As of 2023, South Africa was the country with the highest number of people living with HIV in Africa. At that time, around 7.7 million people in South Africa were HIV positive. In Mozambique, the country with the second-highest number of HIV-positive people in Africa, around 2.4 million people were living with HIV. Which country in Africa has the highest prevalence of HIV? Although South Africa has the highest total number of people living with HIV in Africa, it does not have the highest prevalence of HIV on the continent. Eswatini currently has the highest prevalence of HIV in Africa and worldwide, with almost 26 percent of the population living with HIV. South Africa has the third-highest prevalence, with around 18 percent of the population HIV positive. Eswatini also has the highest rate of new HIV infections per 1,000 population worldwide, followed by Lesotho and South Africa. However, South Africa had the highest total number of new HIV infections in 2023, with around 150,000 people newly infected with HIV that year. Deaths from HIV in Africa Thanks to advances in treatment and awareness, HIV/AIDS no longer contributes to a significant amount of death in many countries. However, the disease is still the fourth leading cause of death in Africa, accounting for around 5.6 percent of all deaths. In 2023, South Africa and Nigeria were the countries with the highest number of AIDS-related deaths worldwide with 50,000 and 45,000 such deaths, respectively. Although not every country in the leading 25 for AIDS-related deaths is found in Africa, African countries account for the majority of countries on the list. Fortunately, HIV treatment has become more accessible in Africa over the years and now up to 95 percent of people living with HIV in Eswatini are receiving antiretroviral therapy (ART). Access to ART does vary from country to country, however, with around 77 percent of people who are HIV positive in South Africa receiving ART, and only 31 percent in the Congo.

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

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

In 2024, in South Africa, there were around 3.1 HIV newly infected persons per every 1,000 inhabitants. This statistic depicts the countries with the highest incidence rates of new HIV infections worldwide as of 2024.

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

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

Abstract

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

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

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

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

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

Geographic coverage

National coverage

Analysis unit

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

Kind of data

Sample survey data [ssd]

Sampling procedure

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

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

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

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

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

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

Mode of data collection

Face-to-face [f2f]

Research instrument

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

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

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

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

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

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

Cleaning operations

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

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

Response rate

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

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

Sampling error

Abstract

More than two decades after its identification, acquired immune deficiency syndrome (AIDS) has become far more widespread and devastating than initially predicted. It affects men, women and children in all parts of the World. In most heavily affected countries, efforts are being made to prevent the spread of the disease (UNAIDS - 2001). But despite such efforts, huge challenges remain. Millions of young African women remain dangerously ignorant about HIV/AIDS. According to UNICEF, more than 70% of adolescent girls (aged 15 - 19) in Somalia and more than 40% in Guinea Bissau and Sierra Leone, have never heard of AIDS. In countries such as Kenya and Tanzania, more than 40% of adolescent girls harbour serious misconceptions about how the virus in transmitted (UNAIDS - 2001). The vast majority of Africans living with HIV do not know they have acquired the virus. One study has found that 50% of adult Tanzanian women know where they could be tested for HIV, yet only 6% have been tested. In Zimbabwe, only 11% of adult women have been tested for the virus. Moreover, many people who agree to be tested prefer not to return and discover the outcome of those tests. A study in Abidjan, Côte d'Ivoire, shows that 80% of pregnant women who agree to undergo a HIV test return to collect their results. But of those who discover they are living with the virus, less than 50% return to receive drug treatment for the prevention of mother-to-child transmission of the virus (UNAIDS - 2001). The key objective of the survey was to ascertain adolescents HIV/AIDS knowledge, attitude and practice, determine their access to the media in so far as getting vital information on HIV/AIDS, and ascertain their acceptance and credibility of the information they receive. The responses were to be analyzed by differentials of age, sex and spatial variations. The survey results will be presented to decision-makers for strategies and interventions that will help to significantly reduce the spread of HIV/AIDS in Sierra Leone.

Geographic coverage

The sample was designed to provide estimates of the indicators at the national level,for rural and urban areas from four administrative districts of the country,four Internally Displaced Persons (IDPs) camps one from each region and a category of people with no fixed abode, the floating population.

Analysis unit

Adolescents aged 12-21 years

Universe

The 2001 Adolescents' HIV/AIDS Knowledge, Attitude and Practices (KAP) Survey covered adolescents aged 12-21 years in both rural and urban areas from four administrative districts of the country; the Western Area in the West, Port Loko district in the Northern region, Bo district in the Southern region and Kenema district in the Eastern region. Data was also collected from adolescents in four Internally Displaced Persons (IDPs) camps one from each region and a category of people with no fixed abode, the floating population.

