Viral suppression among persons living with HIV in Trinidad & Tobago: Implications for targeted prevention programmes
Bibliographic record
Abstract
In Trinidad and Tobago, despite persons living with HIV (PLHIV) having access to subsidised treatment and care, only 47% PLHIV attain viral suppression. The study assessed the role of individual-level factors on viral suppression among PLHIV in Trinidad and Tobago. Data from 9,629 PLHIV who attended an HIV clinic between 2016 and 2018 were analysed. Cases were aged ≥18 who met the CDC HIV case definition. Viral suppression defined as a viral load of <200 copies/ml at last assessment. The chi-square test of association determined statistically significant relationships between individual factors and viral suppression. Logistic regression was used to estimate odds ratios (OR) for viral suppression. PLHIV who were males (OR = 0.76, 95% CI 0.67-0.87), men who have sex with men (MSM) (OR = 0.82, 95% CI 0.67-0.99), single/unmarried (OR = 0.69, 95% CI 0.55-0.87), aged 18-24 years (OR = 0.66, 95% CI 0.49-0.89), aged 25-49 years (OR = 0.81, 95% CI 0.70-0.94) were less likely to achieve viral suppression. These study findings demonstrate that retention/adherence programmes must urgently identify and target vulnerable PLHIV populations in Trinidad and Tobago to improve viral suppression. Further research examining community and societal factors, such as stigma and discrimination, is warranted.
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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 | 0.001 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".