HIV infection does not disproportionately affect the poorer in sub-Saharan Africa
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Wealthier populations do better than poorer ones on most measures of health status, including nutrition, morbidity and mortality, and healthcare utilization. OBJECTIVES: This study examines the association between household wealth status and HIV serostatus to identify what characteristics and behaviours are associated with HIV infection, and the role of confounding factors such as place of residence and other risk factors. METHODS: Data are from eight national surveys in sub-Saharan Africa (Kenya, Ghana, Burkina Faso, Cameroon, Tanzania, Lesotho, Malawi, and Uganda) conducted during 2003-2005. Dried blood spot samples were collected and tested for HIV, following internationally accepted ethical standards and laboratory procedures. The association between household wealth (measured by an index based on household ownership of durable assets and other amenities) and HIV serostatus is examined using both descriptive and multivariate statistical methods. RESULTS: In all eight countries, adults in the wealthiest quintiles have a higher prevalence of HIV than those in the poorer quintiles. Prevalence increases monotonically with wealth in most cases. Similarly for cohabiting couples, the likelihood that one or both partners is HIV infected increases with wealth. The positive association between wealth and HIV prevalence is only partly explained by an association of wealth with other underlying factors, such as place of residence and education, and by differences in sexual behaviour, such as multiple sex partners, condom use, and male circumcision. CONCLUSION: In sub-Saharan Africa, HIV prevalence does not exhibit the same pattern of association with poverty as most other diseases. HIV programmes should also focus on the wealthier segments of the population.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it