcare resources being redirected to handle COVID-19. Some facilities were converted to provide COVID-19 treatment, and clinics and labs had a staffing crisis. Reduced HIV testing rates were the outcome of routine and community-based HIV testing programs being frequently halted to stop the spread of COVID-19. The adoption of telemedicine and remote healthcare services was expedited by the epidem...

In 2018, São Paulo was the Brazilian state with the highest number of HIV-positive patients in the country, with 3,176 cases. It was followed by Rio de Janeiro, with around 1.7 thousand cases and Rio Grande do Sul, with nearly 1.5 thousand patients.

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.

BackgroundIn the generalised epidemics of sub-Saharan Africa (SSA), human immunodeficiency virus (HIV) prevalence shows patterns of clustered micro-epidemics. We mapped and characterised these high-prevalence areas for young adults (15–29 years of age), as a proxy for areas with high levels of transmission, for 7 countries in Eastern and Southern Africa: Kenya, Malawi, Mozambique, Tanzania, Uganda, Zambia, and Zimbabwe.Methods and findingsWe used geolocated survey data from the most recent United States Agency for International Development (USAID) demographic and health surveys (DHSs) and AIDS indicator surveys (AISs) (collected between 2008–2009 and 2015–2016), which included about 113,000 adults—of which there were about 53,000 young adults (27,000 women, 28,000 men)—from over 3,500 sample locations. First, ordinary kriging was applied to predict HIV prevalence at unmeasured locations. Second, we explored to what extent behavioural, socioeconomic, and environmental factors explain HIV prevalence at the individual- and sample-location level, by developing a series of multilevel multivariable logistic regression models and geospatially visualising unexplained model heterogeneity. National-level HIV prevalence for young adults ranged from 2.2% in Tanzania to 7.7% in Mozambique. However, at the subnational level, we found areas with prevalence among young adults as high as 11% or 15% alternating with areas with prevalence between 0% and 2%, suggesting the existence of areas with high levels of transmission Overall, 15.6% of heterogeneity could be explained by an interplay of known behavioural, socioeconomic, and environmental factors. Maps of the interpolated random effect estimates show that environmental variables, representing indicators of economic activity, were most powerful in explaining high-prevalence areas. Main study limitations were the inability to infer causality due to the cross-sectional nature of the surveys and the likely under-sampling of key populations in the surveys.ConclusionsWe found that, among young adults, micro-epidemics of relatively high HIV prevalence alternate with areas of very low prevalence, clearly illustrating the existence of areas with high levels of transmission. These areas are partially characterised by high economic activity, relatively high socioeconomic status, and risky sexual behaviour. Localised HIV prevention interventions specifically tailored to the populations at risk will be essential to curb transmission. More fine-scale geospatial mapping of key populations,—such as sex workers and migrant populations—could help us further understand the drivers of these areas with high levels of transmission and help us determine how they fuel the generalised epidemics in SSA.

In 2022, it was estimated that around 16.4 percent of Botswana's population aged 15-49 years was infected with HIV. This statistic shows the 20 countries with the highest prevalence of HIV worldwide as of 2022.

BackgroundIndian guidelines recommend routine referral for HIV testing of all tuberculosis (TB) patients in the nine states with the highest HIV prevalence, and selective referral for testing elsewhere. We assessed the clinical impact and cost-effectiveness of alternative HIV testing referral strategies among TB patients in India.Methods and FindingsWe utilized a computer model of HIV and TB disease to project outcomes for patients with active TB in India. We compared life expectancy, cost, and cost-effectiveness for three HIV testing referral strategies: 1) selective referral for HIV testing of those with increased HIV risk, 2) routine referral of patients in the nine highest HIV prevalence states with selective referral elsewhere (current standard), and 3) routine referral of all patients for HIV testing. TB-related data were from the World Health Organization. HIV prevalence among TB patients was 9.0% in the highest prevalence states, 2.9% in the other states, and 4.9% overall. The selective referral strategy, beginning from age 33.50 years, had a projected discounted life expectancy of 16.88 years and a mean lifetime HIV/TB treatment cost of US$100. The current standard increased mean life expectancy to 16.90 years with additional per-person cost of US$10; the incremental cost-effectiveness ratio was US$650/year of life saved (YLS) compared to selective referral. Routine referral of all patients for HIV testing increased life expectancy to 16.91 years, with an incremental cost-effectiveness ratio of US$730/YLS compared to the current standard. For HIV-infected patients cured of TB, receiving antiretroviral therapy increased survival from 4.71 to 13.87 years. Results were most sensitive to the HIV prevalence and the cost of second-line antiretroviral therapy.ConclusionsReferral of all patients with active TB in India for HIV testing will be both effective and cost-effective. While effective implementation of this strategy would require investment, routine, voluntary HIV testing of TB patients in India should be recommended.

