Mapping virtual platforms to estimate the population size of men who have sex with men (MSM) who use internet to find sexual partners: implications to enhance HIV prevention among MSM in Kenya
Bibliographic record
Abstract
<ns3:p><ns3:bold>Introduction: </ns3:bold>Men who have sex with men (MSM) in Kenya face a disproportionate HIV disease burden. Over the last few years, the use of virtual platforms and internet sites to seek male sexual partners has increased manyfold in Kenya. New approaches are required to map, estimate and profile MSM who operate through virtual platforms to design interventions for them.</ns3:p><ns3:p> <ns3:bold>Methods:</ns3:bold> This study was conducted in three counties in Kenya: Kiambu, Kisumu and Mombasa with MSM who use virtual platforms such as geosocial networking (GSN) and social networking applications to find and connect with male sex partners. The platforms were profiled through a multi-stage approach and the number of MSM associated with these platforms were estimated. In the final stage, 435 respondents randomly selected from the virtual platforms were interviewed in a secure location after informed consent. Data analysis focused on calculating an estimate of MSM for each virtual platform in each site, adjusting for duplicate profiles and multiple registrations.</ns3:p><ns3:p> <ns3:bold>Results:</ns3:bold> We identified 24 GSN apps, 18 Facebook accounts/pages and 18 WhatsApp groups across the three counties, with Facebook being the preferred platform. Kiambu had the highest number of estimated MSM at 3,635 (95%CI = 3,335 to 3,990) followed by Kisumu at 1,567 (95%CI = 1,480 to 1,665) and Mombasa at 1,469 (95%CI = 1,335 to 1,604) who used virtual platforms to find other male sexual partners. On average, each MSM had 3.7 profiles on multiple platforms, with an average of 2.1 profiles used in the past month.</ns3:p><ns3:p> <ns3:bold>Conclusions:</ns3:bold> The use of conventional population size estimation approaches that focus on physical sites alone may underestimate the total number of MSM in a geography. Virtual mapping should be used in conjunction with conventional hot spot based size estimation methodologies to estimate numbers of MSM to set programmatic targets.</ns3:p>
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".