Dataset Overview

The dataset provides a comprehensive look at HIV/AIDS adult prevalence rates, the number of people living with HIV, and annual deaths across different countries. It is based on publicly available data sources such as the CIA World Factbook, UNAIDS AIDS Info, and other global health organizations. The dataset primarily focuses on adult HIV prevalence (ages 15–49) and includes estimates from recent years (e.g., 2023–2024).

Data Science Applications

This dataset can be used for: - Epidemiological Analysis: Understanding the regional distribution of HIV/AIDS and identifying high-prevalence areas. - Predictive Modeling: Developing machine learning models to predict HIV prevalence trends or identify risk factors. - Resource Allocation: Informing policymakers about regions requiring urgent intervention or resource allocation. - Health Outcome Monitoring: Tracking progress in combating HIV/AIDS over time. - Social Determinants Research: Analyzing the relationship between socio-economic factors and HIV prevalence.

Column Descriptors

1. Country/Region: The geographical area being analyzed.
2. Adult Prevalence (%): Percentage of adults aged 15–49 living with HIV.
3. Number of People with HIV/AIDS: Absolute count of individuals living with HIV in the region.
4. Annual Deaths from HIV/AIDS: Number of deaths attributed to HIV/AIDS annually.
5. Year of Estimate: The year when the data was collected or estimated.

Ethically Mined Data

The dataset is ethically sourced from publicly available and credible platforms such as the CIA World Factbook, UNAIDS, and WHO. These organizations ensure transparency and ethical standards in data collection, protecting individual privacy while providing aggregate statistics for research purposes.

Acknowledgments

1. Data Source Platforms:
   • CIA World Factbook
   • UNAIDS AIDS Info
   • WHO Global Health Observatory
2. Dataset Visualization Image:
   • Created using DALL-E 3 for illustrative purposes.
3. Research Support:
   • Contributions from platforms like ResearchGate, NIMH, and others for insights into data science applications in HIV research.

This dataset serves as a valuable tool for researchers, policymakers, and public health professionals in addressing the global challenge of HIV/AIDS.

Introduction

• HIV (human immunodeficiency virus) is a virus that attacks the body's immune system. If HIV is not treated, it can lead to AIDS (acquired immunodeficiency syndrome) which currently has no cure. Once people get HIV, they have it for life. But with proper medical care, HIV can be controlled. Symptoms: Influenza-like illness; Fatigue… Treatments: Management of HIV/AIDS Type of infectious agent: Virus (Human Immunodeficiency Virus) • AIDS (acquired immune deficiency syndrome) is the name used to describe a number of potentially life-threatening infections and illnesses that happen when one’s immune system has been severely damaged by the HIV virus. While AIDS cannot be transmitted from 1 person to another, the HIV virus can.

Dataset

The data set contains data of the following:- 1. The top causes of deaths in the world 2. Total number of deaths due to HIV/AIDS 3. ART (Anti Retro-viral Therapy) coverage among people living with HIV 4. Knowledge among young citizens (15-24years) about HIV/AIDS 5. Population of HIV/AIDS patients living with TB and their death rate 6. Life expectancy rate among HIV/AIDS patients 7. HIV/AIDS Patients in different age groups 8. Women population living with HIV 9. Young women in India having the knowledge of HIV/AIDS 10. HIV/AIDS deaths in Indian states

Data was scrapped from the official website of UNICEF -https://data.unicef.org/ and https://data.gov.in/

Ask Phase

• Data gives the trend of increasing no. of HIV/AIDS patients across the world • The information available for each country is percentage of total Global AIDS patients • Time period traced is 2000-2019 • Key Questions to answer:  Which countries and regions are affected the most?  How are the different age groups affected?  How much is the ART (Anti Retro-viral Therapy) coverage among the patients and what is the life expectancy rate?  What percentage of the population is aware of the prevention and causes of HIV/AIDS

Prepare phase.

