10 datasets found
  1. Countries with the highest prevalence of HIV in 2000 and 2023

    • statista.com
    • ai-chatbox.pro
    Updated Jun 23, 2025
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    Statista (2025). Countries with the highest prevalence of HIV in 2000 and 2023 [Dataset]. https://www.statista.com/statistics/270209/countries-with-the-highest-global-hiv-prevalence/
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    Dataset updated
    Jun 23, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    Worldwide
    Description

    Among all countries worldwide those in sub-Saharan Africa have the highest rates of HIV. The countries with the highest rates of HIV include Eswatini, Lesotho, and South Africa. In 2023, Eswatini had the highest prevalence of HIV with a rate of around ** percent. Other countries, such as Zimbabwe, have significantly decreased their HIV prevalence. Community-based HIV services are considered crucial to the prevention and treatment of HIV. HIV Worldwide The human immunodeficiency virus (HIV) is a viral infection that is transmitted via exposure to infected semen, blood, vaginal and anal fluids and breast milk. HIV destroys the human immune system, rendering the host unable to fight off secondary infections. Globally, the number of people living with HIV has generally increased over the past two decades. However, the number of HIV-related deaths has decreased significantly in recent years. Despite being a serious illness that affects millions of people, medication exists that effectively manages the progression of the virus in the body. These medications are called antiretroviral drugs. HIV Treatment Generally, global access to antiretroviral treatment has increased in recent years. However, despite being available worldwide, not all adults have access to antiretroviral drugs. Europe and North America have the highest rates of antiretroviral use among people living with HIV. There are many different antiretroviral drugs available on the market. As of 2024, ********, an antiretroviral marketed by Gilead, was the leading HIV treatment based on revenue.

  2. G

    HIV infections by country, around the world | TheGlobalEconomy.com

    • theglobaleconomy.com
    csv, excel, xml
    Updated Apr 24, 2015
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    Globalen LLC (2015). HIV infections by country, around the world | TheGlobalEconomy.com [Dataset]. www.theglobaleconomy.com/rankings/HIV_infections/
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    xml, excel, csvAvailable download formats
    Dataset updated
    Apr 24, 2015
    Dataset authored and provided by
    Globalen LLC
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Dec 31, 1990 - Dec 31, 2022
    Area covered
    World, World
    Description

    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.

  3. Rates of HIV diagnoses in the United States in 2022, by state

    • statista.com
    • ai-chatbox.pro
    Updated Apr 9, 2025
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    Statista (2025). Rates of HIV diagnoses in the United States in 2022, by state [Dataset]. https://www.statista.com/statistics/257734/us-states-with-highest-aids-diagnosis-rates/
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    Dataset updated
    Apr 9, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2022
    Area covered
    United States
    Description

    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.

  4. Number of people with HIV in select countries in Africa 2023

    • statista.com
    • ai-chatbox.pro
    Updated Aug 21, 2024
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    Statista (2024). Number of people with HIV in select countries in Africa 2023 [Dataset]. https://www.statista.com/statistics/1305217/number-people-with-hiv-african-countries/
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    Dataset updated
    Aug 21, 2024
    Dataset authored and provided by
    Statistahttp://statista.com/
    Time period covered
    2023
    Area covered
    Africa
    Description

    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.

  5. w

    National Family Health Survey 2005-2006 - India

    • microdata.worldbank.org
    • datacatalog.ihsn.org
    • +2more
    Updated Jun 16, 2017
    + more versions
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    International Institute for Population Sciences (IIPS) (2017). National Family Health Survey 2005-2006 - India [Dataset]. https://microdata.worldbank.org/index.php/catalog/1406
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    Dataset updated
    Jun 16, 2017
    Dataset authored and provided by
    International Institute for Population Sciences (IIPS)
    Time period covered
    2005 - 2006
    Area covered
    India
    Description

    Abstract

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

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

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

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

    Geographic coverage

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

    Analysis unit

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

    Universe

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

    Kind of data

    Sample survey data

    Sampling procedure

    SAMPLE SIZE

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

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

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

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

    SAMPLE DESIGN

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

    SAMPLE SELECTION IN RURAL AREAS

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

  6. f

    First report of occult hepatitis B infection among ART naïve HIV...

