Patterns of Rising HIV Positivity in Northern Madagascar: Evidence of an Urgent Public Health Concern
Bibliographic record
Abstract
Despite over two decades of progress against HIV/AIDS in adjacent sub-Saharan Africa, HIV rates and deaths due to AIDS are exponentially rising in Madagascar. Furthermore, a growing body of evidence suggests that, due to a scarcity of general-population screening data, even the startling increase demonstrated by official models vastly underestimates the true population prevalence of HIV. We aimed to implement a real-world HIV screening and treatment protocol to serve a general population stemming from across northern Madagascar. In collaboration with the Malagasy Ministry of Health, we provided point-of-care HIV screening and confirmatory testing for over 1000 participants from 73 towns, villages, and cities. We recorded an overall HIV prevalence of 2.94%. Notably, we observed a 13.1% HIV prevalence rate among urban populations and showed that proximity to a major route of travel was significantly associated with HIV risk. We also observed a link between HIV risk and various occupations, including those associated with increased mobility (such as mining). Importantly, all HIV-positive individuals were initiated on antiretroviral therapy in concordance with local health authorities. To our knowledge, this study marks the largest primary test data-based HIV study to date among Madagascar's general population, showing a greatly higher HIV prevalence (2.9%) than previously reported modeling-based figures (0.4%). Our rates aligned with the pattern of higher prevalence demonstrated in smaller general-population screening studies occurring more commonly prior to political strife in the mid-2000s. These findings demonstrate evidence of a growing HIV epidemic in northern Madagascar and underscore the need for future investment into more comprehensive HIV screening and control initiatives in Madagascar.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".