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;

United States US: Incidence of HIV: per 1,000 Uninfected Population data was reported at 0.110 Ratio in 2019. This stayed constant from the previous number of 0.110 Ratio for 2018. United States US: Incidence of HIV: per 1,000 Uninfected Population data is updated yearly, averaging 0.120 Ratio from Dec 2010 (Median) to 2019, with 10 observations. The data reached an all-time high of 0.130 Ratio in 2012 and a record low of 0.110 Ratio in 2019. United States US: Incidence of HIV: per 1,000 Uninfected Population 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. Number of new HIV infections among uninfected populations expressed per 1,000 uninfected population in the year before the period.;UNAIDS estimates.;Weighted average;This is the Sustainable Development Goal indicator 3.3.1 [https://unstats.un.org/sdgs/metadata/].

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.

Description: This data file contains household information about the people who usually live and slept there (the previous night) as per the time of the interview. Their age, sex, relationship to household head, marital status, race, language spoken, are included. The data set contains 300 variables and 10864 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 counseling 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. Clinical measurements Face-to-face interview

Abstract

The 2005 Guyana HIV/AIDS Indicator Survey (GAIS) is the first household-based, comprehensive survey on HIV/AIDS to be carried out in Guyana. The 2005 GAIS was implemented by the Guyana Responsible Parenthood Association (GRPA) for the Ministry of Health (MoH). ORC Macro of Calverton, Maryland provided technical assistance to the project through its contract with the U.S. Agency for International Development (USAID) under the MEASURE DHS program. Funding to cover technical assistance by ORC Macro and for local costs was provided in their entirety by USAID/Washington and USAID/Guyana.

The 2005 GAIS is a nationally representative sample survey of women and men age 15-49 initiated by MoH with the purpose of obtaining national baseline data for indicators on knowledge/awareness, attitudes, and behavior regarding HIV/AIDS. The survey data can be effectively used to calculate valuable indicators of the President’s Emergency Plan for AIDS Relief (PEPFAR), the Joint United Nations Program on HIV/AIDS (UNAIDS), the United Nations General Assembly Special Session (UNGASS), the United Nations Children Fund (UNICEF) Orphan and Vulnerable Children unit (OVC), and the World Health Organization (WHO), among others. The overall goal of the survey was to provide program managers and policymakers involved in HIV/AIDS programs with information needed to monitor and evaluate existing programs; and to effectively plan and implement future interventions, including resource mobilization and allocation, for combating the HIV/AIDS epidemic in Guyana.

Other objectives of the 2005 GAIS include the support of dissemination and utilization of the results in planning, managing and improving family planning and health services in the country; and enhancing the survey capabilities of the institutions involved in order to facilitate the implementation of surveys of this type in the future.

The 2005 GAIS sampled over 3,000 households and completed interviews with 2,425 eligible women and 1,875 eligible men. In addition to the data on HIV/AIDS indicators, data on the characteristics of households and its members, malaria, infant and child mortality, tuberculosis, fertility, and family planning were also collected.

Geographic coverage

National

Analysis unit

• Individuals;
• Households.

Kind of data

Sample survey data [ssd]

Sampling procedure

The primary objective of the 2005 GAIS is to provide estimates with acceptable precision for important population characteristics such as HIV/AIDS related knowledge, attitudes, and behavior. The population to be covered by the 2005 GAIS was defined as the universe of all women and men age 15-49 in Guyana.

The major domains to be distinguished in the tabulation of important characteristics for the eligible population are: • Guyana as a whole • The urban area and the rural area each as a separate major domain • Georgetown and the remainder urban areas.

Administratively, Guyana is divided into 10 major regions. For census purposes, each region is further subdivided in enumeration districts (EDs). Each ED is classified as either urban or rural. There is a list of EDs that contains the number of households and population for each ED from the 2002 census. The list of EDs is grouped by administrative units as townships. The available demarcated cartographic material for each ED from the last census makes an adequate sample frame for the 2005 GAIS.

The sampling design had two stages with enumeration districts (EDs) as the primary sampling units (PSUs) and households as the secondary sampling units (SSUs). The standard design for the GAIS called for the selection of 120 EDs. Twenty-five households were selected by systematic random sampling from a full list of households from each of the selected enumeration districts for a total of 3,000 households. All women and men 15-49 years of age in the sample households were eligible to be interviewed with the individual questionnaire.

The database for the recently completed 2002 Census was used as a sampling frame to select the sampling units. In the census frame, EDs are grouped by urban-rural location within the ten administrative regions and they are also ordered in each administrative unit in serpentine fashion. Therefore, this stratification and ordering will be also reflected in the 2005 GAIS sample.

Based on response rates from other surveys in Guyana, around 3,000 interviews of women and somewhat fewer of men expected to be completed in the 3,000 households selected.

Several allocation schemes were considered for the sample of clusters for each urban-rural domain. One option was to allocate clusters to urban and rural areas proportionally to the population in the area. According to the census, the urban population represents only 29 percent of the population of the country. In this case, around 35 clusters out of the 120 would have been allocated to the urban area. Options to obtain the best allocation by region were also examined. It should be emphasized that optimality is not guaranteed at the regional level but the power for analysis is increased in the urban area of Georgetown by departing from proportionality. Upon further analysis of the different options, the selection of an equal number of clusters in each major domain (60 urban and 60 rural) was recommended for the 2005 GAIS. As a result of the nonproportionalallocation of the number of EDs for the urban-rural and regional domains, the household sample for the 2005 GAIS is not a self-weighted sample.

The 2005 GAIS sample of households was selected using a stratified two-stage cluster design consisting of 120 clusters. The first stage-units (primary sampling units or PSUs) are the enumeration areas used for the 2002 Population and Housing Census. The number of EDs (clusters) in each domain area was calculated dividing its total allocated number of households by the sample take (25 households for selection per ED). In each major domain, clusters are selected systematically with probability proportional to size.

