Prévalence et facteurs associés aux hépatites B et C chez les travailleuses du sexe de Bamako, Mali
Bibliographic record
Abstract
Introduction: hepatitis B (HBV) and C (HCV) are a public health problem, particularly in low- and middle-income countries. In Mali, West Africa, few data exist on the prevalence of these infections among vulnerable groups such as female sex workers (FSWs) living or not with the human immunodeficiency virus (HIV). This cross-sectional study conducted from March to October 2020 in Bamako, main city of Mali, among 400 FSWs (200 HIV+ and 200 HIV-) aimed to determine the prevalence and factors associated with HBs antigen on one hand and HCV antibodies on the other. Methods: a questionnaire was administered, and blood and vaginal samples were collected. Prevalences are presented according to HIV status and multivariate logistic regression was used to assess the determinants of HBV and HCV. Results: the prevalence of HBs antigen and HCV antibodies were 6.6% and 8.6% in HIV+ and 4.6% and 6.1% in HIV- women, respectively. In multivariate analyses, age at first paid sexual intercourse (< 18 years) and presence of HCV antibodies were strongly associated with HBV (adjusted odds ratio [aOR]; 95% Confidence interval [95%CI]: 3.3; 1.24-8.63 and 3.7; 1.21-11.54, respectively). Only HBs antigen was associated with HCV antibodies (aOR; 95%CI: 4.1; 1.29-12.56). Conclusion: in Mali, the relatively high frequency of viral hepatitis B and C among FSWs requires a targeted prevention program.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".