Description: The adult and youth data of the SABSSM 2002 study cover information from adults and youths 15 years and older on topics ranging from biographical information, media and communication, male circumcision, marital status and marriage practice, partner and partner characteristics, sexual behaviour and practices, voluntary counseling and testing (VCT), sexual orientation, interpersonal communication, practices around widowhood, knowledge and perceptions of HIV and AIDS, stigma, hospitalisation and health status. The data set consists of 643 variables and 9788 cases. Abstract: Background: This is the first in a series of national HIV household surveys conducted in South Africa. The survey was commissioned by the Nelson Mandela Children's Fund and the Nelson Mandela Foundation. The key aims were to determine the HIV prevalence in the general population, identify risk factors that increase vulnerability of South Africans to HIV infections, to identify the contexts within which sexual behaviour occurs and the obstacles to risk reduction and to determine the level of exposure of all sectors of society to current prevention. The Nelson Mandela Children's Fund requested the HSRC to assess the impact of current HIV and AIDS education and awareness programmes designed to slow down the epidemic, including infection rates, stigma, care and support for affected individuals and families. Methodology: Sampling methods: multi-stage cluster stratified sample stratified by province, settlement geography (geotype) and predominant race group in each area. A systematic sample of 15 households was drawn from each of 1 000 census enumeration areas (EAs). In each household, one person was randomly selected in each of four mutually exclusive age groups (2-11 years; 12-14 years; 15-24 years; 25+ years). Field workers administered questionnaires to selected respondents and also collected oral fluid specimens for HIV testing. Results: This study sampled a cross-section of 9 963 South Africans aged two years and older. HIV is a generalised epidemic in South Africa that extends to all age groups, geographic areas and race groups. It showed 11.4 % were HIV positive, 15.6 per cent of them aged between 15 and 49. Women (12.8% HIV positive) were more at risk of infection than men (9.5% HIV positive). Urban informal settlements have the highest incidence of HIV infection (21.3%). Free State showed the highest prevalence (14.9%) with Eastern Cape having the lowest (6.6%). Higher rates of infection (5.6%) are also found in children aged 2-14 and Africans (10.2%). Awareness of HIV status was low. Only 18.9% reported that they were previously tested. Fewer women (3.9%) reported more than one sexual partner as compared to men (13.5%). Condom use at last sex was low among both women (24.7%) and men (30.3%). Knowledge of HIV and AIDS is generally high, with sexual behaviour changes taking root in encouragingly low numbers of sexual partners and high levels of abstinence among the youth. There is still great uncertainty of the relationship between HIV and AIDS and popular myths. South Africans from all walks of life are at risk. In particular, wealthy Africans have the same levels of risk as poorer Africans - whereas in other race groups, poorer people are more vulnerable to infection. Conclusions: The study recommended the expansion of voluntary counselling and testing. Prevention programmes ought to focus on reduction on multiple partners and increased condom use. It further recommended, inter alia, that HIV/AIDS prevention programmes be intensified for people living in informal settlements, campaigns be implemented using mass media to address myths and misconceptions and that information needs in rural communities and poorer households due to lack of access to mass media channels, should be attended to.

