P1-S4.18 Using mathematical modelling to investigate the role of the hidden “population of men who have sex with men (MSM) on the HIV epidemic in Southern India”
Bibliographic record
Abstract
Background Biological and behavioural data for men who have sex with men (MSM) in Bangalore, Karnataka, India, have mainly been collected from sites where commercial sex is prevalent. Consequently, the survey data may fail to capture the behaviour of a larger lower-risk “hidden” MSM population. Mathematical modelling is used to explore the potential bias in the survey data and better quantify the characteristics of this hidden population. Methods A dynamic model of HIV transmission among MSM was developed and parameterised using detailed data* from high risk MSM in urban Bangalore. The MSM were categorised into three subgroups: Kothi and Hijra(KH): who mostly take the receptive role in anal sex, Panthis and Bisexuals(PB) who are predominantly insertive partners and Double Deckers(DD) who take both roles. Due to the sampling methods used, it was thought the MSM survey data were more representative of KH and DD than PB, although the extent of this bias is unknown. Therefore, no fitting constraint was applied to the PB HIV prevalence and instead the model was used to explore what PB HIV prevalence values are projected if the model was only fit to the 95% CIs of the prevalence data for KH and DD. One million randomly sampled model simulations were undertaken to find model fits. Results Abstract P1-S4.18 figure 1 shows that, although the model can produce HIV prevalence estimates consistent with the survey estimates, overall the model projections suggest a lower PB HIV prevalence is more consistent with the survey estimates for KH and DD. In addition, 80% of the model fits to the KH and DD HIV prevalence data had a sampled frequency of sex acts for PB in the lower half of the uncertainty interval suggesting PB's sexual activity may be lower than the median reported in the MSM survey. As expected, an inverse relationship occurs between PB population size and their level of sexual activity, with the median PB population size being 55 400 (2.7% of the total urban male population) and varying between 28 000 and 73 000 (1.5 to 3.9% of the total urban male population) for the IQR of the model fits Conclusions: Survey data imply MSM are a small, highly active group, many of whom regularly sell sex, have very high numbers of partners and typically take the receptive role. As demonstrated here, modelling can be used to provide insights into the likely HIV prevalence, population size and sexual activity of hidden “MSM not reached in surveys.” Abstract P1-S4.18 Figure 1 Number and range of projected HIV prevalence estimates for the PB population (from the model fits to KH and DD data. *Integratedbiological and behavioural assessment (IBBA) 2009, collected within the monitoring and evaluation of Avahan, the India AIDS initiative.
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How this classification was reachedexpand
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".