O13.2 Can the UNAIDS Modes of Transmission Model Be Improved? A Comparison of the Original and Revised Model Projections Using Data from Nigeria
Bibliographic record
Abstract
Mathematical modelling has increased our understanding of the HIV epidemic and played a key role in decision making. The UNAIDS Modes of Transmission (MoT) model has been used by 29 countries to analyse their HIV epidemics, with the results helping to guide and focus interventions. However, the simplistic compartmentalisation of the population within the model has raised concerns over its reliability. We compared the MoT model projections for Cross River, Nigeria, with a revised MoT model that incorporates additional heterogeneity (including subgroups for sero-discordant partnerships and individuals engaging in transactional sex) and updated parameters. We categorised population subgroups into ‘high-risk’, representing core groups, their bridging partners and sero-discordant partnerships; ‘medium-risk’, who are regular partners of ‘high-risk’ individuals; and ‘general population’, who are not linked to ‘high-risk’ or ‘medium-risk’ groups. Sensitivity analyses were undertaken and model projections assessed which population categories generated the highest incidence of HIV. The original MoT model projections suggest 73% of HIV infections occur in general population subgroups and 21% amongst ‘high-risk’ groups. Following revisions to the MoT, model projections estimate 76–94% (95%CrI) of new HIV infections are expected to occur in high-risk groups, who make up just 23% of the population, compared to 6–24% amongst general population subgroups. Changes in the distribution of infections result from the introduction of sero-discordant partnerships and ‘transactional sex’ groups (a relatively large subset of the population, often ignored in modelling analysis) in the model, which are classified as ‘high-risk’. The UNAIDS MoT remains an accessible and potentially useful model that can help inform intervention priorities. However, our findings strongly suggest that the current model may produce misleading findings, especially in more concentrated HIV epidemic settings. Results from this study indicate the need for UNAIDS to conduct a formal review of the MoT, and for further revisions to be made.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".