Patterns and trends in Pakistan's heterogeneous HIV epidemic
Bibliographic record
Abstract
BACKGROUND: Considerable HIV transmission occurs among injection drug users (IDUs) in Pakistan and recently the HIV prevalence has been increasing among male (MSW), hijra (transgender; HSW) and female (FSW) sex workers. We describe past and estimate future patterns of HIV emergence among these populations in several cities in Pakistan. METHODS: The density of these key populations per 1000 adult men was calculated using 2011 mapping data from Karachi, Lahore, Faisalabad, Larkana, Peshawar and Quetta, and surveillance data were used to assess bridging between these key populations. We used the UNAIDS Estimation and Projection Package model to estimate and project HIV epidemics among these key populations in Karachi, Lahore, Faisalabad and Larkana. RESULTS: The density and bridging of key populations varied across cities. Lahore had the largest FSW population (11.5/1000 adult men) and the smallest IDU population (1.7/1000 adult men). Quetta had the most sexual and drug injection bridging between sex workers and IDUs (6.7%, 7.0% and 3.8% of FSW, MSW and HSW, respectively, reported injecting drugs). Model evidence suggests that by 2015 HIV prevalence is likely to reach 17-22% among MSWs/HSWs in Karachi, 44-49% among IDUs in Lahore and 46-66% among IDUs in Karachi. Projection suggests the prevalence may reach as high as 65-75% among IDUs in Faisalabad by 2025. HIV prevalence is also estimated to increase among FSWs, particularly in Karachi and Larkana. CONCLUSIONS: There is a need to closely monitor regional and subpopulation epidemic patterns and implement prevention programmes customised to local epidemics.
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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 | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".