Integrated Behavioral and Biological Surveillance Among People Living With HIV Visiting the Antiretroviral Therapy Centers in India: Protocol for a Cross-Sectional Surveillance
Bibliographic record
Abstract
BACKGROUND: The estimated number of people living with HIV (PLHIV) in India in 2023 is 2.54 million (range 2.16-3.03 million). With the initiation of antiretroviral therapy (ART) and the "Test and Treat" policy, the life expectancy of PLHIV on ART has substantially increased, consequently leading to a higher rate of comorbidities among PLHIV. The Joint United Nations Programme on HIV/AIDS (UNAIDS) 2025 targets aim for about 90% of PLHIV to have access to integrated and comprehensive health care services, with a concerted effort to reach the End of AIDS by 2030. Hence, the National Integrated Bio-Behavioral Surveillance (IBBS) among PLHIV (IBBS-PLHIV) has been implemented for the first time in India to establish a baseline understanding of the prevalence of sexually transmitted infections (STIs), noncommunicable diseases (NCDs), and related risk behaviors among PLHIV. OBJECTIVE: The primary aim of IBBS-PLHIV is to estimate the levels of HIV-related risk behaviors and the prevalence of other STIs and NCDs among PLHIV. The specific objectives are identifying the levels of HIV-related sexual and injecting risk behaviors; estimating the prevalence of STIs such as syphilis, hepatitis B virus, and hepatitis C virus; estimating the prevalence of NCDs such as diabetes and hypertension; understanding the lifestyle and behavioral risks associated with NCDs; and assessing the levels of violence, stigma, and discrimination experienced by PLHIV. METHODS: IBBS-PLHIV will be a cross-sectional, biennial surveillance among PLHIV aged 15 years or older. The first round will be implemented at 120 ART centers across 28 states, accounting for approximately 95% of the total estimated PLHIV. Consenting, eligible PLHIV will be recruited through consecutive sampling. The overall sample size at each ART center is approximately 225, and the surveillance period is 3 months. Behavioral data on demographics, reproductive and sexual health, lifestyle and sexual behaviors, stigma, and discrimination will be collected. Blood samples will also be collected to test for STIs and NCDs. RESULTS: IBBS-PLHIV was initiated on January 1, 2024, in a phased manner. Data collection was carried out over 3 months and completed by June 2024 across all 120 sites. A total of 25,257 PLHIV were recruited for the surveillance, including 11,921 males, 11,855 females, and 1481 hijra/transgender individuals. Data entry, followed by data matching and validation of all records, was completed in December 2024. The data are currently being analyzed, and the final findings are expected to be disseminated by December 2025. CONCLUSIONS: Data collected through IBBS-PLHIV will help monitor the levels of HIV-related sexual and injecting risk behaviors among PLHIV. Additionally, it will provide estimates of the prevalence of NCD comorbidities and STI coinfections such as diabetes, hypertension, syphilis, and viral hepatitis. These findings will serve as a baseline and are expected to offer valuable insights for facilitating comprehensive HIV care and management through the effective integration of HIV and broader health service delivery. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/58252.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.032 | 0.021 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.036 | 0.008 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".