The prevalence and incidence of HIV in the ART era (2006–2016) in North West Tanzania
Bibliographic record
Abstract
BACKGROUND: Sub-Saharan countries bear a disproportionate percentage of HIV infections and HIV-related deaths despite the efforts to strengthen HIV prevention and treatments services, including ART. It is important to demonstrate how these services have contributed to reducing the epidemic using available population data. METHODS: We estimated the prevalence and incidence rates from a cohort running over 23 years in Magu District, Mwanza Region-North West Tanzania. Adults 15 years and over who were residents of the Kisesa observational HIV cohort study between 2006 and 2016 were eligible for inclusion. Survival analysis was used to calculate person-time at risk, incidence rates and 95% confidence intervals (CIs). Cox regression models were used for the risk factor analyses disaggregated by sex and age group. RESULTS: The HIV prevalence in the sero-surveys decreased from 7.2% in 2006/07 to 6.6% in 2016, with a notable decrease of over 50% for both men and women aged 15-24 years. The incidence rate for HIV was estimated to be 5.5 (95% CI 4.6-6.6) per 1,000 person-years in women compared to 4.6 (95% CI 3.5-5.8) in men, with a decrease over time. Despite the availability of ART services, the uptake is still small. CONCLUSIONS: New infections are still occurring, with high HIV incidence in individuals aged below 45 years. With new guidelines and the 95-95-95 UNAIDS target, prevalence and incidence must be adequately assessed. In addition, there is a need for additional efforts to assess the impact of HIV/AIDS prevention programmes and intervention services, especially in these areas where resources are limited.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".