Kind of data

Sample survey data [ssd]

Sampling procedure

The sampling unit of the survey is the household. The recently updated sampling frame recommended by the Central Statistics Office (CSO), used in recent surveys, was used for this survey. The Central Statistics Office has a list of Enumeration Areas (EAs) that covers the entire country. The EAs served as clusters and the households as sampling units.

The strata to be used in the sampling process are derived from the administrative structures of the country with special reference to the following administrative areas: Western Area in the West, Port Loko district in the North, Bo district in the South, and Kenema district in the East.

First stage of sampling

The list of EAs were ordered and stratified according to the following variables: location (rural/urban), District, Chiefdom, and Population size. In each of the four regions, one displaced camp was selected at random and added to the list of EAs in the area of existence. About 5% of the floating population was also targeted.

Second stage of sampling

In the second stage of sampling, the EAs were classified as urban and rural, and listed accordingly for each district. The actual number of EAs selected, for each district, within the urban/rural areas was proportional to the population sizes of these urban/rural areas.

An every nth systematic sampling was used to select one hundred and forty (140) EAs all in all. The number of urban and rural EAs selected in the sample are listed in Appendix 1

Third stage of sampling

In each of the EAs chosen in each district a locality was randomly selected and twenty (20) households in turn randomly chosen from this locality. In the few cases where the chosen locality had less than the required number of twenty (20) households, locality was then immediately replaced by a bigger one that was randomly selected from the same EA.

For the purpose of cost reduction and efficiency, the sample design just described is simpler and more convenient than the more tedious method of first dividing each EA into equal segments of twenty (20) households and thereafter, selecting at random one segment from the EA.

The choice of either sampling design is a matter of preference, but in any case, the over all conclusions remain unchanged.

One adolescent (alternating between male and female), chosen at random was interviewed in each household. In households where large extended families or groups of people live together in different units within the same compound, the recommended procedure was to randomly choose a study subject from among those found in a given unit and complete the interview for only that respondent.

The list of EAs and the corresponding localities from which the twenty (20) households were chosen are given in Appendix II.

The population of each IDP camp was ascertained from the UNOCHA database of IDP populations. The database is updated monthly, and considered to be reasonably accurate. One displaced camp was randomly selected in each district and hundred (100) individuals interviewed in the selected camp.

For the floating population, two hundred (200) individuals (50 per district) were targeted and interviewed.

The list of the chosen displaced camps is also given in Appendix II

Sample size

Decisions regarding sample size were made based on a number of factors that included;

(i) The probability of making Type 1 error that the survey was willing to accept. This probability “r” generally set at 0.05 (or 5%), is the probability that the true population value for a given indicator might fall outside of confidence limits (in this case the 95% confidence limit), that surround the estimate of the indicator;

(ii) The design effect (or deff) of the survey. This provides a correction for the loss of sampling efficiency resulting from the use of a more complex (cluster) sampling design, instead of simple random sampling. The default value of 2 is commonly used. Assuming that cluster sample sizes can be kept moderately small, the use of a standard value of deff = 2.0 should adequately compensate for the use of cluster sampling in most cases;

(iii) The average number of people per household (nh). Available data suggest that the average household size in rural areas of Sierra Leone was seven (7), whilst in urban areas it was approximately six (6). An average value of nh = 6.5 was accepted;

(iv) The estimated non-response rate (nr) was 10% and 1.1 was the factor necessary to raise the sample size by 10% for non-response;

(vi) The desired precision “d” of the estimate of key variable, set at d = 0.05;

(vii) the proportion “p” of the total population that the target population group 12 - 21 years comprise; set at p = 0.2 (or about 20%); and

(viii) the predicted or anticipated prevalence for the key indicator, set at v = 0.01 (or 1%). The formula used in estimating the sample size is given in Appendix III.

Mode of data collection

Face-to-face [f2f]

Research instrument

An internationally tested structured questionnaire was developed and used for this study in English. The questionnaire and modules are provided as external resources.

Cleaning operations

Data coding, entry and analysis was carried out at the Central Statistics Office in Freetown. Microsoft Access was used for Data entry and with SPSS to make the data analysis.

Response rate

Response rate was 90%

In 2024, Brazil was the Latin American country with the highest number of people living with HIV. That year, approximately *********** patients were living with this condition in the South American country. Panama followed with an estimate of around ******* people living with HIV.

