Ecological analysis of the association between high-risk population parameters and HIV prevalence among pregnant women enrolled in sentinel surveillance in four southern India states
Bibliographic record
Abstract
BACKGROUND: The HIV epidemic is very heterogeneous at the district level in the four Southern states of India most affected by the epidemic and where transmission is mainly heterosexual. The authors carried out an ecological study of the relationship between high-risk population parameters and HIV prevalence among pregnant women (ANC HIV prevalence). METHODS: The data used in this study included: ANC HIV prevalence available from the National AIDS Control Organization (dependent variable); data on prevalence of HIV and other sexually transmitted infections among female sex workers (FSWs), their clients and high-risk men who have sex with men (HR-MSM) from studies carried out in 24 districts under Avahan; data on clients' volume reported by FSWs and on the size estimates of FSWs and HR-MSM in each district; and census data. The latter two sets of data were used to estimate the percentage of female (male) adults who are FSWs (HR-MSM). The latter was also multiplied by HIV prevalence in FSWs (HR-MSM) to obtain the percentage of HIV-positive FSWs (HR-MSM) in the adult female (male) population. Linear regression was used for statistical analyses. RESULTS: In univariate analyses, HIV (r=0.59, p=0.002) and HSV-2 (r=0.49, p=0.014) prevalence among FSWs and mean number of clients in the last week reported by FSWs (r=0.43, p=0.036) were significant predictors of ANC HIV prevalence. In multivariate analysis, only FSW HIV prevalence remained significant. CONCLUSIONS: This ecological study suggests that there is a link between HIV prevalence among FSWs and the spread of HIV to the general population in Southern India. Such an observation supports the rationale of interventions targeted at the sex industry.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".