Infectious Disease Modelling (Jan 2020)
Using data from ‘visible’ populations to estimate the size and importance of ‘hidden’ populations in an epidemic: A modelling technique
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.