    • figshare.com
    docx
    Updated Jun 1, 2023
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    Awa Abdul Carimo; Eduardo Samo Gudo; Cremildo Maueia; Nédio Mabunda; Lúcia Chambal; Adolfo Vubil; Ana Flora; Francisco Antunes; Nilesh Bhatt (2023). First report of occult hepatitis B infection among ART naïve HIV seropositive individuals in Maputo, Mozambique [Dataset]. http://doi.org/10.1371/journal.pone.0190775
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    docxAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Awa Abdul Carimo; Eduardo Samo Gudo; Cremildo Maueia; Nédio Mabunda; Lúcia Chambal; Adolfo Vubil; Ana Flora; Francisco Antunes; Nilesh Bhatt
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    Mozambique, Maputo
    Description

    BackgroundThe prevalence of hepatitis B virus (HBV) infection and human immunodeficiency virus (HIV) infection in Mozambique is one of the highest in the world, though in spite of this the prevalence of occult hepatitis B infection (OBI) is unknown.ObjectivesThis study was conducted with the aim to investigate the prevalence of OBI and frequency of isolated hepatitis B core antibody (anti-HBc alone) among antiretroviral (ART) naïve HIV-positive patients in Mozambique.MethodsA cross-sectional study was conducted in two health facilities within Maputo city. All ART-naive HIV seropositive patients attending outpatient clinics between June and October 2012 were consecutively enrolled. Blood samples were drawn from each participant and used for serological measurement of HBV surface antigen (HBsAg), antibodies against HBV surface antigen (anti-HBs) and antibodies against core antigen (anti-HBc) using ELISA. Quantification of HBV DNA was performed by real time PCR. A questionnaire was used to obtain demographics and clinical data.ResultsOf the 518 ART-naive HIV-positive subjects enrolled in the study, 90.9% (471/518) were HBsAg negative. Among HBsAg negative, 45.2% (213/471) had isolated anti-HBc antibodies, and the frequency of OBI among patients with anti-HBc alone was 8.3% (17/206). OBI was not correlated either with CD4+ T cells count or transaminases levels. A total of 11.8% of patients with OBI presented elevated HBV DNA level. Frequency of individuals with APRI score > 2 and FIB-4 score > 3.25 was higher in patients with OBI as compared not exposed, immune and anti-HBc alone patients.ConclusionOur data demonstrate for the first time that OBI is prevalent among HIV patients in Mozambique, and will be missed using the commonly available serological assays that measures HBsAg.

  7. a

    Nigeria Medical Health Points

    • ebola-nga.opendata.arcgis.com
    Updated Dec 6, 2014
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    National Geospatial-Intelligence Agency (2014). Nigeria Medical Health Points [Dataset]. https://ebola-nga.opendata.arcgis.com/datasets/nigeria-medical-health-points
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    Dataset updated
    Dec 6, 2014
    Dataset authored and provided by
    National Geospatial-Intelligence Agency
    Area covered
    Description

    Nigeria’s health care system is a tiered system of primary, secondary, and tertiary facilities. Primary care occurs predominately in the form of health clinics and dispensaries scattered throughout the country. Secondary care refers to healthcare and maternity centers and tertiary care is handled through the 12 university teaching hospitals. Overall healthcare institutions are considered poor as shortages of medical material and an unsafe blood supply are commonplace. Nigeria’s health indicators have declined over the past decade.

    Keeping doctors in Nigeria is a problem. Many doctors and highly trained medical staff leave Nigeria to pursue more lucrative jobs in countries with better infrastructure. Doctors who do remain have a history of going on strike, leaving citizens and communities in disarray. As of 2008, there were an estimated 4 doctors for every 10,000 inhabitants.

