This data set includes tables on persons living with HIV/AIDS, newly diagnosed HIV cases and all cause deaths in HIV/AIDS cases by gender, age, race/ethnicity and transmission category. In all tables, cases are reported as of December 31 of the given year, as reported by January 9, 2019, to allow a minimum of 12 months reporting delay. Gender is determined by both current gender and sex at birth variables; transgender values are assigned when current gender is identified as "Transgender" or when a discrepancy is identified between a person's sex at birth and their current gender (e.g., cases where sex at birth is "Male" and current gender is "Female" will become Transgender: Male to Female.) Prior to 2003, Asian and Native Hawaiian/Pacific Islanders were classified as one combined group. In order to present these race/ethnicities separately, living cases recorded under this combined classification were split and redistributed according to their expected proportional population representation estimated from post-2003 data.

HIV/AIDS yearly statistics in Hong Kong 1984 - 2023

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.

Rate: Number of deaths (per 100,000) due to HIV disease

Definition: Deaths with human immunodeficiency virus (HIV) disease as the underlying cause (ICD-10 codes: B20-B24).

Data Sources:

(1) Centers for Disease Control and Prevention, National Center for Health Statistics

(2) Death Certificate Database, Office of Vital Statistics and Registry, New Jersey Department of Health

(3) Population Estimates, State Data Center, New Jersey Department of Labor and Workforce Development

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/

BO: Prevalence of HIV: Female: % Aged 15-24 data was reported at 0.100 % in 2022. This stayed constant from the previous number of 0.100 % for 2021. BO: Prevalence of HIV: Female: % Aged 15-24 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. BO: Prevalence of HIV: Female: % Aged 15-24 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: Social: Health Statistics. Prevalence of HIV, female is the percentage of females who are infected with HIV. Youth rates are as a percentage of the relevant age group.;UNAIDS estimates.;Weighted average;In many developing countries most new infections occur in young adults, with young women especially vulnerable.

This shapefile provides HIV statistics by state that can be used in conjunction with the co-morbidities risk profile to provide more nuance on levels of risk by state. Note that values of 0 mean there is no data for that particular state.The source of data for HIV prevalence rates is the Nigeria Institute for Health Metrics and Evaluation (IHME), HIV Prevalence Geospatial Estimates 2000-2017.

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

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

This map displays the percentage of people ages 15+ with HIV that are female from the 2013 to 2014 dataset. According to the World Bank: "HIV prevalence rates reflect the rate of HIV infection in each country's population. Low national prevalence rates can be misleading, however. They often disguise epidemics that are initially concentrated in certain localities or population groups and threaten to spill over into the wider population. In many developing countries most new infections occur in young adults, with young women especially vulnerable. Data on HIV are from the Joint United Nations Programme on HIV/AIDS (UNAIDS). Changes in procedures and assumptions for estimating the data and better coordination with countries have resulted in improved estimates of HIV and AIDS. The models, which are routinely updated, track the course of HIV epidemics and their impact, making full use of information in HIV prevalence trends from surveillance data as well as survey data. The models take into account reduced infectivity among people receiving antiretroviral therapy (which is having a larger impact on HIV prevalence and allowing HIV-positive people to live longer) and allow for changes in urbanization over time in generalized epidemics. The estimates include plausibility bounds, which reflect the certainty associated with each of the estimates."Source: The World Bank

Sweden SE: Prevalence of HIV: Male: % Aged 15-24 data was reported at 0.100 % in 2016. This stayed constant from the previous number of 0.100 % for 2015. Sweden SE: Prevalence of HIV: Male: % Aged 15-24 data is updated yearly, averaging 0.100 % from Dec 1990 (Median) to 2016, with 27 observations. The data reached an all-time high of 0.100 % in 2016 and a record low of 0.100 % in 2016. Sweden SE: Prevalence of HIV: Male: % Aged 15-24 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Sweden – Table SE.World Bank: Health Statistics. Prevalence of HIV, male is the percentage of males who are infected with HIV. Youth rates are as a percentage of the relevant age group.; ; UNAIDS estimates.; Weighted average; In many developing countries most new infections occur in young adults, with young women being especially vulnerable.

Kenya KE: Incidence of HIV: % of Uninfected Population Aged 15-49 data was reported at 0.250 % in 2016. This records a decrease from the previous number of 0.270 % for 2015. Kenya KE: Incidence of HIV: % of Uninfected Population Aged 15-49 data is updated yearly, averaging 0.420 % from Dec 1990 (Median) to 2016, with 27 observations. The data reached an all-time high of 1.860 % in 1992 and a record low of 0.250 % in 2016. Kenya KE: Incidence of HIV: % of Uninfected Population Aged 15-49 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s Kenya – Table KE.World Bank: Health Statistics. Number of new HIV infections among uninfected populations ages 15-49 expressed per 100 uninfected population in the year before the period.; ; UNAIDS estimates.; Weighted Average;

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.

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.

