The global burden of HIV among Long-distance truck drivers: A systematic review and meta-analysis
Bibliographic record
Abstract
Abstract Long-distance truck drivers (LDTDs) endure a disproportionately high burden of HIV in various global settings. However, unlike other most at-risk populations, the global burden of HIV among LDTDs has not been documented so far. The result has been poor allocation and distribution of the limited HIV preventive resources for LDTDs in most parts of the world. Thus, a systematic review and meta-analysis were conducted to assess the global burden of HIV among LDTDs. A comprehensive electronic search was conducted in PubMed, ProQuest Central, PubMed Central, CINAHL, and Global Index Medicus to identify relevant information published in English on HIV prevalence among LDTDs from 1989 to the 16 th of May 2023. A random-effects meta-analysis was conducted to establish the burden of HIV at global and regional levels. The Joanna Briggs Institute (JBI) and Newcastle-Ottawa Scale (NOS) tools were used to assess the quality of the included studies. Of the 1787 articles identified, 43 were included. Most of the included studies were conducted in sub-Saharan Africa (44.19%, n=19), and Asia and the Pacific (37.21%, n=16). The pooled prevalence of HIV was 3.82%. The burden of HIV was highest in sub-Saharan Africa at 14.34%, followed by Asia and the Pacific at 2.14%, and lastly Western, Central Europe and North America at 0.17%. The overall heterogeneity score was ( I 2 = 98.2%, p < 0.001). The global burden of HIV among LDTDs is 3.82%, six times higher than that of the general population globally. Compared to other regions, the burden of HIV is highest in sub-Saharan Africa at 14.34%, where it’s estimated to be 3% in the general population. Thus, LDTDs endure a disproportionately high burden of HIV compared to other populations. Consequently, more LDTD-centred HIV research and surveillance is needed at national and regional levels to institute tailored preventive policies and interventions. PROSPERO Number CRD42023429390
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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 | 0.014 | 0.032 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.032 |
| Bibliometrics | 0.008 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".