The sampling procedures are more fully described in "Guyana HIV/AIDS Indicator Survey 2005 - Final Report" pp.135-138.

Mode of data collection

Face-to-face [f2f]

Research instrument

Two types of questionnaires were used in the survey, namely: the Household Questionnaire and the Individual Questionnaire. The contents of these questionnaires were based on model questionnaires developed by the MEASURE DHS program. In consultation with USAID/Guyana, MoH, GRPA, and other government agencies and local organizations, the model questionnaires were modified to reflect issues relevant to HIV/AIDS in Guyana. The questionnaires were finalized around mid-May.

The Household Questionnaire was used to list all the usual members and visitors in the selected households. For each person listed, information was collected on sex, age, education, and relationship to the head of the household. An important purpose of the Household Questionnaire was to identify women and men who were eligible for the individual interview.

The Household Questionnaire also collected non-income proxy indicators about the household's dwelling unit, such as the source of water; type of toilet facilities; materials used for the floor, roof and walls of the house; and ownership of various durable goods and land. As part of the Malaria Module, questions were included on ownership and use of mosquito bednets.

The Individual Questionnaire was used to collect information from women and men age 15-49 years and covered the following topics: • Background characteristics (age, education, media exposure, employment, etc.) • Reproductive history (number of births and—for women—a birth history, birth registration, current pregnancy, and current family planning use) • Marriage and sexual activity • Husband’s background • Knowledge about HIV/AIDS and exposure to specific HIV-related mass media programs • Attitudes toward people living with HIV/AIDS • Knowledge and experience with HIV testing • Knowledge and symptoms of other sexually transmitted infections (STIs) • The malaria module and questions on tuberculosis

Cleaning operations

The processing of the GAIS questionnaires began in mid-July 2005, shortly after the beginning of fieldwork and during the first visit of the ORC Macro data processing specialist. Questionnaires for completed clusters (enumeration districts) were periodically submitted to GRPA offices in Georgetown, where they were edited by data processing personnel who had been trained specifically for this task. The concurrent processing of the data—standard for surveys participating in the DHS program—allowed GRPA to produce field-check tables to monitor response rates and other variables, and advise field teams of any problems that were detected during data entry. All data were entered twice, allowing 100 percent verification. Data processing, including data entry, data editing, and tabulations, was done using CSPro, a program developed by ORC Macro, the U.S. Bureau of Census, and SERPRO for processing surveys and censuses. The data entry and editing of the questionnaires was completed during a second visit by the ORC Macro specialist in mid-September. At this time, a clean data set was produced and basic tables with the basic HIV/AIDS indicators were run. The tables included in the current report were completed by the end of November 2005.

Response rate

• From a total of 3,055 households in the sample, 2,800 were occupied. Among these households, interviews were completed in 2,608, for a response rate of 93 percent. • A total of 2,776 eligible women were identified and

The Philippines reported about ****** HIV cases, an increase from the previous year. The number of reported HIV cases has gradually increased since 2012, aside from a significant dip in 2020. The state of HIV As the monthly average number of people newly diagnosed with HIV increases, the risk it poses threatens the lives of Filipinos. HIV is a sexually transmitted infection that attacks the body’s immune system, with more males being diagnosed than females. In 2022, the majority of people newly diagnosed with HIV were those between the age of 25 and 34 years, followed by those aged 15 and 24. There is still no cure for HIV and without treatment, it could lead to other severe illnesses such as tuberculosis and cancers such as lymphoma and Kaposi’s sarcoma. However, HIV is now a manageable chronic illness that can be treated with proper medication. What are the leading causes of death in the Philippines? Between January and September 2024, preliminary figures have shown that ischaemic heart disease was the leading cause of death in the Philippines. The prevalence of heart diseases in the nation has been closely attributed to the Filipino diet, which was described as having a high fat, high cholesterol, and high sodium content. In addition, acute respiratory infections and hypertension also registered the highest morbidity rate among leading diseases in the country in 2021.

