Estimates of the size of key populations at risk for HIV infection: men who have sex with men, female sex workers and injecting drug users in Nairobi, Kenya
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVES: Size estimates of populations at higher risk for HIV infection are needed to help policy makers understand the scope of the epidemic and allocate appropriate resources. Population size estimates of men who have sex with men (MSM), female sex workers(FSW) and intravenous drug users (IDU) are few or non-existent in Nairobi, Kenya. METHODS: We integrated three population size estimation methods into a behavioural surveillance survey among MSM, FSW and IDU in Nairobi during 2010–2011. These methods included the multiplier method, ‘Wisdom of the Crowds’ and an approach that drew on published literature. The median of the three estimates was hypothesised to be the most plausible size estimate with the other results forming the upper and lower plausible bounds. Data were shared with community representatives and stakeholders to finalise ‘best’ point estimates and plausible bounds based on the data collected in Nairobi, a priori expectations from the global literature and stakeholder input. RESULTS: We estimate there are approximately 11 042 MSM with a plausible range of 10 000–22 222, 29 494 FSW with a plausible range of 10 000–54 467 FSW and approximately 6107 IDU and plausibly 5031–10 937 IDU living in Nairobi. CONCLUSIONS: We employed multiple methods and used a wide range of data sources to estimate the size of three hidden populations in Nairobi, Kenya. These estimates may be useful to advocate for and to plan, implement and evaluate HIV prevention and care programmes for MSM, FSW and IDU. Surveillance activities should consider integrating population size estimation in their protocols.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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