Bolivia BO: Net Official Flows from UN Agencies: UNFPA data was reported at 1.969 USD mn in 2022. This records an increase from the previous number of 1.873 USD mn for 2021. Bolivia BO: Net Official Flows from UN Agencies: UNFPA data is updated yearly, averaging 1.180 USD mn from Dec 1977 (Median) to 2022, with 44 observations. The data reached an all-time high of 3.200 USD mn in 2002 and a record low of 0.080 USD mn in 1987. Bolivia BO: Net Official Flows from UN Agencies: UNFPA data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Bolivia – Table BO.World Bank.WDI: Defense and Official Development Assistance. Net official flows from UN agencies are the net disbursements of total official flows from the UN agencies. Total official flows are the sum of Official Development Assistance (ODA) or official aid and Other Official Flows (OOF) and represent the total disbursements by the official sector at large to the recipient country. Net disbursements are gross disbursements of grants and loans minus repayments of principal on earlier loans. ODA consists of loans made on concessional terms (with a grant element of at least 25 percent, calculated at a rate of discount of 10 percent) and grants made to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. Official aid refers to aid flows from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. OOF are transactions by the official sector whose main objective is other than development-motivated, or, if development-motivated, whose grant element is below the 25 per cent threshold which would make them eligible to be recorded as ODA. The main classes of transactions included here are official export credits, official sector equity and portfolio investment, and debt reorganization undertaken by the official sector at nonconcessional terms (irrespective of the nature or the identity of the original creditor). UN agencies are United Nations includes the United Nations Children’s Fund (UNICEF), United Nations Relief and Works Agency for Palestine Refugees in the Near East (UNRWA), World Food Programme (WFP), International Fund for Agricultural Development (IFAD), United Nations Development Programme(UNDP), United Nations Population Fund (UNFPA), United Nations Refugee Agency (UNHCR), Joint United Nations Programme on HIV/AIDS (UNAIDS), United Nations Regular Programme for Technical Assistance (UNTA), United Nations Peacebuilding Fund (UNPBF), International Atomic Energy Agency (IAEA), World Health Organization (WHO), United Nations Economic Commission for Europe (UNECE), Food and Agriculture Organization of the United Nations (FAO), International Labour Organization (ILO), United Nations Environment Programme (UNEP), World Tourism Organization (UNWTO), United Nations Institute for Disarmament Research (UNIDIR), United Nations Capital Development Fund (UNCDF), WHO-Strategic Preparedness and Response Plan (SPRP), United Nations Women (UNWOMEN), Covid-19 Response and Recovery Multi-Partner Trust Fund (UNCOVID), Joint Sustainable Development Goals Fund (SDGFUND), Central Emergency Response Fund (CERF), WTO-International Trade Centre (WTO-ITC), United National Conference on Trade and Development (UNCTAD), and United Nations Industrial Development Organization (UNIDO). Data are in current U.S. dollars.;Development Assistance Committee of the Organisation for Economic Co-operation and Development, Geographical Distribution of Financial Flows to Developing Countries, Development Co-operation Report, and International Development Statistics database. Data are available online at: https://data-explorer.oecd.org/.;Sum;

Abstract

The primary objectives of the 2007-08 THMIS survey were to provide up-to-date information on the prevalence of HIV infection among Tanzanian adults, and the prevalence of malaria infection and anaemia among children under age five years. The findings will be used to evaluate ongoing programmes and to develop new health strategies. Where appropriate, the findings from the 2007-08 THMIS are compared with those from the 2003-04 Tanzania HIV/AIDS Indicator Survey (THIS). The findings of these two surveys are expected to complement the sentinel surveillance system undertaken by the Ministry of Health and Social Welfare under its National AIDS Control Programme (NACP). The THMIS also provides updated estimates of selected basic demographic and health indicators covered in previous surveys, including the 1991-92 Tanzania Demographic and Health Survey (TDHS), the 1996 TDHS, the 1999 Reproductive and Child Health Survey (RCHS), and the 2004-05 TDHS.

More specifically, the objectives of the 2007-08 THMIS were: - To measure HIV prevalence among women and men age 15-49; - To assess levels and trends in knowledge about HIV/AIDS, attitudes towards people infected with the disease, and patterns of sexual behaviour; - To collect information on the proportion of adults who are chronically sick, the extent of orphanhood, levels of and care and support; - To gauge the extent to which these indicators vary by characteristics such as age, sex, region, education, marital status, and poverty status; and - To measure the presence of malaria parasites and anaemia among children age 6-59 months.