This directory is for at-risk for HIV and eligible persons living with HIV in New York City seeking HIV medical and supportive services. The agencies and their listed programs receive CDC and Ryan White Part-A funding to provide: Targeted-Testing among Priority Populations, Food and Nutrition Services, Health Education and Risk Reduction Services, Harm Reduction Services, Legal Services, Mental Health Services, Case Management and Care Coordination Services, and Supportive Counseling Services. To be eligible to recieve these services, prospective clients must: 1)be HIV-positive; 2) have a total household income below 435% of the Federal Poverty Level (FPL) (this is the same as the income eligible guidelines for the New York State AIDS Drug Assistance Program (ADAP) and higher than the income eligiblity guidelines for Medicaid in New York State); and 3) reside in New York City or the counties of Westchester, Rockland, and Putnam. For providers, to make a referral, please contact the program directly using the information provided in the diretory (please be sure to call before directing clients to the program). When making a referral, you may also find it useful to talk to your client about executing a release of information form authorizing you to share confidential health and HIV-related information with another service provider in order to coordinate care (for more information, go to https://www.health.ny.gov/diseases/aids/providers/forms/informedconsent.htm).

All figures are given as % (95% CI) unless noted. There were 61 counties in the top decile and 551 in the remaining deciles.

The Find Ryan White HIV/AIDS Medical Care Providers tool is a locator that helps people living with HIV/AIDS access medical care and related services. Users can search for Ryan White-funded medical care providers near a specific complete address, city and state, state and county, or ZIP code. Search results are sorted by distance away and include the Ryan White HIV/AIDS facility name, address, approximate distance from the search point, telephone number, website address, and a link for driving directions. HRSA's Ryan White program funds an array of grants at the state and local levels in areas where most needed. These grants provide medical and support services to more than a half million people who otherwise would be unable to afford care.

ObjectiveThe study objective is to measure, analyse costs of scaling up HIV prevention for high-risk groups in India, in order to assist the design of future HIV prevention programmes in South Asia and beyond.DesignProspective costing study.MethodsThis study is one of the most comprehensive studies of the costs of HIV prevention for high-risk groups to date in both its scope and size. HIV prevention included outreach, sexually transmitted infections (STI) services, condom provision, expertise enhancement, community mobilisation and enabling environment activities. Economic costs were collected from 138 non-government organisations (NGOs) in 64 districts, four state level lead implementing partners (SLPs), and the national programme level (Bill and Melinda Gates Foundation (BMGF)) office over four years using a top down costing approach, presented in US$ 2011.ResultsMean total unit costs (2004–08) per person reached at least once a year and per monthly contact were US$ 235(56–1864) and US$ 82(12–969) respectively. 35% of the cost was incurred by NGOs, 30% at the state level SLP and 35% at the national programme level. The proportion of total costs by activity were 34% for expertise enhancement, 37% for programme management (including support and supervision), 22% for core HIV prevention activities (outreach and STI services) and 7% for community mobilisation and enabling environment activities. Total unit cost per person reached fell sharply as the programme expanded due to declining unit costs above the service level (from US$ 477 per person reached in 2004 to US$ 145 per person reached in 2008). At the service level also unit costs decreased slightly over time from US$ 68 to US$ 64 per person reached.ConclusionsScaling up HIV prevention for high risk groups requires significant investment in expertise enhancement and programme administration. However, unit costs decreased with programme expansion in spite of an increase in the scope of activities.

United States US: Incidence of HIV: per 1,000 Uninfected Population Aged 15-49 data was reported at 0.220 Ratio in 2018. This stayed constant from the previous number of 0.220 Ratio for 2017. United States US: Incidence of HIV: per 1,000 Uninfected Population Aged 15-49 data is updated yearly, averaging 0.250 Ratio from Dec 1990 (Median) to 2018, with 29 observations. The data reached an all-time high of 0.290 Ratio in 1990 and a record low of 0.220 Ratio in 2018. United States US: Incidence of HIV: per 1,000 Uninfected Population Aged 15-49 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Health Statistics. Number of new HIV infections among uninfected populations ages 15-49 expressed per 1,000 uninfected population in the year before the period.; ; UNAIDS estimates.; Weighted average;

United States US: Children: 0-14 Living with HIV data was reported at 2,500.000 Person in 2019. This records a decrease from the previous number of 2,800.000 Person for 2018. United States US: Children: 0-14 Living with HIV data is updated yearly, averaging 3,700.000 Person from Dec 2010 (Median) to 2019, with 10 observations. The data reached an all-time high of 4,700.000 Person in 2010 and a record low of 2,500.000 Person in 2019. United States US: Children: 0-14 Living with HIV data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s United States – Table US.World Bank.WDI: Social: Health Statistics. Children living with HIV refers to the number of children ages 0-14 who are infected with HIV.;UNAIDS estimates.;;

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.