• By tabulating and filtering the data the required data was obtained to bring out observations. • Data was formatted to the desired format to perform further calculations. • Sorting of data region wise. • Columns with inconsistent and empty cells were deleted. • The data of India was extracted for further analysis • Duplicate entries and undesired data was removed

Process phase

For cleaning the dataset for further analysis MS Excel was used due to small data. • Used sumifs() functions to aggregate the data region wise • Used sumif() to segregate the no. of patients within different age groups • Used sumifs() to find the total number of TB patients among HIV deaths. • Used countif() to find the percentage of male and female patients. • Sorted data to find the top and bottom nation with most and least HIV/AIDS patients

Analyze phase

• Formed the following pivot tables to answer key target questions  Year v/s number of death rates  Country v/s death numbers to bring out nation wise deaths  Causes of death v/s the number of deaths to bring at which position AIDS causes causality  Year v/s percentage of life expectancy to observe the pattern of no. of survivors

Visualization phase

The data was visualized using Tableau.

Presentaion

The final presentation was prepared by accumulating all observations and inferences which is linked below https://docs.google.com/presentation/d/1NEX10Vz5u5Va3CrTLVbvsUHZjO-fn8EOeiOHkP03T3Q/edit?usp=sharing

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

Global Health Outcomes Data

Impact on Mortality Rates and Malnutrition in Countries Around the World

By Humanitarian Data Exchange [source]

About this dataset

This dataset provides comprehensive insights into critical health conditions around the world, such as mortality rate, malnutrition levels, and frequency of preventable diseases. It documents the prevalence of life-threatening diseases like malaria and tuberculosis, and are tracked alongside key health indicators like adult mortality rates, HIV prevalence, physicians per 10,000 people ratio and public health expenditures. Such metrics provide us with an accurate picture of how developed healthcare systems are in certain countries which ultimately leads to improvements in public policy formation and awareness amongst decision-makers. With this data it is possible to observe disparities between different regions of the world which can help inform global strategies for providing equitable care globally. This dataset is a valuable source for researchers interested in understanding global health trends over time or seeking to evaluate regional differences within countries

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How to use the dataset

This dataset provides comprehensive global health outcome data for countries around the world. It includes vital information such as infant mortality rates, child malnutrition rates, adult mortality rates, deaths due to malaria and tuberculosis, HIV prevalence rates, life expectancy at age 60 and public health expenditure. This dataset can be used to gain valuable insight into the challenges faced by different countries in providing a good quality of life for their citizens.

To use this dataset, first identify what questions you need answered and what outcomes you are looking to measure. You may want to look at specific disease-based indicators (e.g. malaria or tuberculosis), health-related indicators (e.g., nutrition), or overall population markers (e.g., life expectancy).

Then decide which data points from the provided fields will help answer your questions and provide the results needed - e.g,. infant mortality rate or HIV prevalence rate - extracting these values from relevant columns like “Infants lacking immunization (% of one-year-olds) Measles 2013” or “HIV prevalence, adult (% ages 15Ð49) 2013” respectively

Next extract other columnwise relevant information - e.g., country name — that could also aid your analysis using tools like Excel or Python's Pandas library; sorting through them based on any metric desired — e..g,, physicians per 10k people — while being mindful that some data points are missing in some cases (denoted by NA).

Finally perform basic analyses with either your own scripting language, like R/Python libraries' numerical functions with accompanying visuals/graphs etc if elucidating trends is desired; drawing meaningful conclusions about overall state of global health outcomes accordingly before making informed decisions thereafter if needed too!

Research Ideas

• Create a world health map to visualize the differences in health outcomes across different countries and regions.
• Develop an AI-based decision support tool that identifies optimal public health policies or interventions based on these metrics for different countries.
• Design a dashboard or web app that displays and updates this data in real-time, to allow users to compare the current state of global health indicators and benchmark them against historical figures

Acknowledgements

If you use this dataset in your research, please credit the original authors. Data Source

License

License: CC0 1.0 Universal (CC0 1.0) - Public Domain Dedication No Copyright - You can copy, modify, distribute and perform the work, even for commercial purposes, all without asking permission. See Other Information.

Columns

File: health-outcomes-csv-1.csv | Column name | Description | |:-------------------------------------------------------------------------------|:--------------------------------------------------------------------------------------------------------------------| | Country | The name of the country. (String) ...