The results of the 2007-08 THMIS are intended to provide information to assist policymakers and programme implementers to monitor and evaluate existing programmes and to design new strategies for combating the HIV/AIDS epidemic in Tanzania. The survey data will also be used as inputs in population projections and to calculate indicators developed by the United Nations General Assembly Special Session (UNGASS), the UNAIDS Programme, and the World Health Organization (WHO).

Geographic coverage

National

Analysis unit

• Households
• Women age 15-49
• Men age 15-49

Kind of data

Sample survey data [ssd]

Sampling procedure

SAMPLE SIZE AND DESIGN

The sampling frame used for the 2007-08 THMIS is the same as that used for the 2004-05 TDHS, which was developed by NBS after the 2002 Population and Housing Census (PHC). The sample excluded nomadic and institutional populations, such as persons staying in hotels, barracks, and prisons. The THMIS utilised a two-stage sample design. The first stage involved selecting sample points (clusters) consisting of enumeration areas delineated for the 2002 PHC. A total of 475 clusters were selected. The sample was designed to allow estimates of key indicators for each of Tanzania's 26 regions. On the Mainland, 25 sample points were selected in Dar es Salaam and 18 in each of the other 20 regions. In Zanzibar, 18 sample points were selected in each of the five regions, for a total of 90 sample points.

A household listing operation was undertaken in all the selected areas prior to the fieldwork. From these lists, households to be included in the survey were selected. The second stage of selection involved the systematic sampling of households from these lists. Approximately 16 households were selected from each sampling point in Dar es Salaam, and 18 households per sampling point were selected in other regions. In Zanzibar, approximately 18 households were selected from each sampling point in Unguja, and 36 households were selected in Pemba to allow reliable estimates of HIV prevalence for each island group.

Because of the approximately equal sample sizes in each region, the sample is not selfweighting at the national level, and weighting factors have been added to the data file so that the results will be proportional at the national level.

In the selected households, interviews were conducted with all women and men age 15-49. The THMIS also collected blood samples for anaemia and malaria testing among children age 6

Mode of data collection

Face-to-face [f2f]

Research instrument

Two questionnaires were used for the 2007-08 THMIS: the Household Questionnaire and the Individual Questionnaire. The questionnaires are based on the standard AIDS Indicator Survey and Malaria Indicator Survey questionnaires, adapted for the population and health issues relevant to Tanzania. Inputs were solicited from various stakeholders representing government ministries and agencies, nongovernmental organizations, and international partners. After the preparation of the definitive questionnaires in English, questionnaires were translated into Kiswahili.

The Household Questionnaire was used to list all the usual members and visitors of selected households. Some basic information was collected on the characteristics of each person listed, including his or her age, sex, education, and relationship to the head of the household. For children under age 18 years, survival status of the parents was determined. If a child in the household had a parent who was sick for more than three consecutive months in the 12 months preceding the survey or a parent who had died, additional questions related to support for orphans and vulnerable children were asked. The Household Questionnaire also included questions on whether household members were seriously ill and whether anyone in the household had died in the past 12 months. In such cases, interviewers asked whether the household had received various kinds of care and support, such as financial assistance, medical support, social or spiritual support.

The Household Questionnaire was also used to identify women and men who were eligible for the individual interview and HIV testing. The Household Questionnaire also collected information on characteristics of the household dwelling, such as source of water, type of toilet facilities, materials used to construct the house, ownership of various durable goods, and ownership and use of mosquito nets.

Furthermore, the Household Questionnaire was used to record haemoglobin and malaria testing results for children age 6-59 months.

The Individual Questionnaire was used to collect information from all women and men age 15-49. These respondents were asked questions on the following topics: • Background characteristics (education, residential history, media exposure, employment, etc.); • Marriage and sexual activity; • Knowledge about HIV/AIDS and exposure to specific HIV-related mass media programmes; • Attitudes towards people living with HIV/AIDS; • Knowledge and experience with HIV testing; • Knowledge and symptoms of other sexually transmitted infections (STIs); and • Other health issues including knowledge of TB and medical injections.

Female respondents were asked about their birth history and illnesses of children they gave birth to since January 2002. These questions are used to gauge the prevalence of fever, an important symptom of malaria.

Response rate

A total of 9,144 households were selected for the sample, from both Mainland Tanzania and Zanzibar. Of these, 8,704 were found to be occupied at the time of the survey. A total of 8,497 households were successfully interviewed, yielding a response rate of 98 percent. In the interviewed households, 9,735 women were identified as eligible for the individual interview. Completed interviews were obtained for 9,343 women, yielding a response rate of 96 percent. Of the 7,935 eligible men identified, 6,975 were successfully interviewed (88 percent response rate). The differential is likely due to the more frequent and longer absence of men from the households. The response rates for urban and rural areas do not vary much.

