The impact of past HIV interventions and diagnosis gaps on new HIV acquisitions, transmissions, and HIV-related deaths in Côte d’Ivoire, Mali, and Senegal
Bibliographic record
Abstract
OBJECTIVES: To estimate the epidemiological impact of past HIV interventions and the magnitude and contribution of undiagnosed HIV among different risk groups on new HIV acquisitions in Côte d'Ivoire, Mali and Senegal. DESIGN: HIV transmission dynamic models among the overall population and key populations [female sex workers (FSW), their clients, and MSM]. METHODS: Models were independently parameterized and calibrated for each set of country-specific demographic, behavioural, and epidemiological data. We estimated the fraction of new HIV infections over 2012-2021 averted by condom use and antiretroviral therapy (ART) uptake among key populations and non-key populations, the direct and indirect contribution of specific groups to new infections [transmission population-attributable fraction (tPAF)] over 2012-2021 due to prevention gaps, and the distribution of undiagnosed people with HIV (PWH) by risk group in January 2022 and their tPAF over 2022-2031. RESULTS: Condom use and ART may have averted 81-88% of new HIV infections over 2012-2021 across countries, mostly due to condom use by key population. The tPAF of all key populations combined over 2012-2021 varied between 27% (Côte d'Ivoire) and 79% (Senegal). Male key populations (clients of FSW and MSM) contributed most to new infections (>60% in Mali and Senegal) owing to their higher HIV prevalence and larger prevention gaps. In 2022, men represented 56% of all PWH with an undiagnosed infection in Côte d'Ivoire (male key populations = 15%), 46% in Mali (male key populations = 23%), and 69% in Senegal (male key populations = 55%). If HIV testing and ART initiation rates remain at current levels, 20% of new HIV infections could be due to undiagnosed key populations living with HIV in Côte d'Ivoire over 2022-2031, 53% in Mali, and 65% in Senegal. CONCLUSION: Substantial HIV diagnosis gaps remain in Western Africa, especially among male key populations. Addressing these gaps is key to impacting the HIV epidemics in the region and achieving the goal of ending AIDS by 2030.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".