    Malaria and tuberculosis are the most common diseases in Nigeria. Malaria and diarrheal diseases accounted for the roughly half of all childhood mortality cases. Nigeria has one of the highest rates of infant and maternal mortality in the developing world. Serious outbreaks of cerebrospinal meningitis still occur in the northern region of the country. HIV/AIDS has reached epidemic levels in Nigeria. At the end of 2003, HIV/AIDS was estimated at 3.6 million and deaths from AIDS were estimated at 310,000.

    ISO3-International Organization for Standardization 3-digit country code

    NAME-Name of the medical facility

    TYPE-Type of medical facility

    CITY-City medical facility is located in

    SPA_ACC-Spatial accuracy of site location 1- high, 2 – medium, 3 - low

    SOURCE_DT-Source creation date

    SOURCE-Primary source

    Collection

    This HGIS was created using information collected from several different websites. BBBike and Wikimapia helped locate medical facilities and pharmacies. Medical facilities are labeled if no definitive type was identified in the research. After collecting this information, all medical facilities were geo-located using DigitalGlobe satellite imagery. Institutions without proper village locations were omitted from the shapefile.

    The data included herein have not been derived from a registered survey and should be considered approximate unless otherwise defined. While rigorous steps have been taken to ensure the quality of each dataset, DigitalGlobe Analytics is not responsible for the accuracy and completeness of data compiled from outside sources.

    Sources (HGIS)

    BBBike, "Nigeria." Last modified 2013. Accessed April 4, 2013. http://extract.bbbike.org.

  8. i

    Multiple Indicator Cluster Survey 2006 - Kazakhstan

    • dev.ihsn.org
    • catalog.ihsn.org
    • +3more
    Updated Apr 25, 2019
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    Agency of Statistics (2019). Multiple Indicator Cluster Survey 2006 - Kazakhstan [Dataset]. https://dev.ihsn.org/nada/catalog/72552
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    Dataset updated
    Apr 25, 2019
    Dataset authored and provided by
    Agency of Statistics
    Time period covered
    2006
    Area covered
    Kazakhstan
    Description

    Abstract

    The Multiple Indicator Cluster Survey (MICS) is a household survey programme developed by UNICEF to assist countries in filling data gaps for monitoring human development in general and the situation of children and women in particular. MICS is capable of producing statistically sound, internationally comparable estimates of social indicators. The current round of MICS is focused on providing a monitoring tool for the Millennium Development Goals (MDGs), the World Fit for Children (WFFC), as well as for other major international commitments, such as the United Nations General Assembly Special Session (UNGASS) on HIV/AIDS and the Abuja targets for malaria.

    Survey Objectives The 2006 Kazakhstan Multiple Indicator Cluster Survey has as its primary objectives: - To provide up-to-date information for assessing the situation of children and women in Kazakhstan - To furnish data needed for monitoring progress toward goals established in the Millennium Declaration, the goals of A World Fit For Children (WFFC), and other internationally agreed upon goals, as a basis for future action; - To contribute to the improvement of data and monitoring systems in Kazakhstan and to strengthen technical expertise in the design, implementation, and analysis of such systems.

    Survey Content MICS questionnaires are designed in a modular fashion that can be easily customized to the needs of a country. They consist of a household questionnaire, a questionnaire for women aged 15-49 and a questionnaire for children under the age of five (to be administered to the mother or caretaker). Other than a set of core modules, countries can select which modules they want to include in each questionnaire.

    Survey Implementation The survey was carried out by The Agency of Statistics of the Republic of Kazakhstan, with the support and assistance of UNICEF and other partners. Technical assistance and training for the surveys is provided through a series of regional workshops, covering questionnaire content, sampling and survey implementation; data processing; data quality and data analysis; report writing and dissemination.