Note: See summarized responses rate by urban/rural in Table 1.1 which is provided in this documentation.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: (1) nonsampling errors, and (2) sampling errors. Nonsampling errors are the results of mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made during the implementation of the 2007-08 Tanzania HIV/AIDS and Malaria Survey (THMIS) to minimize this type of error, nonsampling errors are impossible to avoid and difficult to evaluate statistically.

Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the 2007-08 THMIS is 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 would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability between all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

A sampling error is usually measured in terms of the standard error for a particular statistic (mean, percentage, etc.), which is the square root of the variance. 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 plus or minus two times the standard error of that statistic in 95 percent of all possible samples of identical size and design.

If the

Abstract

The Estimating the Size of Populations through a Household Survey (EPSHS), sought to assess the feasibility of the network scale-up and proxy respondent methods for estimating the sizes of key populations at higher risk of HIV infection and to compare the results to other estimates of the population sizes. The study was undertaken based on the assumption that if these methods proved to be feasible with a reasonable amount of data collection for making adjustments, countries would be able to add this module to their standard household survey to produce size estimates for their key populations at higher risk of HIV infection. This would facilitate better programmatic responses for prevention and caring for people living with HIV and would improve the understanding of how HIV is being transmitted in the country.

The specific objectives of the ESPHS were: 1. To assess the feasibility of the network scale-up method for estimating the sizes of key populations at higher risk of HIV infection in a Sub-Saharan African context; 2. To assess the feasibility of the proxy respondent method for estimating the sizes of key populations at higher risk of HIV infection in a Sub-Saharan African context; 3. To estimate the population size of MSM, FSW, IDU, and clients of sex workers in Rwanda at a national level; 4. To compare the estimates of the sizes of key populations at higher risk for HIV produced by the network scale-up and proxy respondent methods with estimates produced using other methods; and 5. To collect data to be used in scientific publications comparing the use of the network scale-up method in different national and cultural environments.

Geographic coverage

National

Analysis unit

• Household
• Individual

Sampling procedure

The Estimating the Size of Populations through a Household Survey (ESPHS) used a two-stage sample design, implemented in a representative sample of 2,125 households selected nationwide in which all women and men age 15 years and above where eligible for an individual interview. The sampling frame used was the preparatory frame for the Rwanda Population and Housing Census (RPHC), which was conducted in 2012; it was provided by the National Institute of Statistics of Rwanda (NISR).

The sampling frame was a complete list of natural villages covering the whole country (14,837 villages). Two strata were defined: the city of Kigali and the rest of the country. One hundred and thirty Primary Sampling Units (PSU) were selected from the sampling frame (35 in Kigali and 95 in the other stratum). To reduce clustering effect, only 20 households were selected per cluster in Kigali and 15 in the other clusters. As a result, 33 percent of the households in the sample were located in Kigali.

The list of households in each cluster was updated upon arrival of the survey team in the cluster. Once the listing had been updated, a number was assigned to each existing household in the cluster. The supervisor then identified the households to be interviewed in the survey by using a table in which the households were randomly pre-selected. This table also provided the list of households pre-selected for each of the two different definitions of what it means "to know" someone.

For further details on sample design and implementation, see Appendix A of the final report.

Mode of data collection

Face-to-face [f2f]

Research instrument

The Estimating the Size of Populations through a Household Survey (ESPHS) used two types of questionnaires: a household questionnaire and an individual questionnaire. The same individual questionnaire was used to interview both women and men. In addition, two versions of the individual questionnaire were developed, using two different definitions of what it means “to know” someone. Each version of the individual questionnaire was used in half of the selected households.

Cleaning operations

The processing of the ESPHS data began shortly after the fieldwork commenced. Completed questionnaires were returned periodically from the field to the SPH office in Kigali, where they were entered and checked for consistency by data processing personnel who were specially trained for this task. Data were entered using CSPro, a programme specially developed for use in DHS surveys. All data were entered twice (100 percent verification). The concurrent processing of the data was a distinct advantage for data quality, because the School of Public Health had the opportunity to advise field teams of problems detected during data entry. The data entry and editing phase of the survey was completed in late August 2011.

Response rate

A total of 2,125 households were selected in the sample, of which 2,120 were actually occupied at the time of the interview. The number of occupied households successfully interviewed was 2,102, yielding a household response rate of 99 percent.

From the households interviewed, 2,629 women were found to be eligible and 2,567 were interviewed, giving a response rate of 98 percent. Interviews with men covered 2,102 of the eligible 2,149 men, yielding a response rate of 98 percent. The response rates do not significantly vary by type of questionnaire or residence.