Description: The child data of the SABSSM 2002 study include information from the children 12-14 years on various topics topics such as biographical information, knowledge and communication about HIV and AIDS, the child's home environment, care and protection, sexual experience and behaviour, circumcision, hospitalisation history and health status. The data set contains 420 variables and 998 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 counseling 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. Clinical measurements Face-to-face interview Focus group Observation South African population, 2 years and older from urban formal, urban informal, rural formal, rural informal settlements. This project used the HSRC's master sample (HSRC 2002). A master sample is defined as a selection, for the purpose of repeated community or household surveys, of a probability sample of census enumeration areas throughout South Africa that are representative of the country's provincial, settlement and racial diversity. The sampling frame that was used in the design of the master sample was the 2001 census Enumerator Areas (EAs) from Statistics South Africa (Stats SA). The target population for this study were all people in South Africa, excluding persons in so-called special institutions (e.g. hospitals, military camps, old age homes, schools and university hostels). The EAs were used as the Primary Sampling Units (PSUs). Although the 2001 census data are not yet available, it was decided to use the 2001 EAs for the master sample because the sampling units would remain relevant for future surveys conducted by the HSRC within five to ten years' time. In addition, the HSRC would soon have access to the most recent census statistics over this period for weighting of future survey results, including this study. The sample was designed with two main explicit strata, namely, provinces and the geography type (geotype) of the EA. In the 2001 census, the four geotypes are urban formal, urban informal, rural formal (including commercial farms) and tribal areas (i.e. the deep rural areas). In the formal urban areas, race was also used as a third stratification variable. What this means is that the Master Sample has been designed to allow reporting of results (i.e. reporting domain) at a provincial, geotype and race level. A reporting domain is defined as that domain at which estimates of a population characteristic or variable should be of an acceptable precision for the presentation of survey results. The census 2001 EA data provided by Stats SA for drawing the sample contained an estimate of the number of dwelling units (DUs) or visiting points (VPs). A visiting point is defined as a separate (non-vacant) residential stand, address, structure, and flat in a block of flats or homestead. The 2001 estimate of visiting points was used as the Measure of Size (MOS) in the drawing of the sample. The visiting point is the Secondary Sampling Unit (SSU) in each of the selected PSUs. In this study, all people in all the households resident at the visiting point were initially listed, after which the eligible individual was randomly selected in each of the following three age groups 2-14, 15-24 and 25 years and older. These individuals constituted the Ultimate Sampling Units (USUs) of this study. Having completed the sample design, the sample was drawn with 1 000 PSUs or EAs being selected throughout South Africa (see Figure 2). These PSUs were allocated to each of the explicit strata. With a view to obtaining an approximately self-weighting sample of visiting points (i.e. SSUs), (a) the EAs were drawn with probability proportional to the size of the EA using the 2001 estimate of the number of visiting points in the EA database as a measure of size (MOS) and (b) to draw an equal number of visiting points (i.e. SSUs) from each drawn EA. An acceptable precision of estimates per reporting domain requires that a sample of sufficient size be drawn from each of the reporting domains. Consequently, a cluster of 11 VP was systematically selected on the aerial photography produced for each of the EAs in the master sample. Since it is not possible to determine on an aerial photograph whether a 'dwelling unit' is indeed a residential structure or whether it was occupied (i.e. people sleeping there), it was decided to form clusters of 11 dwelling units per PSU, allowing on average for one invalid dwelling unit in the cluster of 11 dwelling units. Previous experience at Statistics SA indicated a sample size of 10 households per PSU to be very efficient, balancing cost and efficiency. Overall, a total of 14 450 potential participants composed of 4 001 children, 3 720 youths and 6 729 adults were selected for the survey and 13 518 (93.6%) were actually visited. A small proportion (6.4%) of potential respondents could not be approached due to logistic constraints that were unavoidable in a study of such magnitude. Among the 13 518 individuals who were selected and contacted for the survey, 9 963 (73.7%) persons agreed to be interviewed, and 8 840 (65.4%) agreed to also give a specimen for an HIV test. The sample was designed with the view to enable reporting of the results on province level, on geography type area and on race of the respondent. The total sample size was limited by financial constraints, but based on other HSRC experience in sample surveys it was decided to aim at obtaining a minimum of 1 200 households per race group. In fact, the aim was to obtain 1 200 Indian households, 1 800 coloured households, 2 200 white households and 4 800 African households, a total thus of 10 000 households. The number of respondents per household for the study was expected to vary between one and three (one respondent in each of the three age groups). A 70% response rate was assumed and a HIV+ prevalence rate of 20%. However, the total refusal and noncontact rate was much higher than expected. Nevertheless, all cases where the interview could have been done were included in the analysis.

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.

Updated 10/6/2022: In the Time/Distance analysis process, points that were found to have been included initially, but with no significant or year-round population were removed. The layer of removed points is also available for viewing. MCNA - Removed Population PointsThe Network Adequacy Standards Representative Population Points feature layer contains 97,694 points spread across California that were created from USPS postal delivery route data and US Census data. Each population point also contains the variables for Time and Distance Standards for the County that the point is within. These standards differ by County due to the County "type" which is based on the population density of the county. There are 5 county categories within California: Rural (<50 people/sq mile), Small (51-200 people/sq mile), Medium (201-599 people/sq mile), and Dense (>600 people/sq mile). The Time and Distance data is divided out by Provider Type, Adult and Pediatric separately, so that the Time or Distance analysis can be performed with greater detail. HospitalsOB/GYN SpecialtyAdult Cardiology/Interventional CardiologyAdult DermatologyAdult EndocrinologyAdult ENT/OtolaryngologyAdult GastroenterologyAdult General SurgeryAdult HematologyAdult HIV/AIDS/Infectious DiseaseAdult Mental Health Outpatient ServicesAdult NephrologyAdult NeurologyAdult OncologyAdult OphthalmologyAdult Orthopedic SurgeryAdult PCPAdult Physical Medicine and RehabilitationAdult PsychiatryAdult PulmonologyPediatric Cardiology/Interventional CardiologyPediatric DermatologyPediatric EndocrinologyPediatric ENT/OtolaryngologyPediatric GastroenterologyPediatric General SurgeryPediatric HematologyPediatric HIV/AIDS/Infectious DiseasePediatric Mental Health Outpatient ServicesPediatric NephrologyPediatric NeurologyPediatric OncologyPediatric OphthalmologyPediatric Orthopedic SurgeryPediatric PCPPediatric Physical Medicine and RehabilitationPediatric PsychiatryPediatric Pulmonology

