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.

The AIDS Public Information Data Set (APIDS) for years 1981-2002 on CDC WONDER online database contains counts of AIDS (Acquired Immune Deficiency Syndrome) cases reported by state and local health departments, by demographics; location (region and selected metropolitan areas); case-definition; month/year and quarter-year of diagnosis, report, and death (if applicable); and HIV exposure group (risk factors for AIDS). Data are produced by the US Department of Health and Human Services (US DHHS), Public Health Service (PHS), Centers for Disease Control and Prevention (CDC), National Center for HIV, STD and TB Prevention (NCHSTP), Division of HIV/AIDS Prevention (DHP).

This dataset contains death counts and crude rates by region, age group, and selected cause of death. For more information, check out: http://www.health.ny.gov/statistics/vital_statistics/, or go to the "About" tab.

Contents

HIV/AIDS** data from the HIV Surveillance Annual Report * Note: Data reported to the HIV Epidemiology and Field Services Program by June 30, 2016. All data shown are for people ages 13 and older. Borough-wide and citywide totals may include cases assigned to a borough with an unknown UHF or assigned to NYC with an unknown borough, respectively. Therefore, UHF totals may not sum to borough totals and borough totals may not sum to citywide totals."

Dataset has 18 features including:

Year, Borough, UHF, Gender, Age, Race, HIV diagnoses, HIV diagnosis rate, Concurrent diagnoses, % linked to care within 3 months, AIDS diagnoses, AIDS diagnosis rate, PLWDHI prevalence, % viral suppression, Deaths, Death rate, HIV-related death rate, Non-HIV-related death rate

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

Statistics relating to HIV infection

This dataset contains death counts, crude rates and adjusted rates for selected causes of death by county and region. For more information, check out: http://www.health.ny.gov/statistics/vital_statistics/, or go to the "About" tab.

Dataset refers to the Statistics Relating to Notification of HIV Aids Cases and Deaths in Mauritius for the year 2000 to 2021

This is an extract of Causes of death since 1997 to 2012 for HIV /Aids which includes B20, B21, B22, B23, B24 (according with the ICD-10 code).

This dataset is about countries per year in Jordan. It has 64 rows. It features 4 columns: country, incidence of HIV, and death rate.

ART not only saves lives but also gives a chance for people living with HIV/AIDS to live long lives. Without ART very few infected people survive beyond ten years.1

Today, a person living in a high-income country who started ART in their twenties can expect to live for another 46 years — that is well into their 60s.2

While the life expectancy of people living with HIV/AIDS in high-income countries has still not reached the life expectancy of the general population, we are getting closer to this goal.3

The combination of antiretroviral drugs which make-up ART have progressively improved. Recent research shows that a person who started ART in the late 1990s would be expected to live ten years less than a person who started ART in 2008.4 This increase goes beyond the general increase in life expectancy in that period and reflects the improvements in ART — fewer side effects, more people following the prescribed treatment, and more support for the people in need of ART.

Infection with HIV (human immunodeficiency virus) can lead to AIDS (acquired immunodeficiency syndrome). AIDS results in a gradual and persistent decline and failure of the immune system, resulting in a heightened risk of life-threatening infection and cancers.

In the majority of cases, HIV is a sexually transmitted infection. However, HIV can also be transmitted from mother to child, during pregnancy or childbirth, or through breastfeeding. Non-sexual transmission can also occur by sharing injection equipment such as needles.

Other research and writing on HIV/AIDS on Our World in Data:

Antiretroviral therapy has saved millions of lives from AIDS and could save more See all interactive charts on HIV/AIDS ↓

HIV/AIDS is one of the world's most fatal infectious disease More than three-quarters of a million people die from HIV/AIDS each year; in some countries, it's the leading cause of death HIV/AIDS is one of the world's most fatal infectious diseases – particularly across Sub-Saharan Africa, where the disease has had a massive impact on health outcomes and life expectancy in recent decades.

The Global Burden of Disease is a major global study on the causes of death and disease published in the medical journal The Lancet.1 These estimates of the annual number of deaths by cause are shown here. This chart shows the global total but can be explored for any country or region using the "Change country" button.

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

Death rate of a population adjusted to a standard age distribution. As most causes of death vary significantly with people's age and sex, the use of standardised death rates improves comparability over time and between countries, as they aim at measuring death rates independently of different age structures of populations. The standardised death rates used here are calculated on the basis of a standard European population (defined by the World Health Organization). Detailed data for 65 causes of death are available in the database (under the heading 'Data').

This dataset is about regions in the Americas. It has 4 rows. It features 3 columns: incidence of HIV, and death rate.

HIV notification rate per million population

Distribution of Singapore Residents with HIV/AIDS by Mode of Transmission

Distribution of Singapore Residents with HIV/AIDS by Gender

Distribution of Singapore Residents with HIV/AIDS by Ethnic Groups

HIV/AIDS yearly statistics in Hong Kong 1984 - 2023

HIV/AIDS data from the HIV Surveillance Annual Report Data reported to the HIV Epidemiology Program by March 31, 2022. All data shown are for people ages 18 and older. Borough-wide and citywide totals may include cases assigned to a borough with an unknown UHF or assigned to NYC with an unknown borough, respectively. Therefore, UHF totals may not sum to borough totals and borough totals may not sum to citywide totals.""

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.