Sampling error estimates

The estimates from a sample survey are affected by two types of errors: (1) non-sampling errors, and (2) sampling errors. Non-sampling errors are the results of mistakes made in implementing data collection and data processing, such as failure to locate and interview the correct household, misunderstanding of the questions on the part of either the interviewer or the respondent, and data entry errors. Although numerous efforts were made to minimize this type of error during the implementation of the Rwanda ESPHS 2011, non-sampling errors are impossible to avoid and difficult to evaluate statistically.

Sampling errors, on the other hand, can be evaluated statistically. The sample of respondents selected in the ESPHS 2011 is only one of many samples that could have been selected from the same population, using the same design and identical size. Each of these samples would yield results that differ somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability between all possible samples. Although the degree of variability is not known exactly, it can be estimated from the survey results.

A sampling error is usually measured in terms of the standard error for a particular statistic (mean, percentage, etc.), which is the square root of the variance. 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 plus or minus two times the standard error of that statistic in 95 percent of all possible samples of identical size and design.

If the sample of respondents had been selected as a simple random sample, it would have been possible to use straightforward formulas for calculating sampling errors. However, the ESPHS 2011 sample is the result of a multi-stage stratified design, and, consequently, it was necessary to use more complex formulae. The computer software used to calculate sampling errors for the ESPHS 2011 is a SAS program. This program uses the Taylor linearization method for variance estimation for survey estimates that are means or proportions.

A more detailed description of estimates of sampling errors are presented in Appendix B of the survey report.

Somalia Net Official Flows from UN Agencies: UNCDF data was reported at -0.013 USD mn in 2022. This records a decrease from the previous number of 0.005 USD mn for 2021. Somalia Net Official Flows from UN Agencies: UNCDF data is updated yearly, averaging 0.005 USD mn from Dec 2020 (Median) to 2022, with 3 observations. The data reached an all-time high of 0.005 USD mn in 2020 and a record low of -0.013 USD mn in 2022. Somalia Net Official Flows from UN Agencies: UNCDF data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Somalia – Table SO.World Bank.WDI: Defense and Official Development Assistance. Net official flows from UN agencies are the net disbursements of total official flows from the UN agencies. Total official flows are the sum of Official Development Assistance (ODA) or official aid and Other Official Flows (OOF) and represent the total disbursements by the official sector at large to the recipient country. Net disbursements are gross disbursements of grants and loans minus repayments of principal on earlier loans. ODA consists of loans made on concessional terms (with a grant element of at least 25 percent, calculated at a rate of discount of 10 percent) and grants made to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. Official aid refers to aid flows from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. OOF are transactions by the official sector whose main objective is other than development-motivated, or, if development-motivated, whose grant element is below the 25 per cent threshold which would make them eligible to be recorded as ODA. The main classes of transactions included here are official export credits, official sector equity and portfolio investment, and debt reorganization undertaken by the official sector at nonconcessional terms (irrespective of the nature or the identity of the original creditor). UN agencies are United Nations includes the United Nations Children’s Fund (UNICEF), United Nations Relief and Works Agency for Palestine Refugees in the Near East (UNRWA), World Food Programme (WFP), International Fund for Agricultural Development (IFAD), United Nations Development Programme(UNDP), United Nations Population Fund (UNFPA), United Nations Refugee Agency (UNHCR), Joint United Nations Programme on HIV/AIDS (UNAIDS), United Nations Regular Programme for Technical Assistance (UNTA), United Nations Peacebuilding Fund (UNPBF), International Atomic Energy Agency (IAEA), World Health Organization (WHO), United Nations Economic Commission for Europe (UNECE), Food and Agriculture Organization of the United Nations (FAO), International Labour Organization (ILO), United Nations Environment Programme (UNEP), World Tourism Organization (UNWTO), United Nations Institute for Disarmament Research (UNIDIR), United Nations Capital Development Fund (UNCDF), WHO-Strategic Preparedness and Response Plan (SPRP), United Nations Women (UNWOMEN), Covid-19 Response and Recovery Multi-Partner Trust Fund (UNCOVID), Joint Sustainable Development Goals Fund (SDGFUND), Central Emergency Response Fund (CERF), WTO-International Trade Centre (WTO-ITC), United National Conference on Trade and Development (UNCTAD), and United Nations Industrial Development Organization (UNIDO). Data are in current U.S. dollars.;Development Assistance Committee of the Organisation for Economic Co-operation and Development, Geographical Distribution of Financial Flows to Developing Countries, Development Co-operation Report, and International Development Statistics database. Data are available online at: https://data-explorer.oecd.org/.;Sum;

