In 2022, approximately *** million people were living with HIV in India. However, there has been a constant decrease in the number of people living with HIV (PLHIV) since 2003, and from 2008 onward, there have been less than ***** million PLHIV yearly.

HIV risk-groups

India’s HIV epidemic is the third-largest in the world. However, this is primarily concentrated among key populations who are at a higher risk of contracting the disease. One of the main drivers of this is unprotected sex among female sex workers and their clients, partners, and spouses. Injecting drugs are also becoming one of the common ways through which HIV can be transmitted due to the reuse of needles. In addition, the prevalence of HIV is higher among men than women. This can be attributed to the increase in the share of men who have sex with men, migrant workers, and drug use injections.

Sex-workers

While prostitution is considered legal in India, all activities associated with running brothels or sex trafficking are prohibited. As a result, there is severe police activity targeting sex workers, with routine raids in areas with brothels justified by related laws. A recent study in Andhra Pradesh suggested a positive correlation between police abuse and an increased risk of HIV along with inconsistency in the usage of condoms. It is not uncommon that stigma and discrimination against sex-workers limit their access to decent healthcare in India.

In 2021, India reported an HIV prevalence rate of nearly **** percent among injecting drug users, which was the highest rate among ***** selected high risk population groups across the country. Meanwhile, the prevalence rate among Hijra or Transgender people amounted to approximately *** percent.

In 2023, India reported an estimate of ** thousand new cases of HIV infections across the country. Male population newly infected with HIV amounted to just above ** thousand, accounting for approximately ** percent of HIV-infected population in India.

Forecast: Total HIV Incidence Rate in India 2023 - 2027 Discover more data with ReportLinker!

Forecast: Number of Deaths Due to Tuberculosis (Excluding HIV Cases) in India 2023 - 2027 Discover more data with ReportLinker!

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

As of 2023, India reported an estimate of above ** thousand cases of HIV infections in children across the country. Male children living with HIV amounted to just above ** thousand, accounting for approximately ** percent of HIV-infected children in India.

Forecast: Number of Deaths Due to Tuberculosis (Excluding HIV Cases) in India 2022 - 2026 Discover more data with ReportLinker!

• Dataset Description: This dataset contains detailed information about HIV patients in India. The data is intended to assist in research related to the treatment, progression, and demographic factors that influence HIV management and outcomes. The information was collected from various regions across India and includes patient-specific health indicators, treatment regimens, and socio-demographic details.

  • Data Collection: The dataset includes data from a range of HIV patients diagnosed across different periods. The patients are monitored for various health metrics, including CD4 count, viral load, adherence to antiretroviral therapy (ART), and follow-up visits. Additionally, demographic variables such as age, gender, region, employment, and education are included to allow for comprehensive analysis.

*Size of the Dataset:

-> Number of Entries:** 17,686 -> Number of Variables:** 16

India has seen a gradual improvement in HIV infection rates, with the number of new HIV infections per 1,000 uninfected population in India declining from 0.06 in 2015 to 0.05 in 2021. Mizoram consistently reported the highest rates, decreasing from 1.62 to 1.31 during this period, followed by Nagaland, which also showed improvement from 0.72 to 0.51. States like Punjab and Gujarat demonstrated significant progress, reducing their rates to 0.05 and 0.04, respectively. However, concerning upward trends were observed in Tripura and Meghalaya. Despite Kerala maintaining one of the lowest rates, HIV cases in India per year remain a critical public health concern.

In 2024, there were *** babies in India who tested positive for HIV at the age of 18 months. According to the source, India reported a total of *** HIV infected babies initiated on antiretroviral therapy (ART) in that same year.