Description: The guardian data of the SABSSM 2002 study cover information from the parents or care givers of children 2-11 years on matters ranging from biographical information of the child and parent/guardian, the child's home environment, care and protection, sources of information on HIV and AIDS, media impact and the health status of the child. The data set contains 380 variables and 2732 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 counseling 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. Clinical measurements Face-to-face interview Focus group Observation South African population, 2 years and older from urban formal, urban informal, rural formal, rural informal settlements. This project used the HSRC's master sample (HSRC 2002). A master sample is defined as a selection, for the purpose of repeated community or household surveys, of a probability sample of census enumeration areas throughout South Africa that are representative of the country's provincial, settlement and racial diversity. The sampling frame that was used in the design of the master sample was the 2001 census Enumerator Areas (EAs) from Statistics South Africa (Stats SA). The target population for this study were all people in South Africa, excluding persons in so-called special institutions (e.g. hospitals, military camps, old age homes, schools and university hostels). The EAs were used as the Primary Sampling Units (PSUs). Although the 2001 census data are not yet available, it was decided to use the 2001 EAs for the master sample because the sampling units would remain relevant for future surveys conducted by the HSRC within five to ten years' time. In addition, the HSRC would soon have access to the most recent census statistics over this period for weighting of future survey results, including this study. The sample was designed with two main explicit strata, namely, provinces and the geography type (geotype) of the EA. In the 2001 census, the four geotypes are urban formal, urban informal, rural formal (including commercial farms) and tribal areas (i.e. the deep rural areas). In the formal urban areas, race was also used as a third stratification variable. What this means is that the Master Sample has been designed to allow reporting of results (i.e. reporting domain) at a provincial, geotype and race level. A reporting domain is defined as that domain at which estimates of a population characteristic or variable should be of an acceptable precision for the presentation of survey results. The census 2001 EA data provided by Stats SA for drawing the sample contained an estimate of the number of dwelling units (DUs) or visiting points (VPs). A visiting point is defined as a separate (non-vacant) residential stand, address, structure, and flat in a block of flats or homestead. The 2001 estimate of visiting points was used as the Measure of Size (MOS) in the drawing of the sample. The visiting point is the Secondary Sampling Unit (SSU) in each of the selected PSUs. In this study, all people in all the households resident at the visiting point were initially listed, after which the eligible individual was randomly selected in each of the following three age groups 2-14, 15-24 and 25 years and older. These individuals constituted the Ultimate Sampling Units (USUs) of this study. Having completed the sample design, the sample was drawn with 1 000 PSUs or EAs being selected throughout South Africa (see Figure 2). These PSUs were allocated to each of the explicit strata. With a view to obtaining an approximately self-weighting sample of visiting points (i.e. SSUs), (a) the EAs were drawn with probability proportional to the size of the EA using the 2001 estimate of the number of visiting points in the EA database as a measure of size (MOS) and (b) to draw an equal number of visiting points (i.e. SSUs) from each drawn EA. An acceptable precision of estimates per reporting domain requires that a sample of sufficient size be drawn from each of the reporting domains. Consequently, a cluster of 11 VP was systematically selected on the aerial photography produced for each of the EAs in the master sample. Since it is not possible to determine on an aerial photograph whether a 'dwelling unit' is indeed a residential structure or whether it was occupied (i.e. people sleeping there), it was decided to form clusters of 11 dwelling units per PSU, allowing on average for one invalid dwelling unit in the cluster of 11 dwelling units. Previous experience at Statistics SA indicated a sample size of 10 households per PSU to be very efficient, balancing cost and efficiency. Overall, a total of 14 450 potential participants composed of 4 001 children, 3 720 youths and 6 729 adults were selected for the survey and 13 518 (93.6%) were actually visited. A small proportion (6.4%) of potential respondents could not be approached due to logistic constraints that were unavoidable in a study of such magnitude. Among the 13 518 individuals who were selected and contacted for the survey, 9 963 (73.7%) persons agreed to be interviewed, and 8 840 (65.4%) agreed to also give a specimen for an HIV test. The sample was designed with the view to enable reporting of the results on province level, on geography type area and on race of the respondent. The total sample size was limited by financial constraints, but based on other HSRC experience in sample surveys it was decided to aim at obtaining a minimum of 1 200 households per race group. In fact, the aim was to obtain 1 200 Indian households, 1 800 coloured households, 2 200 white households and 4 800 African households, a total thus of 10 000 households. The number of respondents per household for the study was expected to vary between one and three (one respondent in each of the three age groups). A 70% response rate was assumed and a HIV+ prevalence rate of 20%. However, the total refusal and noncontact rate was much higher than expected. Nevertheless, all cases where the interview could have been done were included in the analysis.

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. Clinical measurements Face-to-face interview Focus group Observation South African population, 2 years and older from urban formal, urban informal, rural formal, rural informal settlements. This project used the HSRC's master sample (HSRC 2002). A master sample is defined as a selection, for the purpose of repeated community or household surveys, of a probability sample of census enumeration areas throughout South Africa that are representative of the country's provincial, settlement and racial diversity. The sampling frame that was used in the design of the master sample was the 2001 census Enumerator Areas (EAs) from Statistics South Africa (Stats SA). The target population for this study were all people in South Africa, excluding persons in so-called special institutions (e.g. hospitals, military camps, old age homes, schools and university hostels). The EAs were used as the Primary Sampling Units (PSUs). Although the 2001 census data are not yet available, it was decided to use the 2001 EAs for the master sample because the sampling units would remain relevant for future surveys conducted by the HSRC within five to ten years' time. In addition, the HSRC would soon have access to the most recent census statistics over this period for weighting of future survey results, including this study. The sample was designed with two main explicit strata, namely, provinces and the geography type (geotype) of the EA. In the 2001 census, the four geotypes are urban formal, urban informal, rural formal (including commercial farms) and tribal areas (i.e. the deep rural areas). In the formal urban areas, race was also used as a third stratification variable. What this means is that the Master Sample has been designed to allow reporting of results (i.e. reporting domain) at a provincial, geotype and race level. A reporting domain is defined as that domain at which estimates of a population characteristic or variable should be of an acceptable precision for the presentation of survey results. The census 2001 EA data provided by Stats SA for drawing the sample contained an estimate of the number of dwelling units (DUs) or visiting points (VPs). A visiting point is defined as a separate (non-vacant) residential stand, address, structure, and flat in a block of flats or homestead. The 2001 estimate of visiting points was used as the Measure of Size (MOS) in the drawing of the sample. The visiting point is the Secondary Sampling Unit (SSU) in each of the selected PSUs. In this study, all people in all the households resident at the visiting point were initially listed, after which the eligible individual was randomly selected in each of the following three age groups 2-14, 15-24 and 25 years and older. These individuals constituted the Ultimate Sampling Units (USUs) of this study. Having completed the sample design, the sample was drawn with 1 000 PSUs or EAs being selected throughout South Africa. These PSUs were allocated to each of the explicit strata. With a view to obtaining an approximately self-weighting sample of visiting points (i.e. SSUs), (a) the EAs were drawn with probability proportional to the size of the EA using the 2001 estimate of the number of visiting points in the EA database as a measure of size (MOS) and (b) to draw an equal number of visiting points (i.e. SSUs) from each drawn EA. An acceptable precision of estimates per reporting domain requires that a sample of sufficient size be drawn from each of the reporting domains. Consequently, a cluster of 11 VP was systematically selected on the aerial photography produced for each of the EAs in the master sample. Since it is not possible to determine on an aerial photograph whether a 'dwelling unit' is indeed a residential structure or whether it was occupied (i.e. people sleeping there), it was decided to form clusters of 11 dwelling units per PSU, allowing on average for one invalid dwelling unit in the cluster of 11 dwelling units. Previous experience at Statistics SA indicated a sample size of 10 households per PSU to be very efficient, balancing cost and efficiency. Overall, a total of 14 450 potential participants composed of 4 001 children, 3 720 youths and 6 729 adults were selected for the survey and 13 518 (93.6%) were actually visited. A small proportion (6.4%) of potential respondents could not be approached due to logistic constraints that were unavoidable in a study of such magnitude. Among the 13 518 individuals who were selected and contacted for the survey, 9 963 (73.7%) persons agreed to be interviewed, and 8 840 (65.4%) agreed to also give a specimen for an HIV test. The sample was designed with the view to enable reporting of the results on province level, on geography type area and on race of the respondent. The total sample size was limited by financial constraints, but based on other HSRC experience in sample surveys it was decided to aim at obtaining a minimum of 1 200 households per race group. In fact, the aim was to obtain 1 200 Indian households, 1 800 coloured households, 2 200 white households and 4 800 African households, a total thus of 10 000 households. The number of respondents per household for the study was expected to vary between one and three (one respondent in each of the three age groups). A 70% response rate was assumed and a HIV+ prevalence rate of 20%. However, the total refusal and non-contact rate was much higher than expected. Nevertheless, all cases where the interview could have been done were included in the analysis.

