ArticleInfectious Disease Modelling2020
Using data from 'visible' populations to estimate the size and importance of 'hidden' populations in an epidemic: A modelling technique.
Article in Infectious Disease Modelling, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
Abstract
We used reported behavioural data from cisgender men who have sex with men and transgender women (MSM/TGW) in Bangalore, mainly collected from 'hot-spot' locations that attract MSM/TGW, to illustrate a technique to deal with potential issues with the representativeness of this sample. A deterministic dynamic model of HIV transmission was developed, incorporating three subgroups of MSM/TGW, grouped according to their reported predominant sexual role (insertive, receptive or versatile). Using mathematical modelling and data triangulation for 'balancing' numbers of partners and role preferences, we compared three different approaches to determine if our technique could be useful for inferring characteristics of a more 'hidden' insertive MSM subpopulation, and explored their potential importance for the HIV epidemic. Projections for 2009 across all three approaches suggest that HIV prevalence among insertive MSM was likely to be less than half that recorded in the surveys (4.5-6.5% versus 13.1%), but that the relative size of this subgroup was over four times larger (61-69% of all MSM/TGW versus 15%). We infer that the insertive MSM accounted for 10-20% of all prevalent HIV infections among urban males aged 15-49. Mathematical modelling can be used with data on 'visible' MSM/TGW to provide insights into the characteristics of 'hidden' MSM. A greater understanding of the sexual behaviour of all MSM/TGW is important for effective HIV programming. More broadly, a hidden subgroup with a lower infectious disease prevalence than more visible subgroups, has the potential to contain more infections, if the hidden subgroup is considerably larger in size.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.