BackgroundSince the first HIV/AIDS case appeared in 1980s, HIV/AIDS has been the focus of international attention. As a major public health problem, there are epidemiological uncertainties about the future of HIV/AIDS. It is important to monitor the global statistics of HIV/AIDS prevalence, deaths, disability adjusted life years (DALYs), and risk factors for adequate prevention and control.MethodsThe Global Burden of Disease Study 2019 database was used to analyze the burden of HIV/AIDS in 1990–2019. By extracting global, regional, and national data on HIV/AIDS prevalence, deaths, and DALYs, we described the distribution by age and sex, explored the risk factors, and analyzed the trends in HIV/AIDS.ResultsIn 2019, there were 36.85 million HIV/AIDS cases (95% UI: 35.15–38.86 million), 863.84 thousand deaths (95% UI: 78.61–99.60 thousand), and 47.63 million (95% UI: 42.63–55.65 million) DALYs. The global age-standardized HIV/AIDS prevalence, death, and DALY rates were 454.32 (95% UI: 433.76–478.59), 10.72 (95% UI: 9.70–12.39), and 601.49 (95% UI: 536.16–703.92) per 100,000 cases, respectively. In 2019, the global age-standardized HIV/AIDS prevalence, death, and DALY rates increased by 307.26 (95% UI: 304.45–312.63), 4.34 (95% UI: 3.78–4.90), and 221.91 (95% UI: 204.36–239.47) per 100,000 cases, respectively, compared to 1990. Age-standardized prevalence, death, and DALY rates decreased in high sociodemographic index (SDI) areas. High age-standardized rates were observed in low sociodemographic index areas, while low age-standardized rates were observed in high sociodemographic index areas. In 2019, the high age-standardized prevalence, death, and DALY rates were predominant in Southern Sub-Saharan Africa, and global DALYs peaked in 2004 and subsequently decreased. The highest global HIV/AIDS DALYs were in the 40–44 age group. The main risk factors affecting HIV/AIDS DALY rates included behavioral risks, drug use, partner violence, and unsafe sex.ConclusionsHIV/AIDS disease burden and risk factors vary by region, sex, and age. As access to health care increases across countries and treatment for HIV/AIDS infection improves, the HIV/AIDS disease burden is concentrated in areas with low SDIs, particularly in South Africa. Regional differences should be fully considered to target optimal prevention strategies and treatment options based on risk factors.

Effect of suicide rates on life expectancy dataset

Abstract
In 2015, approximately 55 million people died worldwide, of which 8 million committed suicide. In the USA, one of the main causes of death is the aforementioned suicide, therefore, this experiment is dealing with the question of how much suicide rates affects the statistics of average life expectancy.
The experiment takes two datasets, one with the number of suicides and life expectancy in the second one and combine data into one dataset. Subsequently, I try to find any patterns and correlations among the variables and perform statistical test using simple regression to confirm my assumptions.

Data

The experiment uses two datasets - WHO Suicide Statistics[1] and WHO Life Expectancy[2], which were firstly appropriately preprocessed. The final merged dataset to the experiment has 13 variables, where country and year are used as index: Country, Year, Suicides number, Life expectancy, Adult Mortality, which is probability of dying between 15 and 60 years per 1000 population, Infant deaths, which is number of Infant Deaths per 1000 population, Alcohol, which is alcohol, recorded per capita (15+) consumption, Under-five deaths, which is number of under-five deaths per 1000 population, HIV/AIDS, which is deaths per 1 000 live births HIV/AIDS, GDP, which is Gross Domestic Product per capita, Population, Income composition of resources, which is Human Development Index in terms of income composition of resources, and Schooling, which is number of years of schooling.

LICENSE

THE EXPERIMENT USES TWO DATASET - WHO SUICIDE STATISTICS AND WHO LIFE EXPECTANCY, WHICH WERE COLLEECTED FROM WHO AND UNITED NATIONS WEBSITE. THEREFORE, ALL DATASETS ARE UNDER THE LICENSE ATTRIBUTION-NONCOMMERCIAL-SHAREALIKE 3.0 IGO (https://creativecommons.org/licenses/by-nc-sa/3.0/igo/).

