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.

These data were reported to the NYC DOHMH by March 31, 2021 This dataset includes data on new diagnoses of HIV and AIDS in NYC for the calendar years 2016 through 2020. Reported cases and case rates (per 100,000 population) are stratified by United Hospital Fund (UHF) neighborhood, age group, and race/ethnicity. Note: - Cells marked "NA" cannot be calculated because of cell suppression or 0 denominator.

Analysis of ‘HIV AIDS Dataset’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from https://www.kaggle.com/imdevskp/hiv-aids-dataset on 13 February 2022.

--- Dataset description provided by original source is as follows ---

Context

In the time of epidemics, what is the status of HIV AIDS across the world, where does each country stands, is it getting any better. The data set should be helpful to explore much more about above mentioned factors.

Content

The data set contains data on

1. No. of people living with HIV AIDS
2. No. of deaths due to HIV AIDS
3. No. of cases among adults (19-45)
4. Prevention of mother-to-child transmission estimates
5. ART (Anti Retro-viral Therapy) coverage among people living with HIV estimates
6. ART (Anti Retro-viral Therapy) coverage among children estimates

Acknowledgements / Data Source

• WHO : https://www.who.int/hiv/data/en/
• UNESCO : https://data.unicef.org/resources/dataset/hiv-aids-statistical-tables/

Collection methodology

https://github.com/imdevskp/hiv_aids_who_unesco_data_cleaning

Cover Photo

Photo by Anna Shvets from Pexels https://www.pexels.com/photo/red-ribbon-on-white-surface-3900425/

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--- Original source retains full ownership of the source dataset ---

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.""

People aged 15 to 59 years seen at HIV services in the UK, expressed as a rate per 1,000 population.Data is presented by area of residence, and exclude people diagnosed with HIV in England who are resident in Wales, Scotland, Northern Ireland or abroad.RationaleThe geographical distribution of people seen for HIV care and treatment is not uniform across or within regions in England. Knowledge of local diagnosed HIV prevalence and identification of local risk groups can be used to help direct resources for HIV prevention and treatment.In 2008, http://www.bhiva.org/HIV-testing-guidelines.aspx recommended that Local Authority and NHS bodies consider implementing routine HIV testing for all general medical admissions as well as new registrants in primary care where the diagnosed HIV prevalence exceeds 2 in 1,000 population aged 15 to 59 years.In 2017, guidelines were updated by https://www.nice.org.uk/guidance/NG60 which is co-badged with Public Health England. This guidance continues to define high HIV prevalence local authorities as those with a diagnosed HIV prevalence of between 2 and 5 per 1,000 and extremely high prevalence local authorities as those with a diagnosed HIV prevalence of 5 or more per 1,000 people aged 15 to 59 years.When this is applied to national late HIV diagnosis data, it shows that two-thirds of late HIV diagnoses occur in high-prevalence and extremely-high-prevalence local authorities. This means that if this recommendation is successfully applied in high and extremely-high-prevalence areas, it could potentially affect two-thirds of late diagnoses nationally.Local authorities should find out their diagnosed prevalence published in UKHSA's http://fingertips.phe.org.uk/profile/sexualhealth , as well as that of surrounding areas and adapt their strategy for HIV testing using the national guidelines.Commissioners can use these data to plan and ensure access to comprehensive and specialist local HIV care and treatment for HIV diagnosed individuals according to the http://www.medfash.org.uk/uploads/files/p17abl6hvc4p71ovpkr81ugsh60v.pdf and http://www.bhiva.org/monitoring-guidelines.aspx .Definition of numeratorThe number of people (aged 15 to 59 years) living with a diagnosed HIV infection and accessing HIV care at an NHS service in the UK and who are resident in England.Definition of denominatorResident population aged 15 to 59.The denominators for 2011 to 2023 are taken from the respective 2011 to 2023 Office for National Statistics (ONS) revised population estimates from the 2021 Census.Further details on the ONS census are available from the https://www.ons.gov.uk/census .CaveatsData is presented by geographical area of residence. Where data on residence were unavailable, residence have been assigned to the local health area of care.Every effort is made to ensure accuracy and completeness of the data, including web-based reporting with integrated checks on data quality. The overall data quality is high as the dataset is used for commissioning purposes and for the national allocation of funding. However, responsibility for the accuracy and completeness of data lies with the reporting service.Data is as reported but rely on ‘record linkage’ to integrate data and ‘de-duplication’ to prevent double counting of the same individual. The data may not be representative in areas where residence information is not known for a significant proportion of people accessing HIV care.Data supplied for previous years are updated on an annual basis due to clinic or laboratory resubmissions and improvements to data cleaning. Data may therefore differ from previous publications.Values are benchmarked against set thresholds and categorised into the following groups: <2 (low), 2 to 5 (high) and≥5 (extremely high). These have been determined by developments in national testing guidelines.The data reported in 2020 and 2021 is impacted by the reconfiguration of sexual health services during the national response to COVID-19.