Note:P1: before intervention vs after intervention in middle school students’ HIV/AIDS knowledge awareness rate;P2: before intervention vs after intervention in high school students’ HIV/AIDS knowledge awareness rate;P3: middle school vs high school before intervention about students’ HIV/AIDS knowledge awareness rate;P4: middle school vs high school after intervention about students’ HIV/AIDS knowledge awareness rate;

aNew diagnoses of AIDS in Australia, reported by 31 March 2012. AIDS notifications are accepted as being an incomplete record of AIDS diagnoses in Australia in 2010.bThis dataset is not nationally representative; it includes data from 7 of the 13 provinces and territories. The case definition for AIDS in Canada is based on confirmed HIV diagnosis and presence/diagnosis of an AIDS-defining condition (no criteria for CD4 count are included in Canada’s AIDS case definition). Transmission category information was not available for one of the jurisdictions reported here, which accounts for the small cell sizes under the various transmission categories.cData for the whole country, adjusted for under-reporting and reporting delays. Data reported as of 30 June, 2011.dMSM, men who have sex with men; IDU, injection drug use.

Explore World Bank Health, Nutrition and Population Statistics dataset featuring a wide range of indicators such as School enrollment, UHC service coverage index, Fertility rate, and more from countries like Bahrain, China, India, Kuwait, Oman, Qatar, and Saudi Arabia.

School enrollment, tertiary, UHC service coverage index, Wanted fertility rate, People with basic handwashing facilities, urban population, Rural population, AIDS estimated deaths, Domestic private health expenditure, Fertility rate, Domestic general government health expenditure, Age dependency ratio, Postnatal care coverage, People using safely managed drinking water services, Unemployment, Lifetime risk of maternal death, External health expenditure, Population growth, Completeness of birth registration, Urban poverty headcount ratio, Prevalence of undernourishment, People using at least basic sanitation services, Prevalence of current tobacco use, Urban poverty headcount ratio, Tuberculosis treatment success rate, Low-birthweight babies, Female headed households, Completeness of birth registration, Urban population growth, Antiretroviral therapy coverage, Labor force, and more.

Bahrain, China, India, Kuwait, Oman, Qatar, Saudi Arabia

Follow data.kapsarc.org for timely data to advance energy economics research.

This table presents a wide variety of historical data in the field of health, lifestyle and health care. Figures on births and mortality, causes of death and the occurrence of certain infectious diseases are available from 1900, other series from later dates. In addition to self-perceived health, the table contains figures on infectious diseases, hospitalisations per diagnosis, life expectancy, lifestyle factors such as smoking, alcohol consumption and obesity, and causes of death. The table also gives information on several aspects of health care, such as the number of practising professionals, the number of available hospital beds, nursing day averages and the expenditures on care. Many subjects are also covered in more detail by data in other tables, although sometimes with a shorter history. Data on notifiable infectious diseases and HIV/AIDS are not included in other tables.

Data available from: 1900

Status of the figures:

2024: The available figures are definite. 2023: Most available figures are definite. Figures are provisional for: - occurrence of infectious diseases; - expenditures on health and welfare; - perinatal and infant mortality. 2022: Most available figures are definite. Figures are provisional for: - occurrence of infectious diseases; - diagnoses at hospital admissions; - number of hospital discharges and length of stay; - number of hospital beds; - health professions; - expenditures on health and welfare. 2021: Most available figures are definite. Figures are provisional for: - occurrence of infectious diseases; - expenditures on health and welfare. 2020 and earlier: Most available figures are definite. Due to 'dynamic' registrations, figures for notifiable infectious diseases, HIV, AIDS remain provisional.

Changes as of 18 december 2024: - Due to a revision of the statistics Health and welfare expenditure 2021, figures for expenditure on health and welfare have been replaced from 2021 onwards. - Revised figures on the volume index of healthcare costs are not yet available, these figures have been deleted from 2021 onwards.

The most recent available figures have been added for: - live born children, deaths; - occurrence of infectious diseases; - number of hospital beds; - expenditures on health and welfare; - perinatal and infant mortality; - healthy life expectancy; - causes of death.

When will new figures be published? July 2025.

Percentages of MSM newly diagnosed with HIV infection by age and race/ethnicity, 2016, Santa Clara County. Source: Santa Clara County Public Health Department, enhanced HIV/AIDS reporting system (eHARS), data as of 4/30/2017. METADATA:Notes (String): Lists table title, notes and sourcesCategory (String): Lists the category representing the data: Age group: 13-24, 25-29, 30-39, 40-49, 50 and older; race/ethnicity:Asian/Pacific Islander, Black/African American, Latino, White (non-Hispanic White only), Other/Unknown.Percentage (Numeric): Percentage of MSM diagnosed with HIV in a particular category among all MSM diagnoses

Data Series: Number of new HIV infections per 1,000 uninfected population, by sex, age and key populations Indicator: III.8 - Number of new HIV infections per 1,000 uninfected population, by sex, age and key populations Source year: 2022 This dataset is part of the Minimum Gender Dataset compiled by the United Nations Statistics Division. Domain: Health and related services