BackgroundA major barrier to achieving ambitious targets for global control of HIV and hepatitis C virus (HCV) is low levels of awareness of infection among key populations such as men who have sex with men (MSM) and people who inject drugs (PWID). We explored the potential of a strategy routinely used for surveillance in these groups, respondent-driven sampling (RDS), to be used as an intervention to identify HIV- and HCV-infected PWID and MSM who are unaware of their status and those who are viremic across 26 Indian cities at various epidemic stages.Methods and findingsData were collected as part of the baseline assessment of an ongoing cluster-randomized trial. RDS was used to accrue participants at 27 sites (15 PWID sites and 12 MSM sites) selected to reflect varying stages of the HIV epidemic among MSM and PWID in India. A total of 56 seeds recruited a sample of 26,447 persons (approximately 1,000 participants per site) between October 1, 2012, and December 19, 2013. Across MSM sites (n = 11,997), the median age was 25 years and the median number of lifetime male partners was 8. Across PWID sites (n = 14,450), 92.4% were male, the median age was 30 years, and 87.5% reported injection in the prior 6 months. RDS identified 4,051 HIV-infected persons, of whom 2,325 (57.4%) were unaware of their HIV infection and 2,816 (69.5%) were HIV viremic. It also identified 5,777 HCV-infected persons, of whom 5,337 (92.4%) were unaware that they were infected with HCV and 4,728 (81.8%) were viremic. In the overall sample (both MSM and PWID), the prevalence of HIV-infected persons who were unaware of their status increased with sampling depth, from 7.9% in participants recruited in waves 1 through 5 to 12.8% among those recruited in waves 26 and above (p-value for trend < 0.001). The overall detection rate of people unaware of their HIV infection was 0.5 persons per day, and the detection rate of HIV-infected persons with viremia (regardless of their awareness status) was 0.7 per day. The detection rate of HIV viremic individuals was positively associated with underlying HIV prevalence and the prevalence of HIV viremia (linear regression coefficient per 1-percentage-point increase in prevalence: 0.05 and 0.07, respectively). The median detection rate of PWID who were unaware of their HCV infection was 2.5 per day. The cost of identifying 1 unaware HIV-infected individual ranged from US$51 to US$2,072 across PWID sites and from US$189 to US$5,367 across MSM sites. The mean additional cost of identifying 1 unaware HCV-infected PWID was US$13 (site range: US$7–US$140). Limitations of the study include the exclusivity of study sites to India, lack of prior HIV/HCV diagnosis confirmation with clinic records, and lack of cost data from other case-finding approaches commonly used in India.ConclusionsIn this study, RDS was able to rapidly identify at nominal cost a substantial number of unaware and viremic HIV-infected and HCV-infected individuals who were currently not being reached by existing programs and who were at high risk for transmission. Combining RDS (or other network-driven recruitment approaches) with strategies focused on linkage to care, particularly in high-burden settings, may be a viable option for achieving the 90-90-90 targets in key populations in resource-limited settings.

India IN: Newly Infected with HIV: Children: Aged 0-14 data was reported at 3,700.000 Number in 2017. This records a decrease from the previous number of 4,400.000 Number for 2016. India IN: Newly Infected with HIV: Children: Aged 0-14 data is updated yearly, averaging 10,450.000 Number from Dec 1990 (Median) to 2017, with 28 observations. The data reached an all-time high of 24,000.000 Number in 1998 and a record low of 2,500.000 Number in 1990. India IN: Newly Infected with HIV: Children: Aged 0-14 data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s India – Table IN.World Bank: Health Statistics. Number of children (ages 0-14) newly infected with HIV.; ; UNAIDS estimates.; ;

Forecast: Number of Incident Tuberculosis Cases (Including HIV-Positive Cases) in India 2023 - 2027 Discover more data with ReportLinker!

In 2023, India reported an estimate of ** thousand annual AIDS related deaths (ARD) across the country. Male deaths from HIV/AIDS amounted to nearly ** thousand, accounting for approximately ** percent of AIDS related deaths in India that year.

In 2022, India recorded ** thousand new HIV infections. There has been a steady decrease in the number of new HIV infections in the country since 2010, when India had recorded *** thousand new HIV infections.

