Combination interventions for Hepatitis C and Cirrhosis reduction among people who inject drugs: An agent-based, networked population simulation experiment

Hepatitis C virus (HCV) infection is endemic in people who inject drugs (PWID), with prevalence estimates above 60 percent for PWID in the United States. Previous modeling studies suggest that direct acting antiviral (DAA) treatment can lower overall prevalence in this population, but treatment is often delayed until the onset of advanced liver disease (fibrosis stage 3 or later) due to cost. Lower cost interventions featuring syringe access (SA) and medically assisted treatment (MAT) for addiction are known to be less costly, but have shown mixed results in lowering HCV rates below current levels. Little is known about the potential synergistic effects of combining DAA and MAT treatment, and large-scale tests of combined interventions are rare. While simulation experiments can reveal likely long-term effects, most prior simulations have been performed on closed populations of model agents--a scenario quite different from the open, mobile populations known to most health agencies. This paper uses data from the Centers for Disease Control's National HIV Behavioral Surveillance project, IDU round 3, collected in New York City in 2012 by the New York City Department of Health and Mental Hygiene to parameterize simulations of open populations. Our results show that, in an open population, SA/MAT by itself has only small effects on HCV prevalence, while DAA treatment by itself can significantly lower both HCV and HCV-related advanced liver disease prevalence. More importantly, the simulation experiments suggest that cost effective synergistic combinations of the two strategies can dramatically reduce HCV incidence. We conclude that adopting SA/MAT implementations alongside DAA interventions can play a critical role in reducing the long-term consequences of ongoing infection

The diminishing role of hubs in dynamical processes on complex networks

It is notoriously difficult to predict the behaviour of a complex self-organizing system, where the interactions among dynamical units form a heterogeneous topology. Even if the dynamics of each microscopic unit is known, a real understanding of their contributions to the macroscopic system behaviour is still lacking. Here we develop information-theoretical methods to distinguish the contribution of each individual unit to the collective out-of-equilibrium dynamics. We show that for a system of units connected by a network of interaction potentials with an arbitrary degree distribution, highly connected units have less impact on the system dynamics as compared to intermediately connected units. In an equilibrium setting, the hubs are often found to dictate the long-term behaviour. However, we find both analytically and experimentally that the instantaneous states of these units have a short-lasting effect on the state trajectory of the entire system. We present qualitative evidence of this phenomenon from empirical findings about a social network of product recommendations, a protein-protein interaction network, and a neural network, suggesting that it might indeed be a widespread property in nature.Comment: Published versio

High GUD Incidence in the Early 20th Century Created a Particularly Permissive Time Window for the Origin and Initial Spread of Epidemic HIV Strains

The processes that permitted a few SIV strains to emerge epidemically as HIV groups remain elusive. Paradigmatic theories propose factors that may have facilitated adaptation to the human host (e.g., unsafe injections), none of which provide a coherent explanation for the timing, geographical origin, and scarcity of epidemic HIV strains. Our updated molecular clock analyses established relatively narrow time intervals (roughly 1880–1940) for major SIV transfers to humans. Factors that could favor HIV emergence in this time frame may have been genital ulcer disease (GUD), resulting in high HIV-1 transmissibility (4–43%), largely exceeding parenteral transmissibility; lack of male circumcision increasing male HIV infection risk; and gender-skewed city growth increasing sexual promiscuity. We surveyed colonial medical literature reporting incidences of GUD for the relevant regions, concentrating on cities, suffering less reporting biases than rural areas. Coinciding in time with the origin of the major HIV groups, colonial cities showed intense GUD outbreaks with incidences 1.5–2.5 orders of magnitude higher than in mid 20th century. We surveyed ethnographic literature, and concluded that male circumcision frequencies were lower in early 20th century than nowadays, with low rates correlating spatially with the emergence of HIV groups. We developed computer simulations to model the early spread of HIV-1 group M in Kinshasa before, during and after the estimated origin of the virus, using parameters derived from the colonial literature. These confirmed that the early 20th century was particularly permissive for the emergence of HIV by heterosexual transmission. The strongest potential facilitating factor was high GUD levels. Remarkably, the direct effects of city population size and circumcision frequency seemed relatively small. Our results suggest that intense GUD in promiscuous urban communities was the main factor driving HIV emergence. Low circumcision rates may have played a role, probably by their indirect effects on GUD

Stochastic simulation of HIV population dynamics through complex network modelling

We propose a new way to model HIV infection spreading through the use of dynamic complex networks. The heterogeneous population of HIV exposure groups is described through a unique network degree probability distribution. The time evolution of the network nodes is modelled by a Markov process and gives insight in HIV disease progression. The results are validated against historical data of AIDS cases in the USA as recorded by the Center of Disease Control. We find a remarkably good correspondence between the number of simulated and registered HIV cases, indicating that our approach to modelling the dynamics of HIV spreading through a sexual network is a valid approach that opens up completely new ways of reasoning about various medication scenarios