Evaluating HIV Prevention Programs: Herpes Simplex Virus Type 2 Antibodies as Biomarker for Sexual Risk Behavior in Young Adults in Resource-Poor Countries
Bibliographic record
Abstract
BACKGROUND: Measuring effectiveness of HIV prevention interventions is challenged by bias when using self-reported knowledge, attitude or behavior change. HIV incidence is an objective marker to measure effectiveness of HIV prevention interventions, however, because new infection rates are relatively low, prevention studies require large sample sizes. Herpes simplex virus type 2 (HSV-2) is similarly transmitted and more prevalent and could thus serve as a proxy marker for sexual risk behavior and therefore HIV infection. METHODS: HSV-2 antibodies were assessed in a sub-study of 70,000 students participating in an education intervention in Western Province, Kenya. Feasibility of testing for HSV-2 antibodies was assessed comparing two methods using Fisher's exact test. Three hundred and ninety four students (aged 18 to 22 years) were randomly chosen from the cohort and tested for HIV, Chlamydia trachomatis, Neisseria gonorrhoeae, and Trichomonas vaginalis. Out of these, 139 students were tested for HSV-2 with ELISA and surveyed for sexual risk behavior and 89 students were additionally tested for HSV-2 with a point-of-contact (POC) test. RESULTS: Prevalence rates were 0.5%, 1.8%, 0.3% and 2.3% for HIV, Chlamydia trachomatis, Neisseria gonorrhoeae, and Trichomonas vaginalis, respectively. Prevalence of HSV-2 antibodies was 3.4 % as measured by POC test (n=89) and 14.4 % by ELISA (n=139). Specificity of the POC test compared with ELISA was 100%, and the sensitivity only 23.1%. Associations between self-reported sexual behavior and HSV-2 serostatus could not be shown. CONCLUSIONS: Associations between self-reported sexual risk behavior and HSV-2 serostatus could not be shown, probably due to social bias in interviews since its transmission is clearly linked. HSV-2 antibody testing is feasible in resource-poor settings and shows higher prevalence rates than other sexually transmitted diseases thus representing a potential biomarker for evaluation of HIV prevention interventions.
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".