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Using data from ‘visible’ populations to estimate the size and importance of ‘hidden’ populations in an epidemic: A modelling technique

  • Foss, Anna M.1
  • Prudden, Holly J.1
  • Mitchell, Kate M.1
  • Pickles, Michael1, 2
  • Washington, Reynold3, 4
  • Phillips, Anna E.2
  • Alary, Michel5, 6
  • Boily, Marie-Claude2
  • Moses, Stephen4
  • Watts, Charlotte H.1
  • Vickerman, Peter T.1
  • 1 Department of Global Health and Development and Centre for Mathematical Modelling of Infectious Diseases, London School of Hygiene and Tropical Medicine, 15-17 Tavistock Place, London, WC1H 9SH, UK
  • 2 Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, Medical School Building, St Mary’s Campus, Norfolk Place, London, W2 1PG, UK
  • 3 St John’s Research Institute, 100 Feet Road, John Nagar, Koramangala, Bangalore, 560 034, Karnataka, India
  • 4 Department of Community Health Sciences, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, S113-750 Bannatyne Avenue, Winnipeg, Manitoba, R3E 0W3, Canada
  • 5 Centre de recherche du CHU de Québec – Université Laval, 1050 Chemin Ste-Foy, Québec (Qc), G1S 4L8, Canada
  • 6 Département de médecine sociale et préventive, Faculté de médecine, Université Laval, 1050, avenue de la Médecine, Québec (Qc), G1V 0A6, Canada
Published Article
Infectious Disease Modelling
KeAi Publishing
Publication Date
Sep 30, 2020
DOI: 10.1016/j.idm.2020.09.007
PMID: 33102985
PMCID: PMC7566088
PubMed Central


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.

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