Human Immunodeficiency Virus (HIV) remains a significant public health concern, with adults being at greater risk. Thus, understanding the dynamics of HIV transmission is crucial for effective prevention and control strategies, hence the need for a continuous clinical survey of the patients’ records of diagnosis and treatment for HIV. The data include the quarterly records of 138 adults diagnosed with HIV at Osun State University Teaching Hospital, Nigeria which involves the number of adults tested positive and negative for each of the endogenous variables discussed below. Information was sought using a convenient sampling method, which entails careful selection of individual records based on availability. The data was grouped into quarterly records of the diagnosed adults, with an average age ranging between 26 years and 52 years, and spread between the years 2008 and 2021. The records comprise 72 Females and 66 Males while the presence of each symptom is coded as 1 and the absence coded as 0. The endogenous variables observed in the clinical records of the surveyed patients are Fever (F), Diarrhea (D), Abdominal pain (AP), Skin rash (SR), Mouth sour (MS), Cellulitis (C), Coughing with sputum (CS), Loss of appetite (LA), Genital infections (GI), Medical fitness (MF), Headache (H), Catarrh (CA), Weight Loss (WL), Excessive Sweat (ES), Mouth Sour (MS), and Body weakness (BW). The impacts of these aforementioned factors would be examined on the spread of HIV. The clinical survey revealed that 77 individuals (55.80%) did not experience fever, while 61 (44.20%) did. Diarrhea was reported by 39 participants (28.26%), leaving 99 (71.74%) without this symptom. Abdominal pain and cellulitis were both reported by only 4 individuals (2.90%), with 134 participants (97.10%) indicating no occurrences of these symptoms. In terms of medical fitness, 110 individuals (79.71%) reported no fitness issues, whereas 28 (20.29%) reported having some. Cough with sputum affected 50 participants (36.23%), while 88 (63.77%) did not report this symptom. Headaches were almost universally absent, with 137 individuals (99.28%) not experiencing any. Catarrh was present in 14 participants (10.14%), with 124 (89.86%) reporting no instances. Loss of appetite was reported by 5 individuals (3.62%), and skin rashes were observed in 28 participants (20.29%). Weight loss affected 49 individuals (35.51%), and excessive sweating was reported by 137 participants (99.28%). Mouth soreness was noted in 27 participants (19.57%), while genital infections were reported by 6 individuals (4.35%). Body weakness was reported by 49 participants (35.51%). In the age distribution, 56 individuals (40.58%) fall into the young adult’s category while 82 individuals (59.42%) are categorized as older adults. Notably, all participants in the study were confirmed to be HIV positive, emphasizing a focused analysis of this group’s health characteristics.

Spatial analysis at different levels can help understand spatial variation of human immunodeficiency virus (HIV) infection, disease drivers, and targeted interventions. Combining spatial analysis and the evaluation of the determinants of the HIV burden in Southern African countries is essential for a better understanding of the disease dynamics in high-burden settings.The study countries were selected based on the availability of demographic and health surveys (DHS) and corresponding geographic coordinates. We used multivariable regression to evaluate the determinants of HIV burden and assessed the presence and nature of HIV spatial autocorrelation in six Southern African countries.The overall prevalence of HIV for each country varied between 11.3% in Zambia and 22.4% in South Africa. The HIV prevalence rate was higher among female respondents in all six countries. There were reductions in prevalence estimates in most countries yearly from 2011 to 2020. The hotspot cluster findings show that the major cities in each country are the key sites of high HIV burden. Compared with female respondents, the odds of being HIV positive were lesser among the male respondents. The probability of HIV infection was higher among those who had sexually transmitted infections (STI) in the last 12 months, divorced and widowed individuals, and women aged 25 years and older.Our research findings show that analysis of survey data could provide reasonable estimates of the wide-ranging spatial structure of the HIV epidemic in Southern African countries. Key determinants such as individuals who are divorced, middle-aged women, and people who recently treated STIs, should be the focus of HIV prevention and control interventions. The spatial distribution of high-burden areas for HIV in the selected countries was more pronounced in the major cities. Interventions should also be focused on locations identified as hotspot clusters.