Abstract

The 2018 Nigeria AIDS Indicator and Impact Survey (NAIIS) is a cross-sectional survey that will assess the prevalence of key human immunodeficiency virus (HIV)-related health indicators. This survey is a two-stage cluster survey of 88,775 randomly-selected households in Nigeria, sampled from among 3,551 nationally-representative sample clusters. The survey is expected to include approximately 168,029 participants, ages 15-64 years and children, ages 0-14 years, from the selected household. The 2018 NAIIS will characterize HIV incidence, prevalence, viral load suppression, CD4 T-cell distribution, and risk behaviors in a household-based, nationally-representative sample of the population of Nigeria, and will describe uptake of key HIV prevention, care, and treatment services. The 2018 NAIIS will also estimate the prevalence of hepatitis B virus (HBV), hepatitis C virus (HCV) infections, and HBV/HIV and HCV/HIV co-infections.

Geographic coverage

National The survey covered the Federal Republic and was undertaken in each state and the Federal Capital

Analysis unit

Household Health Survey

Universe

1. Women and men aged 15-64 years living in residential households and visitors who slept in the household the night before the survey
2. Children aged 0-14 years living in residential households and child visitors who slept in the household the night before the survey

Kind of data

Sample survey data [ssd]

Sampling procedure

This cross-sectional, household-based survey will use a two-stage cluster sampling design (enumeration area followed by households). The target population is people 15-64 and children ages 0-14 years. The overall size and distribution of the sample is determined by analysis of existing estimates of national HIV incidence, sub-national HIV prevalence, and the number of HIV-positive cases needed to obtain estimates of VLS among adults 15-64 years for each of the 36 states and the FCT while not unnecessarily inflating the sample size needed. From a sampling perspective, the three primary objectives of this proposal are based on competing demands, one focused on national incidence and the other on state-level estimates in a large number of states (37). Since the denominator used for estimating VLS is HIV-positive individuals, the required minimum number of blood draws in a stratum is inversely proportional to the expected HIV prevalence rate in that stratum. This objective requires a disproportionate amount of sample to be allocated to states with the lowest prevalence. A review of state-level prevalence estimates for sources in the last 3 to 5 years shows that state-level estimates are often divergent from one source to the next, making it difficult to ascertain the sample size needed to obtain the roughly 100 PLHIV needed to achieve a 95% confidence interval (CI) of +/- 10 for VLS estimates. An equal-size approach is proposed with a sample size of 3,700 blood specimens in each state. Three-thousand seven hundred specimens will be sufficiently large to obtain robust estimates of HIV prevalence and VLS among HIV-infected individuals in most states. In states with a HIV prevalence above 2.5%, we can anticipate 95% CI of less than +/-10% and relative standard errors (RSEs) of less than 11% for estimates of VLS. In these states, with HIV prevalence above 2.5%, the anticipated 95% CI around prevalence is +/- 0.7% to a high of 1.1-1.3% in states with prevalence above 6%. In states with prevalence between 1.2 and 2.5% HIV prevalence estimates would remain robust with 95% CI of +/- 0.5-0.6% and RSE of less than 20% while 95% CI around VLS would range between 10-15% (and RSE below 15%). With this proposal only a few states, with HIV prevalence below 1.0%, would have less than robust estimates for VLS and HIV prevalence. The evaluation of this “equal-size” approach to the 37 strata are presented in Table 1 below using the 2016 Spectrum estimates with states sorted by prevalence level from highest to lowest. This “equal-size” approach will ensure sufficiently large sample in each state for comparisons between states and satisfy overall need for national incidence estimate. As a result of the “equal-size” approach and the large number of strata (37) it is anticipated that the RSE for a national incidence estimate will be quite small, at less than 9%, when the survey is complete. It is also anticipated that regional incidence estimates (6 regions) will be possible with RSEs of 30% or less.

