Possible reasons for an increase in the proportion of genital ulcers due to herpes simplex virus from a cohort of female bar workers in Tanzania
Bibliographic record
Abstract
OBJECTIVES: To determine trends in the prevalence and aetiological distribution of genital ulcer syndrome (GUS) in a cohort of female bar workers and to assess factors associated with these trends. METHODS: An open cohort of 600 women at high risk of HIV and sexually transmitted infection (STI) was offered screening and treatment for STI at 3-month intervals. The prevalence of GUS and associated aetiological agents (Herpes simplex virus (HSV), Treponema pallidum and Haemophilus ducreyi) were monitored over 27 months through clinical examination, dry lesion swabbing and multiplex polymerase chain reaction. The effects of HIV status and other factors on the prevalence trends of STI were assessed. RESULTS: A total of 753 women were recruited into the cohort over 10 examination rounds. At recruitment, the seroprevalence was 67% for HIV and 89% for HSV type 2 (HSV-2). During follow-up, 57% of ulcers had unknown aetiology, 37% were due to genital herpes and 6% to bacterial aetiologies, which disappeared completely in later rounds. The absolute prevalence of genital herpes remained stable at around 2%. The proportion of GUS caused by HSV increased from 22% to 58%, whereas bacterial causes declined. These trends were observed in both HIV-negative and HIV-positive women. CONCLUSIONS: The changes observed in the frequency and proportional distribution of GUS aetiologies suggest that regular STI screening and treatment over an extended period can effectively reduce bacterial STI and should therefore be sustained. However, in populations with a high prevalence of HSV-2, there remains a considerable burden of genital herpes, which soon becomes the predominant cause of GUS. Given the observed associations between genital herpes and HIV transmission, high priority should be given to the evaluation of potential interventions to control HSV-2 either through a vaccine or through episodic or suppressive antiviral therapy and primary prevention.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".