P719 Prevalence and type-specific distribution of oncogenic human papillomavirus among female sex workers in cotonou, west africa
Bibliographic record
Abstract
<h3>Background</h3> Female sex workers (FSW) are at higher risk of Human Papillomavirus (HPV) infections. Yet, few data exist on the prevalence and the types of HPV circulating among them. Baseline data from FSW recruited in a longitudinal study were analyzed to determine the prevalence and type-specific distribution of oncogenic HPV among FSW in Cotonou. <h3>Methods</h3> Data from 309 FSW with valid cervical specimens (out of 312 enrolled) were analyzed. Cervical specimens were processed through March 2019, using the Linear Array HPV genotyping test (LA-HPV) (Roche Molecular Systems). Where appropriate, a real-time PCR assay specific for type 52 was performed to control for cross-reactivity with HPV-33, 35 or 58. The overall and type-specific prevalence of oncogenic HPV were estimated according to the level of risk: high risk (HR-HPV) and low risk (LR-HPV). <h3>Results</h3> The mean age of the 309 women at enrollment was 34.97 (± 10.66) and that at their first intercourse was 17.53 (± 2.66). Almost half of them (45.8%) were Beninese and 25.8% were HIV positive. Condom use at the last sex with clients and boyfriend was reported by 97.7% and 14.5% of women, respectively. At least one HR-HPV was detected in 237 women (88.3%) and the ten most frequent were HPV58 (37.5%), HPV16 (36.6%), HPV52 (28.8%), HPV35 (23.3%), HPV68 (22.0%), HPV18 (20.7%), HPV45 (15.2%), HPV33 (11.0%), HPV59 (9.1%), HPV51 (6.5%). LR-HPV were found in 186 women (60.2%): HPV81 (23.6%); HPV61 (23.0%); HPV72 (15.2%); VPH42 (12.0%); VPH70 (8.4%), VHP54 (5.8%); VPH 6/VPH11 (5.5%) and VPH40 (2.6%). HR-HPV presence was not associated with HIV status (p=0.897) while that of LR-HPV was (p=0.037). <h3>Conclusion</h3> To our knowledge, this study is the first to provide HPV data among FSW in West Africa. The high prevalence and atypical distribution of oncogenic HPV among this high risk population might have implications for vaccine design. <h3>Disclosure</h3> No significant relationships.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".