O13.3 Estimating the Epidemiological Impact of Antiretroviral Treatment on Heterosexual HIV Epidemics in South India: A Modeling Study
Bibliographic record
Abstract
Background In south India, where intensive condom-based targeted interventions (TIs) for female sex workers (FSWs) have been successful, the potential impact of past, current, and proposed universal antiretroviral treatment (ART) eligibility criteria on concentrated HIV epidemics, remains unknown. Methods We developed a mathematical model of heterosexual HIV transmission to simulate the HIV epidemic in three south Indian districts, using district-specific epidemiological data. The model was calibrated to HIV prevalence by risk groups (low-risk, clients, FSWs), population size, and ART coverage. Assuming that condom-based TIs, HIV testing and treatment access, and retention in HIV-care are sustained at current levels, we compared the following scenarios against no ART: (a) continue with the previous eligibility criteria (CD4 ≤ 250 cells/μL) from the start of each district’s ART programme; (b) expand from previous to current eligibility (CD4 ≤ 350 cells/μL) after November 2011; and (c) expand to early ART at any CD4 cell count after January 2013. Results Without ART, the three districts achieve local elimination between the years 2040 and 2082, and by 2035–2063 under the current ART programme (eligibility criteria: CD4 ≤ 250 cells/μL prior to November 2011, CD4 ≤ 350 cells/μL thereafter). By January 2013, the current ART programme has potentially averted 7.8–11.0% of HIV infections, and saved 32–44 life-years per 100-person years on ART, in addition to gains achieved by local TIs. By 2023, the additional fraction of HIV infections averted by ART(compared to sustained TIs without ART) under scenarios A, B, and C are 21–42%, 33–57%, and 43–69%, respectively, and the incremental gains in life-years per 100-person years on ART are 120–140, 68–111, and 40–91, respectively. Conclusions In declining HIV epidemics with sustained TIs, current ART programmes and proposed ART expansion could provide additional epidemiological impact. The medium-term incremental gains become smaller as eligibility expands but access and retention in care remain constant.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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".