Seroprevalence of human T‐lymphotropic virus (<scp>HTLV</scp>) in blood donors in sub‐Saharan Africa: a systematic review and meta‐analysis
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVE: Human T-cell lymphotropic viruses (HTLV) 1 and 2 are endemic in sub-Saharan Africa (SSA), transfusion-transmissible and causally linked to various severe diseases. However, even in SSA countries with moderate to high endemicity, routine blood donor screening for HTLV is rarely, if ever, performed. Information on seroprevalence is limited. The aim of this review is to establish the prevalence of HTLV-1 and HTLV-1/2 among blood donors in sub-Saharan Africa. MATERIALS AND METHODS: We systematically reviewed databases including EMBASE, MEDLINE and the Cochrane database library from their inception to June 2018. Studies presenting data on HTLV prevalence among blood donors in sub-Saharan Africa were included. A random-effect meta-analysis was conducted on all eligible studies. RESULTS: A total of 25 studies were included, representing 74 119 blood donors, of whom over 80% (61 002) were only tested for HTLV-1. The evidence base was high and moderate in quality. The pooled prevalence of the 17 studies that screened only for HTLV-1 and the nine studies that screened for HTLV-1/2 was 0·68 (95% CI: 0·29-1·60) and 1·11 (95% CI: 0·47-2·59) per 100 blood donors, respectively. CONCLUSION: The prevalence of HTLV-1 infection among blood donors is relatively low. The current review is intended to inform debates and decisions about best practices to prevent transfusion-transmitted HTLV in sub-Saharan Africa. Further work is required to determine the risk of infections by transfusion and the cost-effectiveness of any new measures such as routine screening.
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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 | 0.010 | 0.025 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.028 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".