The ultimate goal of HIV treatment is to achieve viral suppression, which means the amount of HIV in the body is very low or undetectable. This is important for people with HIV to stay healthy, have improved quality of life, and live longer. People living with HIV who maintain viral suppression have effectively no risk of passing HIV to others. Texas DSHS is the source of this data. Diagnosed- received a diagnosis of HIV Linked to care*-visited an HIV heath care provider within 1 month (30 days) after learning they were HIV positive Received-** or were retained in care*** received medical care for HIV infection Viral suppression- their HIV “viral load” – the amount of HIV in the blood – was at a very low level.

This was a retrospective unmatched case control study, which targeted 583 (147 cases and 436 controls) HIV infected individuals attending HIV clinics at eleven USAID/SUSTAIN supported Ugandan RRH. The specific objectives were 1. To identify the foods commonly consumed by PLHIV attending HIV clinics at RRH in Uganda. 2. To compare dietary patterns of malnourished and non-malnourished HIV patients attending HIV clinics at RRH in Uganda. 3. To explore demographic, socio-economic and hospital care factors associated with dietary patterns among HIV patients attending HIV clinics at RRH in Uganda. 4. To identify and compare coping mechanisms during food scarcity between the malnourished and non-malnourished HIV patients attending HIV clinics at RRH in Uganda.

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.

The dataset collection consists of a table titled 'Cases of HIV Infection Transmission among Men Who Have Sex with Men per 100,000 Men in Finland'. This dataset collection is sourced from the web site of Sotkanet in Finland.

The dataset “Impact of HIV strategies for MSM” contains data obtained from an agent-based model. The model follows the sexual life of 20,000 men who have sex with men (MSM) in the Netherlands. Via sexual contacts, men may get infected with HIV or N. Gonorrhoeae (NG). The model simulates sexual behaviour, demography, and the course of HIV or NG infection (for those who have been infected). The data from the model are therefore data of “fictitious” (simulated) individuals, not of real individuals. The course of HIV infection was modelled using data from the national database of HIV-positive individuals in the Netherlands (Source: Stichting HIV Monitoring). Parameters relating to sexual behaviour were obtained from data from the Amsterdam Cohort Study and the Network Study among MSM in Amsterdam. The model was calibrated to data on annual HIV diagnoses in 2008-2014 (from Stichting HIV Monitoring) and gonorrhoea positivity in 2009-2014 (data obtained from the National Database of STI Clinics in the Netherlands (SOAP)). Model outcomes include the annual numbers of MSM getting infected with HIV; HIV-positive MSM getting diagnosed, entering care, or starting treatment; MSM developing AIDS; MSM getting infected with NG; MSM treated for gonorrhoea; HIV tests, NG tests, etc. With the model, we calculated these numbers for the years 2018-2027, for the situation with the current testing rates and without PrEP. Subsequently we calculated these numbers with increased HIV/STI testing: a small, a moderate, and a high increase in testing among all MSM or only among MSM in specific subgroups of MSM. Finally, the calculations were repeated accounting for a nationwide PrEP programme for MSM at high risk to acquire HIV.