Context

HealthStats compiles an extensive array of health, nutrition, and population statistics gleaned from a diverse array of global sources. Encompassing themes ranging from population dynamics to health financing and disease prevalence, this repository covers a broad spectrum of indicators, including immunization rates, infectious diseases, HIV/AIDS, and population projections. Additionally, HealthStats presents nuanced statistics categorized by wealth quintiles, offering a comprehensive view of societal disparities.

Content

Within this dataset, a compendium of 470 indicators sheds light on critical metrics such as immunization rates, malnutrition prevalence, and vitamin A supplementation across 266 countries worldwide. Spanning a timeframe from 1960 to 2022, this data collection encapsulates yearly statistics, providing a comprehensive historical perspective on health, nutrition, and population dynamics.

Dataset Structure

This dataset (health_nutrition_population_statistics.csv) covering from 1960 up to 2022 includes the following columns:

Questions for Exploration

• Are there unexpected correlations or shifts in indicators that warrant inclusion for a more holistic understanding?
• Is there a discernible relationship between condom use and HIV transmission rates among newborns, and how have these trends evolved over time?
• Identifying countries with the highest iodized salt consumption and tracking changes over time could reveal intriguing patterns. Are there other indicators that correlate significantly with this consumption trend?

Acknowledgment

The primary dataset was retrieved from the World Bank's Data Catalog. I would like to express our sincere appreciation to the World Bank team for providing the core data used in this dataset.

© Image credit: Freepik

United States US: Newly Infected with HIV: Children: Aged 0-14 data was reported at 200.000 Number in 2019. This stayed constant from the previous number of 200.000 Number for 2018. United States US: Newly Infected with HIV: Children: Aged 0-14 data is updated yearly, averaging 200.000 Number from Dec 2010 (Median) to 2019, with 10 observations. The data reached an all-time high of 500.000 Number in 2012 and a record low of 200.000 Number in 2019. United States US: Newly Infected with HIV: Children: Aged 0-14 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. Number of children (ages 0-14) newly infected with HIV.;UNAIDS estimates.;;This indicator is related to Sustainable Development Goal 3.3.1 [https://unstats.un.org/sdgs/metadata/].

Mexico MX: Prevalence of HIV: Male: % Aged 15-24 data was reported at 0.200 % in 2017. This stayed constant from the previous number of 0.200 % for 2016. Mexico MX: Prevalence of HIV: Male: % Aged 15-24 data is updated yearly, averaging 0.200 % from Dec 1990 (Median) to 2017, with 28 observations. The data reached an all-time high of 0.200 % in 2017 and a record low of 0.100 % in 2009. Mexico MX: Prevalence of HIV: Male: % Aged 15-24 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Mexico – Table MX.World Bank.WDI: Health Statistics. Prevalence of HIV, male is the percentage of males who are infected with HIV. Youth rates are as a percentage of the relevant age group.; ; UNAIDS estimates.; Weighted average; In many developing countries most new infections occur in young adults, with young women being especially vulnerable.