    Geographic coverage

    The sample for the Kazakhstan Multiple Indicator Cluster Survey (MICS) was designed to provide estimates on a large number of indicators on the situation of children and women at the national level, for urban and rural areas, as well as at sub-national level for 16 regions - 14 Oblasts and 2 Cities: - Akmola Oblast - Aktobe Oblast - Almaty Oblast - Atyrau Oblast - West Kazakhstan Oblast - Zhambyl Oblast - Karaganda Oblast - Kostanai Oblast - Kyzylorda Oblast - Mangistau Oblast - South Kazakhstan Oblast - Pavlodar Oblast - North Kazakhstan Oblast - East Kazakhstan Oblast - Astana City - Almaty City

    Analysis unit

    Households (defined as a group of persons who usually live and eat together)

    De jure household members (defined as memers of the household who usually live in the household, which may include people who did not sleep in the household the previous night, but does not include visitors who slept in the household the previous night but do not usually live in the household)

    Women aged 15-49

    Children aged 0-4

    Universe

    The survey covered all de jure household members (usual residents), all women aged 15-49 years resident in the household, and all children aged 0-4 years (under age 5) resident in the household.

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    Regions were identified as the main sampling domains and the sample was selected in two stages. The sample was stratified by urban and rural areas (which represent second level territorial and administrative units). 1999 Population Census enumeration areas were selected as Primary Sampling Units (PSUs). The number of primary sampling units (PSUs) for oblast and main cities depended on the total population at the beginning of 2005.

    At the first stage, mentioned number of PSUs was randomly selected for each stratum. In general, 625 PSUs were selected within the country. At the second stage, 24 households were systematically selected in each sampled primary sampling unit. Thus, total number of sampled households made 15,000.

    The sample was stratified by region and is not self-weighting. For reporting national level results, sample weights are used.

    For more information on the sampling design please see the sampling design document under the technical documents folder.

    Sampling deviation

    No major deviations from the original sample design were made. All sample enumeration areas were accessed and successfully interviewed with good response rates.

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    The questionnaires for the Kazakhstan MICS were structured questionnaires based on the MICS3 Model Questionnaire with some modifications and additions. A household questionnaire was administered in each household, which collected various information on household members including sex, age, relationship, and orphanhood status. The household questionnaire includes household characteristics, education, child labour, water and sanitation, and salt iodization, with optional modules for child discipline, maternal mortality and durability of housing and Kazakhstan specific modules about UICEF.

    In addition to a household questionnaire, questionnaires were administered in each household for women age 15-49 and children under age five. For children, the questionnaire was administered to the mother or caretaker of the child.

    The women's questionnaire include women's characteristics, child mortality, maternal and newborn health, marriage and union, contraception, and HIV/AIDS knowledge, with optional modules for domestic violence, and sexual (reproductive) behavior and Kazakhstan specific module for Tuberculosis.

    The children's questionnaire includes children's characteristics, birth registration and early learning, breastfeeding, care of illness, immunization, and anthropometry, with an optional module for child development.

    The questionnaires are based on the MICS3 model questionnaire; however, some Modules were adapted to Kazakhstan (in particular, Education Module, which was considerably changed). English questionnaires were translated into Russian and Kazakh. Questionnaires were pre-tested in Fabrichnyi (Almaty Oblast) and Kordai (Zhambyl Oblast) settlements in November 2005. Based on the results of the pre-test, modifications were made to the wording and translation of the questionnaires. All questionnaires and modules are provided as external resources.

    Cleaning operations

    Data editing took place at a number of stages throughout the processing (see Other processing), including: a) Office editing and coding b) During data entry c) Structure checking and completeness d) Secondary editing e) Structural checking of SPSS data files

    Detailed documentation of the editing of data can be found in the data processing guidelines

    Response rate

    Of the 15,000 households selected for the sample, 14,984 were found to be occupied. Of these 14,564 were successfully interviewed for a household response rate of 97.2 percent. In the interviewed households, 14,719 women (age 15-49) were identified. Of these, 14,570 were successfully interviewed, yielding a response rate of 99.0 percent. In addition, 4,424 children under age five were listed in the household questionnaire. Of these, questionnaires were completed for 4,416, which correspond to a response rate of 99.8 percent. Overall response rates calculated for the interviews of women 15-49 years of age and children under-5 were 96.2 and 97.0 percents respectively.

