Self-Collected Specimens Revealed a Higher Vaccine- and Non-Vaccine-Type Human Papillomavirus Prevalences in a Cross-Sectional Study in Akuse
Bibliographic record
Abstract
BACKGROUND: Population-specific epidemiologic data on human Papillomavirus infection, which are limited in most of the SubSaharan African countries, are necessary for effective cervical cancer prevention. This study aimed to generate population-specific data on human Papillomavirus infections, and determine which of these, self-collected and provider-collected specimens, gives a higher estimate of the prevalence of human Papillomaviruses, including vaccine and non-vaccine-type human Papillomavirus. METHODS: In this cross-sectional study, following a questionnaire-based collection of epidemiological data, self-, and provider-collected specimens, obtained from women 15-65 years of age, were analysed for human Papillomavirus types by a nested-multiplex polymerase chain reaction, and for cervical lesions by Pap testing. HPV data were categorised according to risk type and vaccine types for further analysis. RESULTS: ≤ 0.001). The prevalence of quadrivalent vaccine-type human Papillomaviruses was 12.3% with self-collected specimens, but 6.0% with provider-collected specimens. For the nonavalent vaccine-types, the prevalences were 26.6% and 16.7% respectively. There were multiple infections involving both vaccine-preventable and nonvaccine preventable high-risk human Papillomavirus genotypes. CONCLUSION: The Akuse subdistrict can, therefore, be said to have a high burden of human Papillomavirus infections, which included nonvaccine types, as detected with both self-collected and provider-collected specimens. These imply that self-collection is to be given a higher consideration as a means for a population-based high-risk human Papillomavirus infections burdens assessment/screening. Additionally, even with a successful implementation of the HPV vaccination, if introduced in Ghana, there is still the need to continue with the screening of women.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 teacher head, 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".