The Rio Grande Valley (RGV) in South Texas has one of the highest prevalence of obesity and type 2 diabetes (T2D) in the United States (US). We report for the first time the T2D prevalence in persons with HIV (PWH) in the RGV and the interrelationship between T2D, cardiometabolic risk factors, HIV-related indices, and antiretroviral therapies (ART). The PWH in this study received medical care at Valley AIDS Council (VAC) clinic sites located in Harlingen and McAllen, Texas. Henceforth, this cohort will be referred to as Valley AIDS Council Cohort (VACC). Cross-sectional analyses were conducted using retrospective data obtained from 1,827 registries. It included demographic and anthropometric variables, cardiometabolic traits, and HIV-related virological and immunological indices. For descriptive statistics, we used mean values of the quantitative variables from unbalanced visits across 20 months. Robust regression methods were used to determine the associations. For comparisons, we used cardiometabolic trait data obtained from HIV-uninfected San Antonio Mexican American Family Studies (SAMAFS; N = 2,498), and the Mexican American population in the National Health and Nutrition Examination Survey (HHANES; N = 5,989). The prevalence of T2D in VACC was 51% compared to 27% in SAMAFS and 19% in HHANES, respectively. The PWH with T2D in VACC were younger (4.7 years) and had lower BMI (BMI 2.43 units less) when compared to SAMAFS individuals. In contrast, VACC individuals had increased blood pressure and dyslipidemia. The increased T2D prevalence in VACC was independent of BMI. Within the VACC, ART was associated with viral load and CD4+ T cell counts but not with metabolic dysfunction. Notably, we found that individuals with any INSTI combination had higher T2D risk: OR 2.08 (95%CI 1.67, 2.6; p < 0.001). In summary, our results suggest that VACC individuals may develop T2D at younger ages independent of obesity. The high burden of T2D in these individuals necessitates rigorously designed longitudinal studies to draw potential causal inferences and develop better treatment regimens.

Description: This data set has the statistics of the FETcolleges and public schools in South Africa addressing human resources regarding educators and student educators. It also addresses staff loss and relative wealth ranking. There are 1508 records and 119 variables. Abstract: The study on the impact of HIV/AIDS on educators in South African public schools build on other studies conducted on HIV/AIDS epidemic. In response to HIV/AIDS resolutions of the education convention of 2002, this study sought for deeper understanding of the impact of HIV/AIDS on the education sector and effectiveness of policies and programmes in addressing the HIV/AIDS epidemic in South Africa. The process of planning for human resources in the teaching profession is crucial to the supply and demand of sufficiently qualified educators. Understanding of drivers of the HIV/AIDS epidemic for educators, direction the epidemic takes and precise impact it has on educators is essential. The HIV/AIDS epidemic complicated prediction of teacher attrition and mortality. For this reason, the South African Education Labour Relations Council (ELRC) commissioned the HSRC-led consortium to undertake this study. The study aimed at gathering information to assist the government and unions in the ELRC in planning educator supply/demand at national, provincial and district level. The specific objectives were to determine: the prevalence of HIV, drivers of the epidemic, the most affected areas, mortality rate, attrition rate, policies currently in place, trend in enrolment of learners and the impact of the life skills programme on HIV/AIDS, amongst educators in public schools in South Africa. The key findings were: high prevalence of HIV amongst the educators and various drivers of HIV/AIDS epidemic namely behavioural, knowledge deficit, lack of self-efficacy skills, migratory practices, gender, and alcohol misuse. In addition, chronic conditions such as hypertension, stomach ulcers, arthritis and diabetes were common. High proportion of educators would be lost due to job dissatisfaction, job stress and low morale. The health status and working conditions of the educators need to be improved in order to minimize the effect of HIV/AIDS. The ELRC is best suited to facilitate the implementation of the findings made in this study. Clinical measurements Face-to-face interview Public educational institutions and FET colleges in South Africa. A stratified one-stage cluster sample was designed. The explicit strata were provinces, education districts, type of school (i.e. primary versus secondary) and school size. Within each educational district, schools were stratified into 'primary' and 'secondary' schools. Mixed schools (e.g. schools with grades 1 to 9 or 10) were grouped into one of the above categories according to the numbers of pupils in grades 1 to 7 and in grades 8+. The primary sampling unit were the school and the ultimate sampling unit were education personnel. With a view to obtaining a self-weighting sample within explicit strata, schools were drawn 'epsem' (equal probability selection method). The sample frame for the project was the School Register of Needs (2000) data from the national Department of Education (DoE). Eligible sample consisted of 1 766 schools with 24 200 state-paid educators. Informed consent was obtained for those who agreed to participate in the interview and provide a specimen for HIV testing. Pilot study was carried out to test the questionnaire, administration and HIV testing. Registered (South African Nursing Council) nurses were employed conduct interviews and collect either a blood specimen or an oral fluid (Orasure) specimen. Four hundred and thirty six trained nurses carried out the fieldwork. Directors of Education in all provinces selected co-ordinators whose role was to inform about the study. HSRC used Masters and PHD research interns as co-ordinators to make appointments at schools and addressing educators with the aid of the District officers who promoted study participation. Fieldworkers were supported by National field manager, with a separate project manager who managed project progress. School visits times were adapted to avoid disruption of teaching time.

Artificial Intelligence (AI) in HIV and AIDS Market Outlook

The global market size for Artificial Intelligence (AI) in HIV and AIDS was valued at approximately $1.2 billion in 2023 and is projected to reach around $5.8 billion by 2032, growing at a compound annual growth rate (CAGR) of 19.1%. The primary growth factor for this market is the increasing prevalence of HIV and AIDS worldwide, which necessitates more efficient and effective methods for diagnosis, treatment, and patient management. Other contributing factors include advancements in AI technology and the growing integration of AI solutions in healthcare systems globally.

The market growth is significantly driven by the need for improved diagnostic tools. Traditional methods for diagnosing and monitoring HIV are often time-consuming and may not be entirely accurate. AI technologies, particularly those involving machine learning and deep learning, offer the potential for higher accuracy and speed, leading to early detection and better patient outcomes. For instance, AI algorithms can analyze large datasets, identifying patterns and anomalies that might be missed by human practitioners. This capability is crucial for both early diagnosis and ongoing management of HIV.

Another key factor driving market expansion is the continuous evolution in treatment methodologies. AI has shown promise in optimizing treatment plans tailored to individual patients, considering their unique genetic makeup, lifestyle, and disease progression. Personalized medicine, supported by AI, can significantly enhance the efficacy of antiretroviral therapies (ARTs), minimizing side effects and improving patient adherence to treatment regimens. The ability of AI systems to predict how a patient might react to different treatment options can revolutionize HIV care, making it more precise and effective.