    Household response rates in rural areas were higher than in urban - 99.4 and 95.6 percent respectively. Overall household response rate throughout the country was high and varied from 91.6 percent in Almaty City up to 99 percent in Zhambyl Oblast.

    Sampling error estimates

    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 the implementation of data collection and data processing. Numerous efforts were made during implementation of the 2006 MICS to minimize this type of error, however, non-sampling errors are impossible to avoid and difficult to evaluate statistically.

    Sampling errors can be evaluated statistically. The sample of respondents to the 2006 MICS is only one of many possible 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 differe somewhat from the results of the actual sample selected. Sampling errors are a measure of the variability in the results of the survey between all possible samples, and, although, the degree of variability is not known exactly, it can be estimated from the survey results. The sampling erros are measured in terms of the standard error for a particular statistic (mean or percentage), which is the square root of the variance. Confidence intervals are calculated for each statistic within which the true value for the population can be assumed to fall. Plus or minus two standard errors of the statistic is used for key statistics presented in MICS, equivalent to a 95 percent confidence interval.

    If the sample of respondents had been a simple random sample, it would have been possible to use straightforward formulae for calculating sampling errors. However, the 2006 MICS sample is the result of a multi-stage stratified design, and consequently needs to use more

  9. i

    Multiple Indicator Cluster Survey 2005 - Belarus

    • dev.ihsn.org
    • catalog.ihsn.org
    • +2more
    Updated Apr 25, 2019
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    Ministry of Statistics and Analysis (2019). Multiple Indicator Cluster Survey 2005 - Belarus [Dataset]. https://dev.ihsn.org/nada/catalog/72457
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    Dataset updated
    Apr 25, 2019
    Dataset provided by
    Ministry of Statistics and Analysis
    Research Institute of Statistics
    Time period covered
    2005
    Area covered
    Belarus
    Description

    Abstract

    The Multiple Indicator Cluster Survey (MICS) is a household survey programme developed by UNICEF to assist countries in filling data gaps for monitoring human development in general and the situation of children and women in particular. MICS is capable of producing statistically sound, internationally comparable estimates of social indicators. The current round of MICS is focused on providing a monitoring tool for the Millennium Development Goals (MDGs), the World Fit for Children (WFFC), as well as for other major international commitments, such as the United Nations General Assembly Special Session (UNGASS) on HIV/AIDS and the Abuja targets for malaria.

    Survey Objectives The 2005 Belarus Multiple Indicator Cluster Survey has as its primary objectives: - To provide up-to-date information for assessing the situation of children and women in Belarus - To furnish data needed for monitoring progress toward goals established in the Millennium Declaration, the goals of A World Fit For Children (WFFC), and other internationally agreed upon goals, as a basis for future action; - To contribute to the improvement of data and monitoring systems in Belarus and to strengthen technical expertise in the design, implementation, and analysis of such systems.

    Survey Content MICS questionnaires are designed in a modular fashion that can be easily customized to the needs of a country. They consist of a household questionnaire, a questionnaire for women aged 15-49 and a questionnaire for children under the age of five (to be administered to the mother or caretaker). Other than a set of core modules, countries can select which modules they want to include in each questionnaire.

    Survey Implementation The survey was carried out by the Ministry of Statistics and Analysis of the Republic of Belarus, and Research Institute of Statistics of the Ministry of Statistics and Analysis of the Republic of Belarus with the support and assistance of UNICEF and Ministry of Health. Technical assistance and training for the surveys is provided through a series of regional workshops, covering questionnaire content, sampling and survey implementation; data processing; data quality and data analysis; report writing and dissemination.

    Geographic coverage

    The survey is nationally representative and covers the whole of Belarus.