[1] https://www.kaggle.com/szamil/who-suicide-statistics

[2] https://www.kaggle.com/kumarajarshi/life-expectancy-who

Cuba CU: Prevalence of HIV: Total: % of Population Aged 15-49 data was reported at 0.600 % in 2022. This stayed constant from the previous number of 0.600 % for 2021. Cuba CU: Prevalence of HIV: Total: % of Population Aged 15-49 data is updated yearly, averaging 0.200 % from Dec 1990 (Median) to 2022, with 33 observations. The data reached an all-time high of 0.600 % in 2022 and a record low of 0.100 % in 2003. Cuba CU: Prevalence of HIV: Total: % of Population Aged 15-49 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Cuba – Table CU.World Bank.WDI: Social: Health Statistics. Prevalence of HIV refers to the percentage of people ages 15-49 who are infected with HIV.;UNAIDS estimates.;Weighted average;

Source: The World Bank Last Updated: 10/26/2023 Database: World Development Indicators Series: Prevalence of HIV, total (% of population ages 15-49) Adults (ages 15+) and children (ages 0-14) newly infected with HIV Adults (ages 15-49) newly infected with HIV Antiretroviral therapy coverage (% of people living with HIV) Antiretroviral therapy coverage for PMTCT (% of pregnant women living with HIV) Children (0-14) living with HIV Children (ages 0-14) newly infected with HIV Incidence of HIV, ages 15-24 (per 1,000 uninfected population ages 15-24) Incidence of HIV, ages 15-49 (per 1,000 uninfected population ages 15-49) Incidence of HIV, all (per 1,000 uninfected population) Prevalence of HIV, female (% ages 15-24) Prevalence of HIV, male (% ages 15-24) Women's share of population ages 15+ living with HIV (%) Young people (ages 15-24) newly infected with HIV

https://datacatalog.worldbank.org/public-licenses#cc-by

Series Name: Number of new HIV infections per 1 000 uninfected population by sex and age (per 1 000 uninfected population)Series Code: SH_HIV_INCDRelease Version: 2021.Q2.G.03 This dataset is the part of the Global SDG Indicator Database compiled through the UN System in preparation for the Secretary-General's annual report on Progress towards the Sustainable Development Goals.Indicator 3.3.1: Number of new HIV infections per 1,000 uninfected population, by sex, age and key populationsTarget 3.3: By 2030, end the epidemics of AIDS, tuberculosis, malaria and neglected tropical diseases and combat hepatitis, water-borne diseases and other communicable diseasesGoal 3: Ensure healthy lives and promote well-being for all at all agesFor more information on the compilation methodology of this dataset, see https://unstats.un.org/sdgs/metadata/

This dataset provides detailed insights into the prevalence of HIV/AIDS among adults (ages 15–49) across various countries and regions. The data is primarily sourced from the CIA World Factbook and the UNAIDS AIDSinfo platform and reflects the most recent available estimates as of 2022–2024.

What’s Included:

Country/Region – The name of each nation or area.

Adult Prevalence of HIV/AIDS (%) – The percentage of adults estimated to be living with HIV.

Number of People with HIV/AIDS – Estimated count of people infected in each country.

Annual Deaths from HIV/AIDS – Estimated number of HIV/AIDS-related deaths per year.

Year of Estimate – The year the data was reported or estimated.

Key Highlights:

Global Prevalence: Around 0.7% of the global population was living with HIV in 2022, affecting nearly 39 million people.

Hotspots: The epidemic is most severe in Southern Africa, with countries like Eswatini, Botswana, Lesotho, and Zimbabwe reporting adult prevalence rates above 20%.

High Burden Countries:

South Africa: 17.3% prevalence, approximately 9.2 million infected

Tanzania: approximately 7.49 million

Mozambique: approximately 2.48 million

Nigeria: approximately 2.45 million (1.3% prevalence)

Notes:

Data may vary in accuracy and is subject to ongoing updates and verification.

Some entries include a dash ("-") where data was not published or available.

Countries with over 1% adult prevalence are categorized under Generalized HIV Epidemics (GHEs) by UNAIDS.

Health Nutrition and Population Statistics database provides key health, nutrition and population statistics gathered from a variety of international and national sources. Themes include global surgery, health financing, HIV/AIDS, immunization, infectious diseases, medical resources and usage, noncommunicable diseases, nutrition, population dynamics, reproductive health, universal health coverage, and water and sanitation.

No. of Deaths: Caused by: HIV Disease (Aids) data was reported at 547.000 Person in Sep 2024. This records a decrease from the previous number of 557.000 Person for Jun 2024. No. of Deaths: Caused by: HIV Disease (Aids) data is updated quarterly, averaging 558.000 Person from Mar 2017 (Median) to Sep 2024, with 30 observations. The data reached an all-time high of 659.000 Person in Mar 2018 and a record low of 461.000 Person in Sep 2020. No. of Deaths: Caused by: HIV Disease (Aids) data remains active status in CEIC and is reported by National Administrative Department of Statistics. The data is categorized under Global Database’s Colombia – Table CO.G012: Number of Deaths: Cause of Death.

