ArticleJournal of theoretical biology2014
Who mixes with whom among men who have sex with men? Implications for modelling the HIV epidemic in southern India.
Article in Journal of theoretical biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 9 citations in OpenAlex.
- A scoping review of lesbian, gay, bisexual, transgender, queer, and intersex (LGBTQI+) people's health in India.PLOS global public health · 2023Article
- Overlapping Key Populations and HIV Transmission in Tijuana, Mexico: A Modelling Analysis of Epidemic Drivers.AIDS and behavior · 2021Article
- Using data from 'visible' populations to estimate the size and importance of 'hidden' populations in an epidemic: A modelling technique.Infectious Disease Modelling · 2020Article
- "We are not gays… don't tell me those things": engaging 'hidden' men who have sex with men and transgender women in HIV prevention in Myanmar.BMC public health · 2019Article
- Pre-exposure prophylaxis (PrEP) for MSM in low HIV incidence places: should high risk individuals be targeted?Scientific reports · 2018Article
- Article
- Potential impact of pre-exposure prophylaxis for female sex workers and men who have sex with men in Bangalore, India: a mathematical modelling study.Journal of the International AIDS Society · 2016Article
- Optimal allocation of resources in female sex worker targeted HIV prevention interventions: model insights from Avahan in South India.PloS one · 2014Article
Corrections and comments
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Authors and funding
19 authors at 7 institutions in 3 countries.
Funding
Abstract
In India, the identity of men who have sex with men (MSM) is closely related to the role taken in anal sex (insertive, receptive or both), but little is known about sexual mixing between identity groups. Both role segregation (taking only the insertive or receptive role) and the extent of assortative (within-group) mixing are known to affect HIV epidemic size in other settings and populations. This study explores how different possible mixing scenarios, consistent with behavioural data collected in Bangalore, south India, affect both the HIV epidemic, and the impact of a targeted intervention. Deterministic models describing HIV transmission between three MSM identity groups (mostly insertive Panthis/Bisexuals, mostly receptive Kothis/Hijras and versatile Double Deckers), were parameterised with behavioural data from Bangalore. We extended previous models of MSM role segregation to allow each of the identity groups to have both insertive and receptive acts, in differing ratios, in line with field data. The models were used to explore four different mixing scenarios ranging from assortative (maximising within-group mixing) to disassortative (minimising within-group mixing). A simple model was used to obtain insights into the relationship between the degree of within-group mixing, R0 and equilibrium HIV prevalence under different mixing scenarios. A more complex, extended version of the model was used to compare the predicted HIV prevalence trends and impact of an HIV intervention when fitted to data from Bangalore. With the simple model, mixing scenarios with increased amounts of assortative (within-group) mixing tended to give rise to a higher R0 and increased the likelihood that an epidemic would occur. When the complex model was fit to HIV prevalence data, large differences in the level of assortative mixing were seen between the fits identified using different mixing scenarios, but little difference was projected in future HIV prevalence trends. An oral pre-exposure prophylaxis (PrEP) intervention was modelled, targeted at the different identity groups. For intervention strategies targeting the receptive or receptive and versatile MSM together, the overall impact was very similar for different mixing patterns. However, for PrEP scenarios targeting insertive or versatile MSM alone, the overall impact varied considerably for different mixing scenarios; more impact was achieved with greater levels of disassortative mixing.
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