Macedonia MK: Net Official Flows from UN Agencies: UNICEF data was reported at 0.640 USD mn in 2016. This records a decrease from the previous number of 0.980 USD mn for 2015. Macedonia MK: Net Official Flows from UN Agencies: UNICEF data is updated yearly, averaging 0.720 USD mn from Dec 1995 (Median) to 2016, with 22 observations. The data reached an all-time high of 1.360 USD mn in 1996 and a record low of 0.480 USD mn in 2000. Macedonia MK: Net Official Flows from UN Agencies: UNICEF data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Macedonia – Table MK.World Bank: Defense and Official Development Assistance. Net official flows from UN agencies are the net disbursements of total official flows from the UN agencies. Total official flows are the sum of Official Development Assistance (ODA) or official aid and Other Official Flows (OOF) and represent the total disbursements by the official sector at large to the recipient country. Net disbursements are gross disbursements of grants and loans minus repayments of principal on earlier loans. ODA consists of loans made on concessional terms (with a grant element of at least 25 percent, calculated at a rate of discount of 10 percent) and grants made to promote economic development and welfare in countries and territories in the DAC list of ODA recipients. Official aid refers to aid flows from official donors to countries and territories in part II of the DAC list of recipients: more advanced countries of Central and Eastern Europe, the countries of the former Soviet Union, and certain advanced developing countries and territories. Official aid is provided under terms and conditions similar to those for ODA. Part II of the DAC List was abolished in 2005. The collection of data on official aid and other resource flows to Part II countries ended with 2004 data. OOF are transactions by the official sector whose main objective is other than development-motivated, or, if development-motivated, whose grant element is below the 25 per cent threshold which would make them eligible to be recorded as ODA. The main classes of transactions included here are official export credits, official sector equity and portfolio investment, and debt reorganization undertaken by the official sector at nonconcessional terms (irrespective of the nature or the identity of the original creditor).). UN agencies are United Nations includes the United Nations Children’s Fund (UNICEF), United Nations Relief and Works Agency for Palestine Refugees in the Near East (UNRWA), World Food Programme (WFP), International Fund for Agricultural Development (IFAD), United Nations Development Programme(UNDP), United Nations Population Fund (UNFPA), United Nations Refugee Agency (UNHCR), Joint United Nations Programme on HIV/AIDS (UNAIDS), United Nations Regular Programme for Technical Assistance (UNTA), , United Nations Peacebuilding Fund (UNPBF), International Atomic Energy Agency (IAEA), Wolrd Health Organization (WHO), United Nations Economic Commission for Europe (UNECE), Food and Agriculture Organization of the United Nations (FAO), and International Labour Organization (ILO). Data are in current U.S. dollars.; ; Development Assistance Committee of the Organisation for Economic Co-operation and Development, Geographical Distribution of Financial Flows to Developing Countries, Development Co-operation Report, and International Development Statistics database. Data are available online at: www.oecd.org/dac/stats/idsonline.; Sum;

countries that start with B. name, long name, population (source), population, constitutional form, drives on, head of state authority, Main continent, number of airports, Airports - with paved runways, Airports - with unpaved runways, Area, Birth rate, calling code, Children under the age of 5 years underweight, Current Account Balance, Death rate, Debt - external, Economic aid donor, Electricity consumption, Electricity consumption per capita, Electricity exports, Electricity imports, Electricity production, Exports, GDP - per capita (PPP), GDP (purchasing power parity), GDP real growth rate, Gross national income, Human Development Index, Health expenditures, Heliports, HIV AIDS adult prevalence rate, HIV AIDS deaths, HIV AIDS people living with HIV AIDS, Hospital bed density, capital city, Currency, Imports, Industrial production growth rate, Infant mortality rate, Inflation rate consumer prices, Internet hosts, internet tld, Internet users, Investment (gross fixed), iso 3166 code, ISO CODE, Labor force, Life expectancy at birth, Literacy, Manpower available for military service, Manpower fit for military service, Manpower reaching militarily age annually, is democracy, Market value of publicly traded shares, Maternal mortality rate, Merchant marine, Military expenditures percent of GDP, Natural gas consumption, Natural gas consumption per capita, Natural gas exports, Natural gas imports, Natural gas production, Natural gas proved reserves, Net migration rate, Obesity adult prevalence rate, Oil consumption, Oil consumption per capita, Oil exports, Oil imports, Oil production, Oil proved reserves, Physicians density, Population below poverty line, Population census, Population density, Population estimate, Population growth rate, Public debt, Railways, Reserves of foreign exchange and gold, Roadways, Stock of direct foreign investment abroad, Stock of direct foreign investment at home, Telephones main lines in use, Telephones main lines in use per capita, Telephones mobile cellular, Telephones mobile cellular per capita, Total fertility rate, Unemployment rate, Unemployment, youth ages 15-24, Waterways, valley, helicopter, canyon, artillery, crater, religion, continent, border, Plateau, marsh, Demonym