Patient management is also seeing transformative changes due to AI integration. Enhanced patient monitoring systems that utilize AI can track health metrics in real-time, providing alerts for any concerning changes. This real-time data collection and analysis can facilitate proactive healthcare measures, reducing hospital readmissions and improving overall patient quality of life. AI-driven mobile health applications are becoming more prevalent, offering patients better tools to manage their condition, adhere to treatment schedules, and maintain consistent communication with healthcare providers.

Regionally, North America remains a dominant player in the AI in HIV and AIDS market, driven by advanced healthcare infrastructure, substantial funding for AI research, and high adoption rates of new technologies. Meanwhile, Asia Pacific is expected to witness the fastest growth, attributed to rising awareness about HIV, increasing healthcare expenditure, and substantial technological advancements. Collaboration between governments and private entities in these regions is fostering an environment conducive to AI-driven healthcare innovations.

Component Analysis

The AI in HIV and AIDS market is segmented by components into software, hardware, and services. The software segment is expected to hold the largest market share due to the rapid development of AI algorithms and platforms specifically designed for healthcare applications. AI software solutions can analyze complex medical data, assisting in diagnosis, treatment planning, and patient management. The proliferation of cloud-based AI software is also contributing to its dominance, as it offers scalability, cost-effectiveness, and ease of access.

Hardware is another critical component, albeit with a smaller market share compared to software. This segment includes specialized computing systems, servers, and data storage devices required to run AI algorithms efficiently. The growing demand for high-performance hardware solutions that can handle extensive datasets and complex computations is driving advancements in this segment. Innovations in hardware, such as the development of AI-specific processors, are further enhancing the capabilities of AI systems in healthcare settings.

The services segment encompasses a wide range of offerings, including consulting, integration, maintenance, and support services. As healthcare providers increasingly adopt AI solutions, the need for specialized services to implement and optimize these technologies is growing. Consulting services, in particu

The 2006-07 Namibia Demographic and Health Survey (NDHS) is a nationally representative survey of 9,804 women age 15-49 and 3,915 men age 15-49. The 2006-07 NDHS is the third comprehensive survey conducted in Namibia as part of the Demographic and Health Surveys (DHS) programme. The data are intended to provide programme managers and policymakers with detailed information on levels and trends in fertility; nuptiality; sexual activity; fertility preferences; awareness and use of family planning methods; breastfeeding practices; nutritional status of mothers and young children; early childhood mortality, adult and maternal mortality; maternal and child health; and awareness and behaviour regarding HIV/AIDS and other sexually transmitted infections. The 2006-07 NDHS is the first NDHS survey to collect information on malaria prevention and treatment. The 2006-07 NDHS has been a large-scale research project. Twenty-eight field teams interviewed about 9,200 households, 9,800 women and 3,900 men age 15-49. The interviews were conducted between November 2006 and March 2007. The survey covered about 500 primary sampling units in all regions. The 2006-07 Namibia Demographic and Health Survey is designed to: Determine key demographic rates, particularly fertility, under-five mortality, and adult mortality rates; Investigate the direct and indirect factors that determine the level and trends of fertility; Measure the level of contraceptive knowledge and practice among women and men by method; Determine immunisation coverage and prevalence and treatment of diarrhoea and acute respiratory diseases among children under five; identify infant and young child feeding practices and assess the nutritional status of children age 6-59 months and women age 15-49 years; Assess knowledge and attitudes of women and men regarding sexually transmitted infections and HIV/AIDS, and evaluate patterns of recent behaviour regarding condom use; Identify behaviours that protect or predispose people to HIV infection and examine social, economic, and cultural determinants of HIV; Determine the proportion of households with orphans and vulnerable children (OVCs); and Determine the proportion of households with sick people taken care of at household level. The 2006-07 NDHS is part of the worldwide Demographic and Health Surveys (DHS) programme funded by the United States Agency for International Development (USAID). DHS surveys are designed to collect data on fertility, family planning, and maternal and child health; assist countries in conducting periodic surveys to monitor changes in population, health, and nutrition; and provide an international database that can be used by researchers investigating topics related to population, health, and nutrition. MAIN RESULTS Fertility : The survey results show that Namibia has experienced a decline in fertility of almost two births over the past 15 years, with the fertility rate falling from 5.4 births per woman in 19901992 to 3.6 births in 2005-07. Family planning : Knowledge of family planning in Namibia has been nearly universal since 1992. In the 2006-07 NDHS, 98 percent of all women reported knowing about a contraceptive method. Male condoms, injectables, and the pill are the most widely known methods. Child health : Data from the 2006-07 NDHS indicate that the under-five mortality rate in Namibia is 69 deaths per 1,000 live births (based on the five-year period preceding the survey). Maternal health : In Namibia, almost all women who had a live birth in the five years preceding the survey received antenatal care from health professionals (95 percent): 16 percent from a doctor and 79 percent from a nurse or midwife. Only 4 percent of mothers did not receive any antenatal care. Breastfeeding and nutrition : Breastfeeding is common in Namibia, with 94 percent of children breastfed at some point during childhood. The median breastfeeding duration in Namibia is 16.8 months. Malaria: One in four households interviewed in the survey has at least one mosquito net, and most of these households have a net that has been treated at some time with an insecticide (20 percent). HIV/AIDS and STIS : Knowledge of HIV and AIDS is universal in Namibia; 99 percent of women age 15-49 and 99 percent of men age 15-49 have heard of AIDS. Orphans and vulnerable children : One-quarter of Namibian children under age 18 in the households sampled for the 2006-07 NDHS live with both parents, while one in three does not live with either parent. Seventeen percent of children under age 18 are orphaned, that is, one or both parents is dead. Access to health facilities : Households interviewed in the 2006-07 NDHS were asked to name the nearest government health facility, the mode of transport they would use to visit the facility, and how long it takes to get to the facility using the transport of choice.