    Analysis unit

    Households (defined as a group of persons who usually live and eat together)

    De jure household members (defined as memers of the household who usually live in the household, which may include people who did not sleep in the household the previous night, but does not include visitors who slept in the household the previous night but do not usually live in the household)

    Women aged 15-49

    Children aged 0-4

    Universe

    The survey covered all de jure household members (usual residents), all women aged 15-49 years resident in the household, and all children aged 0-4 years (under age 5) resident in the household.

    Kind of data

    Sample survey data [ssd]

    Sampling procedure

    The principal objective of the sample design was to provide current and reliable estimates on a set of indicators covering the four major areas of the World Fit for Children declaration, including promoting healthy lives; providing quality education; protecting against abuse, exploitation and violence; and combating HIV/AIDS. The population covered by the 2005 MICS is defined as the universe of all women aged 15-49 and all children aged under 5. A sample of households was selected and all women aged 15-49 identified as usual residents of these households were interviewed. In addition, the mother or the caretaker of all children aged under 5 who were usual residents of the household were also interviewed about the child.

    The 2005 MICS collected data from a nationally representative sample of households, women and children. The primary focus of the 2005 MICS was to provide estimates of key population and health, education, child protection and HIV related indicators for the country as a whole, and for urban and rural areas separately. In addition, the sample was designed to provide estimates for each of the 7 regions for key indicators. Belarus is divided into 7 regions. Each region is subdivided into big cities, small towns and rural areas (selskie sovety). In addition each unit was subdivided into polling stations in urban areas and rural settlements in selskie sovety. In total Belarus includes 20 big cities, 187 small cities and 1388 selskie soveties.

    MICS3 is utilizing the sample frame of household surveys that is being used in the republic. To provide uniform distribution of the sample allocation of the households in the republic the selection was carried out in Brest, Vitebsk, Gomel, Grodno, Minsk, Mogilev regions and in Minsk city.

    Three stage sampling has been carried out. At the first stage in each of the regions (oblasts) three sampling strata has been created: big cities, small towns and rural areas (selskie sovety); at the second stage - polling stations in urban areas and rural settlements in selskie sovety; at the third stage in the selected settlements the households were selected. Within the strata of big cities, at first stage, 20 big cities were selected with the probability equalling to 1. Within the strata of small towns 29 small towns were sampled systematically with pps and the measure of size was total population of the small towns. The number of small towns in every region (oblast) was selected based on division of the total number of population of all small towns of each region into average household size (2,6), sample share (1/600) and average load of interviewer (40).

    Within the strata of rural settlements (selskie sovety) at the first stage of sampling 53 rural settlements were selected systematically with pps and the measure of size was number of households in the rural settlement.

    On the second stage of sampling within the big cities and the small towns the polling stations were selected as sampling unit, in the rural settlements - settlements in rural area (selskie sovety).

    To cover the whole territory of the selected city the cartographical materials were used on the second stage of sampling within the big cities. The number of the polling stations was calculated based on division of the population of the city into the average size of the family (2,6), sample share (1/600) and estimated number of the households in each polling station (20).

    Three polling stations were selected in each small town from the list of the polling stations, ranking by number of voters. In rural areas, taking into account the difficulty of access and scattered nature of settlements, the territories of the rural areas (selskie sovety) were divided into zones and the closest rural settlements were grouped. One zone was selected in each rural area (selskie sovety) and within this zone all settlements were investigated.

    Throughout the Republic of Belarus there were 304 polling stations and the rural zones in selskie sovery selected in 2005.

    On the third stage of sampling, households were selected from the updated lists systematically taking into account the size of the cluster. In big cities the size of the cluster which is selected from the updated list households within the territory of polling station is 19-20 households, in small towns the size of the cluster is 13-14 households, and in rural areas the size of the cluster is 39-40 households.The size of clusters is not uniform. Variation in cluster sizes for urban and rural settlements was done on purpose since existing sampling plan was considering load of one interviewer, as one of the parameters, and distribution of sampled population into the sampling domains - proportionally to the distribution in general population.

