Evidence map›Paper›PMID 24727187›Full record

ArticleJournal of theoretical biology2014

Who mixes with whom among men who have sex with men? Implications for modelling the HIV epidemic in southern India.

K M Mitchell, A M Foss, H J Prudden, Z Mukandavire, M Pickles, J R Williams, H C Johnson, B M Ramesh, R Washington, S Isac and 9 more

Open access · hybridAbstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
0.5field-weighted citation impact, top 32% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 9 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

19 authors at 7 institutions in 3 countries.

K M MitchellLondon School of Hygiene and Tropical Medicine, London, UK. Electronic address: Kate.Mitchell@lshtm.ac.uk.
A M FossLondon School of Hygiene and Tropical Medicine, London, UK. Electronic address: Anna.Foss@lshtm.ac.uk.
H J PruddenLondon School of Hygiene and Tropical Medicine, London, UK. Electronic address: Holly.Prudden@lshtm.ac.uk.
Z MukandavireLondon School of Hygiene and Tropical Medicine, London, UK. Electronic address: Zindoga.Mukandavire@lshtm.ac.uk.
M PicklesLondon School of Hygiene and Tropical Medicine, London, UK; Imperial College London, London, UK. Electronic address: M.Pickles@imperial.ac.uk.
J R WilliamsImperial College London, London, UK. Electronic address: JR.Williams@imperial.ac.uk.
H C JohnsonLondon School of Hygiene and Tropical Medicine, London, UK. Electronic address: Helen.Johnson@lshtm.ac.uk.
B M RameshKarnataka Health Promotion Trust, Bangalore, India; University of Manitoba, Winnipeg, MB, Canada. Electronic address: bmramesh@khpt.org.
R WashingtonKarnataka Health Promotion Trust, Bangalore, India; St. John's Research Institute, Bangalore, India. Electronic address: reynold@khpt.org.
S IsacKarnataka Health Promotion Trust, Bangalore, India. Electronic address: shajyisac@khpt.org.
S RajaramCHARME-India Project, Bangalore, India. Electronic address: rajaram@khpt.org.
A E PhillipsImperial College London, London, UK. Electronic address: a.phillips05@imperial.ac.uk.
J BradleyCHARME-India Project, Bangalore, India; Centre de recherche du CHU de Québec, Québec, QC, Canada. Electronic address: jbradley360@shaw.ca.
M AlaryCentre de recherche du CHU de Québec, Québec, QC, Canada; Département de medicine sociale et preventive, Université laval, Québec, QC, Canada; Institut national de santé publique du Québec, Québec, QC, Canada. Electronic address: malary@uresp.ulaval.ca.
S MosesUniversity of Manitoba, Winnipeg, MB, Canada. Electronic address: Stephen.Moses@med.umanitoba.ca.
C M LowndesCentre de recherche du CHU de Québec, Québec, QC, Canada; Public Health England, London, UK. Electronic address: Catherine.lowndes@phe.gov.uk.
C H WattsLondon School of Hygiene and Tropical Medicine, London, UK. Electronic address: Charlotte.Watts@lshtm.ac.uk.
M-C BoilyImperial College London, London, UK. Electronic address: mc.boily@imperial.ac.uk.
P VickermanUniversity of Bristol, Bristol, UK; London School of Hygiene and Tropical Medicine, London, UK. Electronic address: Peter.Vickerman@lshtm.ac.uk.
London School of Hygiene & Tropical Medicine · GBImperial College London · GBCentre hospitalier universitaire de Québec · CAKarnataka Health Promotion Trust · INPublic Health England · GBSt. John's National Academy of Health Sciences · INUniversity of Manitoba · CA

Funding

Medical Research Council MR/K012126/1Wellcome Trust 086431/Z/08/Z
6 · The paper itself

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.

Indexed as

HIV-1Homosexuality, MaleModels, BiologicalHIV InfectionsHumansIndiaMalePrevalenceDisassortative mixingMathematical modelMixing matrixPre-exposure prophylaxisSexually transmitted infection

Identifiers

PMID24727187
PMCPMC4064301
OpenAlexW2128289824

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.