Financial overview and grant giving statistics of Solidarity and Action Against the Hiv Infection in India Inc.

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

HIV and AIDS Clinical Trials Market Outlook

The global HIV and AIDS clinical trials market size was valued at approximately USD 2.6 billion in 2023 and is anticipated to reach USD 4.3 billion by 2032, growing at a compound annual growth rate (CAGR) of 5.8% during the forecast period. This market growth can be attributed to the increasing prevalence of HIV/AIDS, significant advancements in treatment methodologies, and rising investments in research and development activities across the globe. As the medical community continues to advance in the understanding and treatment of HIV and AIDS, the clinical trials market is expected to witness robust growth, driven by technological innovations and increasing support from government and non-government organizations.

One of the primary growth factors of the HIV and AIDS clinical trials market is the increasing global prevalence of HIV/AIDs, which continues to be a major public health concern. According to UNAIDS, there were approximately 38 million people living with HIV worldwide in 2022, highlighting the urgent need for effective treatment and prevention strategies. This ongoing public health challenge has catalyzed substantial investments in clinical trials aimed at discovering new therapies and improving existing treatment regimens. Governments, philanthropic organizations, and pharmaceutical companies are actively supporting these initiatives, further fueling market growth.

Another significant growth factor is the continuous advancement in medical technology and drug development processes. The advent of novel drug delivery systems, such as long-acting injectable formulations and pre-exposure prophylaxis (PrEP), has revolutionized the landscape of HIV treatment and prevention. Additionally, the development of antiretroviral therapies (ART) has significantly improved the life expectancy and quality of life for individuals living with HIV. These advancements have spurred a surge in clinical trials aimed at refining these therapies and exploring new treatment modalities, thereby driving market expansion.

The growing focus on personalized medicine is also propelling the market forward. Personalized medicine aims to tailor treatment based on individual genetic profiles and disease characteristics, ensuring more effective and targeted therapies. This approach has gained traction in the field of HIV research, where understanding the genetic makeup of both the virus and the host can lead to more effective treatments. Consequently, personalized medicine is becoming a cornerstone of clinical trial designs, further boosting the market.

From a regional perspective, North America is expected to hold a dominant share of the HIV and AIDS clinical trials market due to the presence of leading research institutions, substantial funding from government and non-government organizations, and advanced healthcare infrastructure. Europe follows closely, driven by a similar set of factors. Meanwhile, the Asia Pacific region is anticipated to witness the highest growth rate, propelled by increasing healthcare expenditure, rising awareness, and escalating HIV prevalence in countries like India and China.

Phase Analysis

The HIV and AIDS clinical trials market is segmented by phase, including Phase I, Phase II, Phase III, and Phase IV trials. Each phase plays a crucial role in the development and approval of new therapies. Phase I trials, typically involving a small group of healthy volunteers or patients, focus on assessing the safety, tolerability, and optimal dosing of new drugs. These trials are fundamental in establishing the initial pharmacokinetic and pharmacodynamic profiles of the investigational drugs. Although Phase I trials involve a limited number of participants, they are critical for paving the way for subsequent trial phases.

Phase II trials involve a larger group of participants and aim to provide preliminary data on the efficacy of the new treatment while continuing to monitor its safety. These trials are essential for determining the therapeutic potential of the drug and identifying any adverse effects that may not have been apparent in Phase I trials. The data obtained from Phase II trials are crucial for designing Phase III trials and refining the overall clinical development strategy. As the HIV and AIDS clinical trials market grows, Phase II trials are witnessing increased attention and investment, given their pivotal role in the development pipeline.

Phase III trials are expansive, involving a large cohort of participants to confirm the drug’s efficacy, monitor side effects, and c

Table of quotations from the qualitative study on the use of telemedicine (TM) for children living with HIV/AIDS (CLHA), Maharashtra, India.