Prevalence and risk factors for human papillomavirus infection among female sex workers in Hanoi and Ho Chi Minh City, Viet Nam: a cross-sectional study
Bibliographic record
Abstract
Background: Female sex workers (FSWs) are at high risk of human papillomavirus (HPV) infections and cervical cancer due to their high number of sexual partners. The objectives of this study were to determine the prevalence of HPV and identify risk factors for high-risk HPV infection among FSWs in Hanoi and Ho Chi Minh City (HCMC), Viet Nam. Methods: A cross-sectional study was conducted in Hanoi and HCMC between December 2017 and May 2018. We surveyed and screened 699 FSWs aged >18 years for HPV infection and abnormal cytology. A multivariable modified Cox regression model was used to determine risk factors for high-risk HPV infection. Results: The overall prevalence of any HPV, high-risk HPV and HPV-16/18 infection in the 699 FSWs was 26.3%, 17.6% and 4.0%, respectively, and were similar in both cities. Multiple infections were identified in 127 participants (69.0%). HPV-52 was the most prevalent (7%), followed by HPV-58 (6%). Abnormal cytology was detected in 91 participants (13.0%). FSWs who are divorced (adjusted prevalence ratio [aPR]: 1.96, 95% confidence interval [CI]: 1.01–3.81), widowed (aPR: 3.26, 95% CI: 1.49–7.12) or living alone (aPR: 1.85, 95% CI: 1.01–3.39) were associated with a higher prevalence of high-risk HPV infection. Discussion: Almost one in five FSWs in Viet Nam are infected with high-risk HPV. This highlights the importance of prevention strategies such as HPV vaccination and screening in this high-risk group.
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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 | 0.001 | 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".