Understanding the effects of different HIV transmission models in individual-based microsimulation of HIV epidemic dynamics in people who inject drugs

Authored by J F G Monteiro, D J Escudero, C Weinreb, T Flanigan, S Galea, S R Friedman, B D L Marshall

Date Published: 2016

DOI: 10.1017/s0950268815003180

Sponsors: United States National Institutes of Health (NIH)

Platforms: No platforms listed

Model Documentation: Other Narrative Mathematical description

Model Code URLs: Model code not found

Abstract

We investigated how different models of HIV transmission, and assumptions regarding the distribution of unprotected sex and syringe-sharing events ('risk acts'), affect quantitative understanding of HIV transmission process in people who inject drugs (PWID). The individual-based model simulated HIV transmission in a dynamic sexual and injecting network representing New York City. We constructed four HIV transmission models: model 1, constant probabilities; model 2, random number of sexual and parenteral acts; model 3, viral load individual assigned; and model 4, two groups of partnerships (low and high risk). Overall, models with less heterogeneity were more sensitive to changes in numbers risk acts, producing HIV incidence up to four times higher than that empirically observed. Although all models overestimated HIV incidence, micro-simulations with greater heterogeneity in the HIV transmission modelling process produced more robust results and better reproduced empirical epidemic dynamics.

Tags

United-states Risk behaviors New-york-city Viral load Active antiretroviral therapy Substance-abuse treatment Behavioral surveillance system Immunodeficiency-virus type-1 Out-of-treatment Sex partners