Prevalence and Molecular Epidemiology of Human T-Lymphotropic Virus Type 1 among Women Attending Antenatal Clinics in Sub-Saharan Africa: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Human T-cell lymphotropic virus type 1 (HTLV-1) imposes a substantial disease burden in sub-Saharan Africa (SSA), which is arguably the world's largest endemic area for HTLV-1. Evidence that mother-to-child transmission persists as a major mode of transmission in SSA prompted us to estimate the pooled prevalence of HTLV-1 among pregnant women throughout the region. We systematically reviewed databases including EMBASE, MEDLINE, Web of Science, and the Cochrane Database of Systemic Reviews from their inception to November 2018. We selected studies with data on HTLV-1 prevalence among pregnant women in SSA. A random effect meta-analysis was conducted on all eligible data and heterogeneity was assessed through subgroup analyses. A total of 18 studies, covering 14,079 pregnant women, were selected. The evidence base was high to moderate in quality. The pooled prevalence, per 100 women, of the 18 studies that screened HTLV-1 was 1.67 (95% CI: 1.00-2.50), a figure that masks regional variations. In Western, Central, Southern, and Eastern Africa, the numbers were 2.34 (1.68-3.09), 2.00 (0.75-3.79), 0.30 (0.10-0.57), and 0.00 (0.00-0.21), respectively. The prevalence of HTLV-1 infection among pregnant women in SSA, especially in Western and Central Africa, strengthens the case for action to implement routine screening of pregnant women for HTLV-1. Rigorous studies using confirmatory testing and molecular analysis would characterize more accurately the prevalence of this infection, consolidate the evidence base, and further guide beneficial interventions.
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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 | 0.011 | 0.026 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.022 | 0.036 |
| 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) | 0.003 | 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".