countries that start with O. name, long name, population (source), population, constitutional form, drives on, head of state authority, Main continent, number of airports, Airports - with paved runways, Airports - with unpaved runways, Area, Birth rate, calling code, Children under the age of 5 years underweight, Current Account Balance, Death rate, Debt - external, Economic aid donor, Electricity consumption, Electricity consumption per capita, Electricity exports, Electricity imports, Electricity production, Exports, GDP - per capita (PPP), GDP (purchasing power parity), GDP real growth rate, Gross national income, Human Development Index, Health expenditures, Heliports, HIV AIDS adult prevalence rate, HIV AIDS deaths, HIV AIDS people living with HIV AIDS, Hospital bed density, capital city, Currency, Imports, Industrial production growth rate, Infant mortality rate, Inflation rate consumer prices, Internet hosts, internet tld, Internet users, Investment (gross fixed), iso 3166 code, ISO CODE, Labor force, Life expectancy at birth, Literacy, Manpower available for military service, Manpower fit for military service, Manpower reaching militarily age annually, is democracy, Market value of publicly traded shares, Maternal mortality rate, Merchant marine, Military expenditures percent of GDP, Natural gas consumption, Natural gas consumption per capita, Natural gas exports, Natural gas imports, Natural gas production, Natural gas proved reserves, Net migration rate, Obesity adult prevalence rate, Oil consumption, Oil consumption per capita, Oil exports, Oil imports, Oil production, Oil proved reserves, Physicians density, Population below poverty line, Population census, Population density, Population estimate, Population growth rate, Public debt, Railways, Reserves of foreign exchange and gold, Roadways, Stock of direct foreign investment abroad, Stock of direct foreign investment at home, Telephones main lines in use, Telephones main lines in use per capita, Telephones mobile cellular, Telephones mobile cellular per capita, Total fertility rate, Unemployment rate, Unemployment, youth ages 15-24, Waterways, valley, helicopter, canyon, artillery, crater, religion, continent, border, Plateau, marsh, Demonym

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.

countries capital city Libreville. name, long name, population (source), population, constitutional form, drives on, head of state authority, Main continent, number of airports, Airports - with paved runways, Airports - with unpaved runways, Area, Birth rate, calling code, Children under the age of 5 years underweight, Current Account Balance, Death rate, Debt - external, Economic aid donor, Electricity consumption, Electricity consumption per capita, Electricity exports, Electricity imports, Electricity production, Exports, GDP - per capita (PPP), GDP (purchasing power parity), GDP real growth rate, Gross national income, Human Development Index, Health expenditures, Heliports, HIV AIDS adult prevalence rate, HIV AIDS deaths, HIV AIDS people living with HIV AIDS, Hospital bed density, capital city, Currency, Imports, Industrial production growth rate, Infant mortality rate, Inflation rate consumer prices, Internet hosts, internet tld, Internet users, Investment (gross fixed), iso 3166 code, ISO CODE, Labor force, Life expectancy at birth, Literacy, Manpower available for military service, Manpower fit for military service, Manpower reaching militarily age annually, is democracy, Market value of publicly traded shares, Maternal mortality rate, Merchant marine, Military expenditures percent of GDP, Natural gas consumption, Natural gas consumption per capita, Natural gas exports, Natural gas imports, Natural gas production, Natural gas proved reserves, Net migration rate, Obesity adult prevalence rate, Oil consumption, Oil consumption per capita, Oil exports, Oil imports, Oil production, Oil proved reserves, Physicians density, Population below poverty line, Population census, Population density, Population estimate, Population growth rate, Public debt, Railways, Reserves of foreign exchange and gold, Roadways, Stock of direct foreign investment abroad, Stock of direct foreign investment at home, Telephones main lines in use, Telephones main lines in use per capita, Telephones mobile cellular, Telephones mobile cellular per capita, Total fertility rate, Unemployment rate, Unemployment, youth ages 15-24, Waterways, valley, helicopter, canyon, artillery, crater, religion, continent, border, Plateau, marsh, Demonym