Lost in Transition: HIV Prevalence and Correlates of Infection among Young People Living in Post-Emergency Phase Transit Camps in Gulu District, Northern Uganda
Bibliographic record
Abstract
OBJECTIVE: Little is known about HIV infection and the related vulnerabilities of young people living in resource-scarce, post-emergency transit camps that are now home to thousands of Internally Displaced Persons (IDPs) following two decades of war in northern Uganda. The objective of this analysis was to assess the prevalence and correlates of HIV infection among young people living in post-conflict transition in Gulu District, northern Uganda. METHODS: In 2010, a cross-sectional demographic and behavioural survey was conducted in two of Gulu District's sub-counties with 384 purposively selected transit camp residents aged 15 to 29 years. Biological specimens were collected for rapid HIV testing in the field and confirmatory laboratory testing. Multivariable logistic regression identified independent determinants of HIV infection. RESULTS: HIV prevalence was alarmingly high at 12.8% (95% CI: 9.6%, 16.5%). The strongest determinant of HIV infection among young people was a non-consensual sexual debut (adjusted odds ratio [AOR], 9.88; 95% CI: 1.70-18.06). Residing in Awach sub-county (AOR, 2.93; 95% CI: 1.28-6.68), experiencing STI symptoms in the previous 12 months (AOR, 2.36; 95% CI: 1.43-6.17), and practicing dry sex (AOR, 2.31; 95% CI: 1.04-5.13) were other key determinants of HIV infection. CONCLUSIONS: Study findings contribute to filling an important gap in epidemiological evidence and are useful for planning public health interventions in northern Uganda that effectively target young people in post-conflict transition and support them in the resettlement process. Findings serve to recommend reaching beyond traditional prevention programming in a way more effectively beneficial to young people in post-conflict settings by developing population-specific responses sensitive to local contexts and sufficient to address the underlying causes of the complex risk factors influencing the spread of HIV.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".