Prevalence of human papillomavirus (HPV) in Brazil: A systematic review and meta-analysis
Bibliographic record
Abstract
OBJECTIVES: This study aimed to estimate the prevalence of genital, anal and oral HPV infection in Brazil through systematic review and meta-analysis. METHODS: We searched EMBASE, LILACS, MEDLINE, Web of Science and SciELO from inception to December 2018. Original research articles that assessed the prevalence of genital (i.e., cervical, penile), anal and oral HPV infection in Brazil were selected in pairs by independent authors. No sex, age, HPV vaccination, language or date restrictions were applied. HPV prevalence was estimated and stratified according to risk factors population and by geographic area throughout the country. The study prevalence was pooled using a random effects model. Analysis was performed using R (version 3.5.2), packages meta version 4.9-4 and metaphor 2.0-0. This review is registered on PROSPERO under protocol number CRD42016032751. RESULTS: We identified 3,351 references. After the screening process, 139 of them were eligible for this systematic review (57,513 total participants). Prevalence of cervical HPV was 25.41% (95% CI 22.71-28.32). Additionally, prevalence was 36.21% (95% CI 23.40, 51.33) in the penile region, 25.68% (95%CI 14.64, 41.04) in the anal region, and 11.89% (95%CI 6.26, 21.43) in the oral region. Subgroup analysis showed prevalence in each anatomic site was higher in high-risk populations. CONCLUSION: The prevalence of HPV is high in the Brazilian population and varies by population risk and anatomic body site, with lower rates in the oral cavity compared to that in the cervical, penile and anal region. Studies on HPV have primarily been developed to evaluate infection and cancer in the cervical region. There is a profound lack of HPV data in many geographic regions of Brazil and for different anatomic sites.
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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 | 0.018 | 0.040 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.037 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".