O1-S11.02 Determinants of time trends in HIV prevalence in the young antenatal population of Karnataka districts
Bibliographic record
Abstract
Background In 2003, the Bill & Melinda Gates Foundation initiated a focused HIV prevention program (India AIDS Initiative: Avahan) among high-risk and bridge groups. We studied determinants of time trends in HIV prevalence among young (<25 years) antenatal (ANC) women caused by these intensive prevention intervention (IPI) program compared to non-intensive intervention (Non-IPI) program. Methods Random intercept multilevel models were developed using logistic regression (xtmelogit command) to examine effects of IPI, program and district level variables on HIV prevalence among young ANC women. Data from annual sentinel surveillance of ANC women were used as individual level characteristics. Selected program and socio-demographic variables at district level were included as distal variables. Interaction between time and intensity of program intervention was assessed. Results HIV prevalence in young ANC women decreased steadily from 1.4% to 0.77% from 2003 to 2007, and increased to 0.83% in 2008 (Adjusted OR (AOR)=0.59, (95% CI):0.45% to 0.77%). Rural (AOR=0.87, 95% CI: 0.76% to 0.99%) and literate women (AOR=0.76,95% CI:0.66% to 0.87%) had lower risk of HIV compared to urban and illiterate women respectively. Presence of major truck halt points (AOR=1.57,95% CI: 1.17% to 2.12%) in the district was associated with high risk of HIV. Higher age at marriage was associated with lower risk of HIV (AOR=0.85,95% CI: 0.78% to 0.93%). There was significant interaction between time and intensity of intervention. In the years 2006 and 2007, Non-IPI districts had a significantly higher risk of HIV compared to IPI districts (AOR2006=1.86, 95% CI: 1.18% to 2.93% and AOR 2007=2.25, 95% CI: 1.39% to 3.62%) respectively. Among the program variables regular contact with high risk group was associated with slightly reduced risk of HIV (AOR=0.998, 95% CI: 0.996% to 0.999%) see Abstract O1-S11.02 table 1. Abstract O1-S11.02 Table 1 Determinants of time trends in HIV prevalence in the young antenatal population of Karnataka districts Individual/district level characteristics Null model Random intercept model: % high risk group persons contacted regularly AOR (95% CI) AOR (95% CI) Fixed part of the model Constant 0.009 (0.0080 to 0.0114) 0.528 (0.097 to 2.8782) Individual characteristics Year–2003 (Reference) 2004 0.992 (0.7854 to 1.2521) 2005 0.804 (0.6287 to 1.0288) 2006 0.585 (0.4458 to 0.7681) 2007 0.418 (0.3109 to 0.562) 2008 0.585 (0.4475 to 0.7649) Locality–Urban (Reference) Rural 0.867 (0.7581 to 0.9915) Type of site–District headquarter (Reference) First referral unit–rural 0.784 (0.6904 to 0.8907) Literacy–llliterate (reference) Literate 0.759 (0.6622 to 0.871) Type of intervention–IPI (reference) Non-IPI 0.871 (0.5578 to 1.361) Programme variable % Contacted regularly 0.998 (0.9959 to 0.9999) District level variables Mean age at marriage for girls (years) 0.848 (0.7773 to 0.9261) Major truck halt points 1.573 (1.166 to 2.1212) Interaction Year 2004 and Non-IPI 1.101 (0.7184 to 1.6887) Year 2005 and Non-IPI 1.443 (0.929 to 2.2427) Year 2006 and Non-IPI 1.856 (1.1769 to 2.9253) Year 2007 and Non-IPI 2.245 (1.3902 to 3.6249) Year 2008 and Non-IPI 1.098 (0.6477 to 1.8601) Random part of the model District-level variance: total 0.1333 (0.0642 to 0.2767) 0.072 (0.0337 to 0.1530) Conclusion HIV prevalence in ANC population declined significantly in IPI districts from 2003 to 2008 compared to non-IPI districts in Karnataka. IPI had a definite impact on reduction of HIV prevalence in general population during 2006 and 2007. This coincides with the maturity of IPI during 2006 and 2007 along with the initiation of NACP-III in 2007. Learning from IPI might have influenced National AIDS Control Program-III implementation in non-IPI districts in Karnataka leading to similar effects in IPI and non-IPI districts in 2008. Improving female literacy and increasing the age at marriage would help favour reduction of HIV.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".