Trinidad and Tobago TT: Prevalence of HIV: Total: % of Population Aged 15-49 data was reported at 1.200 % in 2016. This stayed constant from the previous number of 1.200 % for 2015. Trinidad and Tobago TT: Prevalence of HIV: Total: % of Population Aged 15-49 data is updated yearly, averaging 1.100 % from Dec 1990 (Median) to 2016, with 27 observations. The data reached an all-time high of 1.200 % in 2016 and a record low of 0.100 % in 1990. Trinidad and Tobago TT: Prevalence of HIV: Total: % of Population Aged 15-49 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Trinidad and Tobago – Table TT.World Bank: Health Statistics. Prevalence of HIV refers to the percentage of people ages 15-49 who are infected with HIV.; ; UNAIDS estimates.; Weighted Average;

Users can access data related to international women’s health as well as data on population and families, education, work, power and decision making, violence against women, poverty, and environment. Background World’s Women Reports are prepared by the Statistics Division of the United Nations Department for Economic and Social Affairs (UNDESA). Reports are produced in five year intervals and began in 1990. A major theme of the reports is comparing women’s situation globally to that of men in a variety of fields. Health data is available related to life expectancy, cause of death, chronic disease, HIV/AIDS, prenatal care, maternal morbidity, reproductive health, contraceptive use, induced abortion, mortality of children under 5, and immunization. User functionality Users can download full text or specific chapter versions of the reports in color and black and white. A limited number of graphs are available for download directly from the website. Topics include obesity and underweight children. Data Notes The report and data tables are available for download in PDF format. The next report is scheduled to be released in 2015. The most recent report was released in 2010.

Users can find data on a range of global health topics like mortality, the burden of disease, infectious diseases, risk factors and health expenditures. Background The Global Health Observatory (GHO) database is the World Health Organization's main health statistics repository. Data is available for 193 World Health Organization member states on topics including but not limited to: Health related millennium goals, mortality, immunization, nutrition, infectious disease, non- communicable disease, tobacco control, violence, injuries, alcohol, HIV/AIDS, tuberculosis, malaria, water and sanitation, maternal and reproductive health, cho lera, child health, child nutrition, and road safety. User FunctionalityUsers can generate tables and charts according to country or region, health indicator, and time period. Data can also be compared across countries. Data can be filtered, tabulated, charted, and downloaded into Excel statistical software. These data are also published in statistical reports covering topics including: Alcohol and health, Child health, Cholera, HIV/AIDS, Malaria, Maternal and reproductive heal th, Non-communicable diseases, Public health and environment, Road safety, Tuberculosis, Tobacco control. Data Notes Data are derived from surveillance and household surveys. Years in which data were collected is indicated with these health statistics. Information is available for each WHO member country and international region. The most recent data is available from 2009.

PurposeHIV/AIDS is a critical public health concern worldwide. This article investigated the spatial and temporal trends in HIV/AIDS burden from 1990 to 2019.MethodsData were extracted from the Global Burden of Disease (GBD) Study 2019. The estimated annual percentage change (EAPC) and the age-standardized rate (ASR) were used to quantify the change in trends at the global, regional, and national levels.ResultsIn terms of temporal trends, during the period 1990–2004, increasing trends in prevalence (EAPC = 7.47, 95% confidence interval [CI] 5.84, 9.12), death (EAPC = 10.85, 95% CI 8.90–12.84), and disability-adjusted life years (DALYs) (EAPC = 10.40, 95% CI 8.47–12.36) of HIV/AIDS were observed. During the period 2005–2019, the global trends in HIV/AIDS incidence, death, and DALYs of HIV/AIDS decreased, with the EAPCs of −2.68 (95% CI−2.82–−2.53), −6.73 (95% CI −6.98–−6.47), and −6.75 (95% CI −6.95–−6.54), respectively. However, the disease prevalence showed a slight increasing trend (EAPC = 0.71, 95% CI 0.54–0.87). In terms of spatial trends, over the past 15 years, trends in HIV/AIDS incidence of HIV/AIDS appeared upward in High-middle and High sociodemographic index (SDI) areas (EAPC = 6.51, 95% CI 5.50–7.53; EAPC = 2.31, 95% CI 2.02–2.60, respectively).ConclusionDecreasing trends in HIV/AIDS incidence, death, and DALYs have been observed worldwide over the past 15 years, especially in death and DALYs rates. However, the global population living with HIV/AIDS is still increasing. It is worth noting that an unfavorable trend emerged in High-middle and High SDI areas. Prevention and control of HIV/AIDS still need to be strengthened to counteract these concerning trends.

