Mobility, Sexual Behavior, and HIV Infection in an Urban Population in Cameroon
Bibliographic record
Abstract
Several studies, notably from rural areas, have shown an association between mobility and HIV infection. However, reasons for this association are poorly documented. In this study, we examined the relationship between mobility, sexual behavior, and HIV infection in an urban population of Cameroon. A representative sample of 896 men and 1017 women were interviewed and tested for HIV infection and other sexually transmitted infections in Yaoundé in 1997. Mobile and nonmobile people were compared with respect to sociodemographic attributes, risk exposure, condom use, and prevalence of HIV infection, using descriptive statistics and multivariate logistic regression. Seventy-three percent of men and 68% of women reported at least 1 trip outside of Yaoundé in the preceding 12 months. Among men, the prevalence of HIV infection increased with time away from town. Men who declared no absence were 5 times less likely to be infected than were those away for >31 days (1.4% vs. 7.6%, respectively; adjusted odds ratio, 0.23; 95% confidence interval, 0.07-0.82). Furthermore, mobile men reported more risky sexual behaviors (ie, more partners and more one-off contacts). For women, the pattern was less clear: differences in the prevalence of HIV infection were less marked for nonmobile than for mobile women (6.9% vs. 9.8%, respectively; P > 0.1). This study suggests that characteristics of male mobility may be an important feature of the HIV epidemic in Cameroon.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".