The 2004 Malawi Demographic and Health Survey (MDHS) is a nationally representative survey of 11,698 women age 1549 and 3,261 men age 15-54. The main purpose of the 2004 MDHS is to provide policymakers and programme managers with detailed information on fertility, family planning, childhood and adult mortality, maternal and child health, as well as knowledge of and attitudes related to HIV/AIDS and other sexually transmitted infections (STIs). The 2004 MDHS is designed to provide data to monitor the population and health situation in Malawi as a followup of the 1992 and 2000 MDHS surveys, and the 1996 Malawi Knowledge, Attitudes, and Practices in Health Survey. New features of the 2004 MDHS include the collection of information on use of mosquito nets, domestic violence, anaemia testing of women and children under 5, and HIV testing of adults. The 2004 MDHS survey was implemented by the National Statistical Office (NSO). The Ministry of Health and Population, the National AIDS Commission (NAC), the National Economic Council, and the Ministry of Gender contributed to the development of the questionnaires for the survey. Most of the funds for the local costs of the survey were provided by multiple donors through the NAC. The United States Agency for International Development (USAID) provided additional funds for the technical assistance through ORC Macro. The Department for International Development (DfID) of the British Government, the United Nations Children's Fund (UNICEF), and the United Nations Population Fund (UNFPA) also provided funds for the survey. The Centers of Disease Control and Prevention provided technical assistance in HIV testing. The survey used a two-stage sample based on the 1998 Census of Population and Housing and was designed to produce estimates for key indicators for ten large districts in addition to estimates for national, regional, and urban-rural domains. Fieldwork for the 2004 MDHS was carried out by 22 mobile interviewing teams. Data collection commenced on 4 October 2004 and was completed on 31 January 2005. The principal aim of the 2004 MDHS project was to provide up-to-date information on fertility and childhood mortality levels, nuptiality, fertility preferences, awareness and use of family planning methods, use of maternal and child health services, and knowledge and behaviours related to HIV/AIDS and other sexually transmitted infections. It was designed as a follow-on to the 2000 MDHS survey, a national-level survey of similar scope. The 2004 MDHS survey, unlike the 2000 MDHS, collected blood samples which were later tested for HIV in order to estimate HIV prevalence in Malawi. In broad terms, the 2004 MDHS survey aimed to: Assess trends in Malawi's demographic indicators, principally fertility and mortality Assist in the monitoring and evaluation of Malawi's health, population, and nutrition programmes Advance survey methodology in Malawi and contribute to national and international databases Provide national-level estimates of HIV prevalence for women age 15-49 and men age 15-54. In more specific terms, the 2004 MDHS survey was designed to: Provide data on the family planning and fertility behaviour of the Malawian population and thereby enable policymakers to evaluate and enhance family planning initiatives in the country Measure changes in fertility and contraceptive prevalence and analyse the factors that affect these changes, such as marriage patterns, desire for children, availability of contraception, breastfeeding habits, and important social and economic factors Examine basic indicators of maternal and child health and welfare in Malawi, including nutritional status, use of antenatal and maternity services, treatment of recent episodes of childhood illness, and use of immunisation services. Particular emphasis was placed on malaria programmes, including malaria prevention activities and treatment of episodes of fever. Provide levels and patterns of knowledge and behaviour related to the prevention of HIV/AIDS and other sexually transmitted infections Provide national estimates of HIV prevalence Measure the level of infant and adult mortality including maternal mortality at the national level Assess the status of women in the country. MAIN FINDINGS Fertility Fertility Levels and Trends. While there has been a significant decline in fertility in the past two decades from 7.6 children in the early 1980s to 6.0 children per woman in the early 2000s, compared with selected countries in Eastern and Southern Africa, such as Zambia, Tanzania, Mozambique, Kenya, and Uganda, the total fertility rate (TFR) in Malawi is high, lower only than Uganda (6.9). Family planning Knowledge of Contraception. Knowledge of family planning is nearly universal, with 97 percent of women age 15-49 and 97 percent of men age 15-54 knowing at least one modern method of family planning. The most widely known modern methods of contraception among all women are injectables (93 percent), the pill and male condom (90 percent each), and female sterilisation (83 percent). Maternal health Antenatal Care. There has been little change in the coverage of antenatal care (ANC) from a medical professional since 2000 (93 percent in 2004 compared with 91 percent in 2000). Most women receive ANC from a nurse or a midwife (82 percent), although 10 percent go to a doctor or a clinical officer. A small proportion (2 percent) receives ANC from a traditional birth attendant, and 5 percent do not receive any ANC. Only 8 percent of women initiated ANC before the fourth month of pregnancy, a marginal increase from 7 percent in the 2000 MDHS. Adult and Maternal Mortality. Comparison of data from the 2000 and 2004 MDHS surveys indicates that mortality for both women and men has remained at the same levels since 1997 (11-12 deaths per 1,000). Child health Childhood Mortality. Data from the 2004 MDHS show that for the 2000-2004 period, the infant mortality rate is 76 per 1,000 live births, child mortality is 62 per 1,000, and the under-five mortality rate is 133 per 1,000 live births. Nutrition Breastfeeding Practices. Breastfeeding is nearly universal in Malawi. Ninety-eight percent of children are breastfed for some period of time. The median duration of breastfeeding in Malawi in 2004 is 23.2 months, one month shorter than in 2000. HIV/AIDS Awareness of AIDS. Knowledge of AIDS among women and men in Malawi is almost universal. This is true across age group, urban-rural residence, marital status, wealth index, and education. Nearly half of women and six in ten men can identify the two most common misconceptions about the transmission of HIV-HIV can be transmitted by mosquito bites, and HIV can be transmitted by supernatural means-and know that a healthy-looking person can have the AIDS virus.