Health Nutrition and Population Statistics database provides key health, nutrition and population statistics gathered from a variety of international and national sources. Themes include global surgery, health financing, HIV/AIDS, immunization, infectious diseases, medical resources and usage, noncommunicable diseases, nutrition, population dynamics, reproductive health, universal health coverage, and water and sanitation.

The 2011 Uganda AIDS Indicator Survey (AIS) is a nationally representative, population-based, HIV serological survey. The survey was designed to obtain national and sub-national estimates of the prevalence of HIV and syphilis infection as well as information about other indicators of programme coverage, such as knowledge, attitudes, and sexual behaviour related to HIV/AIDS. Data collection took place from 8 February to the first few days of September 2011. The UAIS was implemented by the Ministry of Health. ICF International provided financial and technical assistance for the survey through a contract with USAID/Uganda. Financial and technical assistance was also provided by the U.S. Centers for Disease Control and Prevention (CDC). Financial support was provided by the Government of Uganda, the U.S. Agency for International Development (USAID), the President’s Emergency Fund for AIDS Relief (PEPFAR), the World Health Organisation (WHO), the UK Department for International Development (DFID), and the Danish International Development Agency (DANIDA) through the Partnership Fund. The Uganda Bureau of Statistics also partnered in the implementation of the survey. Central testing was conducted at the Uganda Virus Research Institute, with CDC conducting CD4 counts, polymerase chain reaction (PCR) testing for children, and quality control tests. The survey provided information on knowledge, attitudes, and behaviour regarding HIV/AIDS and indicators of coverage and access to other programmes, for example, HIV testing, access to antiretroviral therapy, services for treating sexually transmitted infections, and coverage of interventions to prevent motherto-child transmission of HIV. The survey also collected information on the prevalence of HIV and syphilis and their social and demographic variations in the country. The overall goal of the survey was to provide programme managers and policymakers involved in HIV/AIDS programmes with strategic information to effectively plan, implement, and evaluate HIV/AIDS interventions. The information obtained from the survey will help programme implementers to monitor and evaluate existing programmes and design new strategies for combating the HIV/AIDS epidemic in Uganda. The survey data will in addition be used to make population projections and to calculate indicators developed by the UN General Assembly Special Session (UNGASS), USAID, PEPFAR, the UNAIDS Programme, WHO, the Uganda Health Sector Strategic and Investment Plan, and the Uganda AIDS Commission. The specific objectives of the 2011 UAIS were to provide information on: • Prevalence and distribution of HIV and syphilis • Indicators of knowledge, attitudes, and behaviour related to HIV/AIDS and other sexually transmitted infections • HIV/AIDS programme coverage indicators • Levels of CD4 T-lymphocyte counts among HIV-positive adults to quantify HIV treatment needs and to calibrate model-based estimates • HIV prevalence that can be used to calibrate and improve the sentinel surveillance system • Risk factors for HIV and syphilis infections in Uganda.

Bulgaria BG: Prevalence of HIV: Total: % of Population Aged 15-49 data was reported at 0.100 % in 2022. This stayed constant from the previous number of 0.100 % for 2021. Bulgaria BG: Prevalence of HIV: Total: % of Population Aged 15-49 data is updated yearly, averaging 0.100 % from Dec 1990 (Median) to 2022, with 33 observations. The data reached an all-time high of 0.100 % in 2022 and a record low of 0.100 % in 2022. Bulgaria BG: Prevalence of HIV: Total: % of Population Aged 15-49 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Bulgaria – Table BG.World Bank.WDI: Social: Health Statistics. Prevalence of HIV refers to the percentage of people ages 15-49 who are infected with HIV.;UNAIDS estimates.;Weighted average;