    Besides, taking into account the limited representation of children under 5 in the household sample, the additional sub-sample of households with children aged 0-4 was formed. For this purpose, in each of the 304 clusters the lists of households was updated with the information on households with under 5 children through local out-patient health institutions. From these lists with higher probability then for households without children, the households with children aged 0-4 were selected.

    The resulting number of households for MICS3 sample in the Republic of Belarus was 7,000, including 2,857 households with children aged 0-4.

    Following standard MICS data collection rules, if a household was actually more than one household when visited, then a) if the selected household contained two households, both were interviewed, or b) if the selected household contained 3 or more households, then only the household of the person named as the head was interviewed.

    Sampling deviation

    No major deviations from the original sample design were made. All sample enumeration areas were accessed and successfully interviewed with good response rates.

    Mode of data collection

    Face-to-face [f2f]

    Research instrument

    The questionnaires for the Belarus MICS were structured questionnaires based on the MICS3 Model Questionnaire. A household questionnaire was administered in each household, which collected various information on household members including sex, age, relationship, and orphanhood status. The household questionnaire includes household listing, education, water and sanitation, household characteristics, child labour, and child discipline.

    In addition to a household questionnaire, questionnaires were administered in each household for women age 15-49 and children under age five. For children, the questionnaire was administered to the mother or

  10. f

    Condom use, STI/HIV testing behaviours, and PrEP use stratified by city.

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    Updated Mar 20, 2025
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    Richard Muhindo; Rachel King; Whitney Irie; Andrew Mujugira; Edith Nakku-Joloba; Stephen Okoboi; Patience Muwanguzi; Eva Laker Odongpiny; Nazarius Mbona Tumwesigye; Barbara Castelnuovo (2025). Condom use, STI/HIV testing behaviours, and PrEP use stratified by city. [Dataset]. http://doi.org/10.1371/journal.pone.0320065.t002
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    xlsAvailable download formats
    Dataset updated
    Mar 20, 2025
    Dataset provided by
    PLOS ONE
    Authors
    Richard Muhindo; Rachel King; Whitney Irie; Andrew Mujugira; Edith Nakku-Joloba; Stephen Okoboi; Patience Muwanguzi; Eva Laker Odongpiny; Nazarius Mbona Tumwesigye; Barbara Castelnuovo
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Condom use, STI/HIV testing behaviours, and PrEP use stratified by city.

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Statista (2025). Countries with the highest prevalence of HIV in 2000 and 2023 [Dataset]. https://www.statista.com/statistics/270209/countries-with-the-highest-global-hiv-prevalence/
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Countries with the highest prevalence of HIV in 2000 and 2023

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12 scholarly articles cite this dataset (View in Google Scholar)
Dataset updated
Jun 23, 2025
Dataset authored and provided by
Statistahttp://statista.com/
Area covered
Worldwide
Description

Among all countries worldwide those in sub-Saharan Africa have the highest rates of HIV. The countries with the highest rates of HIV include Eswatini, Lesotho, and South Africa. In 2023, Eswatini had the highest prevalence of HIV with a rate of around ** percent. Other countries, such as Zimbabwe, have significantly decreased their HIV prevalence. Community-based HIV services are considered crucial to the prevention and treatment of HIV. HIV Worldwide The human immunodeficiency virus (HIV) is a viral infection that is transmitted via exposure to infected semen, blood, vaginal and anal fluids and breast milk. HIV destroys the human immune system, rendering the host unable to fight off secondary infections. Globally, the number of people living with HIV has generally increased over the past two decades. However, the number of HIV-related deaths has decreased significantly in recent years. Despite being a serious illness that affects millions of people, medication exists that effectively manages the progression of the virus in the body. These medications are called antiretroviral drugs. HIV Treatment Generally, global access to antiretroviral treatment has increased in recent years. However, despite being available worldwide, not all adults have access to antiretroviral drugs. Europe and North America have the highest rates of antiretroviral use among people living with HIV. There are many different antiretroviral drugs available on the market. As of 2024, ********, an antiretroviral marketed by Gilead, was the leading HIV treatment based on revenue.

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