Trends and determinants of HIV transmission among men who inject drugs in the Pokhara Valley, Nepal: Analysis of cross-sectional studies
Bibliographic record
Abstract
Abstract Background HIV is a major public health issue around the world, especially in developing countries. Although the overall prevalence of HIV in Nepal is relatively low, there are specific sub-populations where the prevalence is far higher than the national average. One of these sub-groups is male people who inject drugs (male PWIDs). In order to understand the reasons for the differences in prevalence, a series of socio-demographic, behavioural and knowledge-based risk factors were assessed. Methods The study used a series of 7 cross-sectional survey datasets from Pokhara (Nepal), collected between 2003 and 2017 (N=2,235) to investigate trends in HIV prevalence among male PWIDs by socio-demographic, behavioural, and knowledge-based risk factors. A series of logistic regression models were conducted to investigate the association between study factors and HIV. Results HIV prevalence decreased from the levels seen in 2003 (22.0%) and 2005 (21.7%), with the lowest prevalence recorded in 2015 (2.6%), however prevalence increased in the most recent period (4.9%). A lower risk of HIV was associated with younger age (<=24 years compared to >24 years, OR = 0.17, 95% CI = 0.10-0.31), being married (OR = 1.91, 95% CI = 1.25-3.02) and shorter duration of drug use (<=4 years compared to >4 years, OR = 0.16, 95% CI = 0.09-0.29). A higher risk of HIV was associated with low (compared to secondary or higher) education level (OR = 2.76, 95% CI = 1.75-4.36), a lack of addiction treatment (OR = 2.59, 95% CI = 1.64-4.08), and recent use of unsterilized injection equipment (OR = 2.22, 95% CI = 1.20-4.11). Conclusion The prevalence of HIV in male PWIDs in Pokhara has been variable, but overall has reduced in recent years to 2.6% before increasing in 2017 to 4.9%. The main determinants which increase the risk of HIV among male PWIDs in Pokhara are low education level, a lack of treatment for drug addiction and the recent use of unsterilised equipment. Each of these indicate the need to improve addiction treatment and education programs for intra-venous drug use to aid this key population in avoiding risk-taking behaviours.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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 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".