Mode of data collection

Face-to-face [f2f]

Research instrument

Household Questionnaire Adult Questionnaire Early Adolescent Questionnaire (10-14 Years)

Cleaning operations

During the household data collection, questionnaire and laboratory data were transmitted between tablets via Bluetooth connection. This facilitated synchronization of household rosters and ensured data collection for each participant followed the correct pathway. All field data collected in CSPro and the Laboratory Data Management System (LDMS) were transmitted to a central server using File Transfer Protocol Secure (FTPS) over a 4G or 3G telecommunication provider at least once a day. Questionnaire data cleaning was conducted using CSPro and SAS 9.4 (SAS Institute Inc., Cary, North Carolina, United States). Laboratory data were cleaned and merged with the final questionnaire database using unique specimen barcodes and study identification numbers. All results presented in the technical report were based on weighted estimates unless otherwise stated. Analysis weights accounted for sample selection probabilities and adjusted for nonresponse and noncoverage. Nonresponse adjusted weights were calculated for households, individual interviews and individual blood draws in a hierarchical form. Adjustment for nonresponse for initial individual and bloodlevel weights was based on the development of weighting adjustment cells defined by a combination of variables that were potential predictors of response and HIV status. The nonresponse adjustment cells were constructed using the Chi-square Automatic Interaction Detector (CHAID) algorithm. The cells were defined based on data from the household interview for the adjustment of individual-level weights and from both the household and individual interviews for the adjustment of blood specimen-level weights. Post-stratification adjustments were implemented to compensate for non-coverage in the sampling process. This final adjustment calibrated the nonresponse-adjusted individual and blood weights to make the sum of each set of weights conform to national population totals by sex and five-year age groups. Descriptive analyses of response rates, characteristics of respondents, HIV prevalence, CD4 count distribution, HIV testing, self-reported HIV status, self-reported ART, VLS, PMTCT indicators, HBV, HCV and sexual behavior were conducted using SAS 9.4.

Response rate

A total of 101,267 households were selected, 89,345 were occupied and 83,909 completed the household interview . • For adults aged 15-64 years, interview response rate was 91.6% for women and 88.2% for men; blood draw response rate was 92.9% for women and 93.6% for men. • For adolescents aged 10-14 years, interview response rate was 86.8% for women and 86.2% for men; blood draw response rate was 91.2% for women and 92.3% for men. • For children aged 0-9 years, blood draw response rate was 68.5% for women and men.

Sampling error estimates

Estimates from sample surveys are affected by two types of errors: non-sampling errors and sampling errors. Non-sampling errors result from mistakes made during data collection, e.g., misinterpretation of an HIV test result and data management errors such as transcription errors during data entry. While NAIIS implemented numerous quality assurance and control measures to minimize non-sampling errors, these were impossible to avoid and difficult to evaluate statistically. In contrast, sampling errors can be evaluated statistically. Sampling errors are a measure of the variability between all possible samples. The sample of respondents selected for NAIIS was only one of many samples that could have been selected from the same population, using the same design and expected size. Each of these samples could yield results that differed somewhat from the results of the actual sample selected. Although the degree of variability cannot be known exactly, it can be estimated from the survey results. The standard error, which is the square root of the variance, is the usual measurement of sampling error for a statistic (e.g., proportion, mean, rate, count). In turn, the standard error can be used to calculate confidence intervals within which the true value for the population can reasonably be assumed to fall. For example, for any given statistic calculated from a sample survey, the value of that statistic will fall within a range of approximately plus or minus two times the standard error of that statistic in 95% of all possible samples of identical size and design.

NAIIS utilized a multi-stage stratified sample design, which required complex calculations to obtainsampling errors. The Taylor linearization method of variance estimation was used for survey estimates that are proportions, e.g., HIV prevalence. The Jackknife repeated replication method was used for variance estimation of more complex statistics such as rates, e.g., annual HIV incidence and counts such as the number of people living with HIV. The Taylor linearization method treats any percentage or average as a ratio estimate, , where y represents the total sample value