The heterosexual risk group has become the largest HIV infected group in the United Kingdom during the last 10 years, but little is known of the network structure and dynamics of viral transmission in this group. The overwhelming majority of UK heterosexual infections are of non-B HIV subtypes, indicating viruses originating among immigrants from sub-Saharan Africa. The high rate of HIV evolution, combined with the availability of a very high density sample of viral sequences from routine clinical care has allowed the phylodynamics of the epidemic to be investigated for the first time. Sequences of the viral protease and partial reverse transcriptase coding regions from 11,071 patients infected with HIV of non-B subtypes were studied. Of these, 2774 were closely linked to at least one other sequence by nucleotide distance. Including the closest sequences from the global HIV database identified 296 individuals that were in UK-based groups of 3 or more individuals. There were a total of 8 UK-based clusters of 10 or more, comprising 143/2774 (5%) individuals, much lower than the figure of 25% obtained earlier for men who have sex with men (MSM). Sample dates were incorporated into relaxed clock phylogenetic analyses to estimate the dates of internal nodes. From the resulting time-resolved phylogenies, the internode lengths, used as estimates of maximum transmission intervals, had a median of 27 months overall, over twice as long as obtained for MSM (14 months), with only 2% of transmissions occurring in the first 6 months after infection. This phylodynamic analysis of non-B subtype HIV sequences representing over 40% of the estimated UK HIV-infected heterosexual population has revealed heterosexual HIV transmission in the UK is clustered, but on average in smaller groups and is transmitted with slower dynamics than among MSM. More effective intervention to restrict the epidemic may therefore be feasible, given effective diagnosis programmes.

Much of the information on national HIV prevalence in Tanzania derives from surveillance of HIV in special populations, such as women attending antenatal clinics and blood donors. For example, Mainland Tanzania currently maintains a network of 134 antenatal care (ANC) sites from which HIV prevalence estimates are generated. However, these surveillance data do not provide an estimate of the HIV prevalence among the general population. HIV prevalence is higher among individuals who are employed (6 percent) than among those who are not employed (3 percent) and is higher in urban areas than in rural areas (7percent and 4 percent, respectively). In Mainland Tanzania, HIV prevalence is markedly higher than in Zanzibar (5 percent versus 1 percent). Differentials by region are large. Among regions on the Mainland,Njombe has the highest prevalence estimate (15 percent), followed by Iringa and Mbeya (9 percent each);Manyara and Tanga have the lowest prevalence (2 percent). Among the five regions that comprise Zanzibar, all have HIV prevalence estimates at 1 percent or below. Consistent with the overall national estimate among men and women, HIV prevalence is higher among women than men in nearly all regions of Tanzania.

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

This dataset contains surveillance study estimates for population size, HIV prevalence, and ART coverage among female sex workers (FSW), men who have sex with men (MSM), people who inject drugs (PWID), and transgender men and women (TGM/W) from 2010-2023. It was created to support the UNAIDS Estimates Key Population Workbook for use by HIV estimates teams in sub-Saharan Africa. Key population surveillance reports, including Ministry of Health-led biobehavioural surveys, mapping studies, and academic studies were used to populate the database.

The dataset was populated using existing key population size estimate databases including:

UNAIDS Key Population Atlas

US Centers for Disease Control and Prevention surveillance database

Global Fund against HIV/AIDS, TB, and Malaria surveillance database

Global.HIV database

Systematic review databases among MSM (Stannah et al, 2019 and Stannah et al., 2023) and PWID (Degenhardt et al., 2023)

and was additionally supplemented by a literature review of peer-reviewed and grey literature sources.

The data can be explored in this web application and the accompanying manuscript can be found here

Minimal dataset of people-living with HIV of the manuscript "Implementation of the advanced HIV disease care package with point-of-care CD4 during tuberculosis case finding: a mixed-methods evaluation"

A multi-site study of 13-24 year-old Hispanic/Latino men who have sex with men, heterosexual men, and heterosexual women. Comparisons were made between alternative venue-based testing (AVT) and social and sexual network-based interviewing and HIV testing (SSNIT) strategies, assessing the most effective means for identifying undiagnosed HIV infection in young, at-risk Hispanics/Latinos. Study participants completed an audio computer-assisted self-interview (ACASI) and HIV screening. All participants with presumptive HIV+ screening results were referred for confirmatory testing and linkage to HIV medical care. In addition, a subset of SSNIT participants went on to recruit members of their social and sexual network who were eligible for study participation.

The Find Ryan White HIV/AIDS Medical Care Providers tool is a locator that helps people living with HIV/AIDS access medical care and related services. Users can search for Ryan White-funded medical care providers near a specific complete address, city and state, state and county, or ZIP code. Search results are sorted by distance away and include the Ryan White HIV/AIDS facility name, address, approximate distance from the search point, telephone number, website address, and a link for driving directions. HRSA's Ryan White program funds an array of grants at the state and local levels in areas where most needed. These grants provide medical and support services to more than a half million people who otherwise would be unable to afford care.