EvoNetHIV -- Agent based model for simulating HIV epidemics

Evonet Team: Steven Goodreau, Joshua Herbeck, John Mittler, James Murphy, Kathryn Peebles, Sarah Stansfield, Juandalyn Burke, Neil Abernethy, Geoffrey Gottlieb

2017-10-18 (in progress)

EvonetHIV is a stochastic agent-based simulation model that incorporates sexual network structure, behavior, HIV evolution, and treatment. Each simulation first estimates a statistical model that governs sexual network structure, and then proceeds through a burn-in period and epidemic simulation. At each time step of both the burn-in period and epidemic simulation, (1) partnerships form and dissolve; (2) sexual acts take place within a subset of existing partnerships; (3) HIV transmission occurs probabilistically within a subset of sexual acts; (4) viral dynamics and disease progression are updated for each infected agent; (5) vital dynamics, such as aging, are updated, and (6) testing and treatment are implemented at user-specified intervals.

Model Information (in progress)

EvoNet User Guide
Overview of model dynamics
Annotated EvoNet run script (simple example)
Agent attributes overview
Tutorials (coming soon)

Abstracts for In Prep / Submitted papers

Goodreau SM, Stansfield SE, Murphy JT, Peebles KC, Gottlieb GS, Abernethy NF, Herbeck JT, Mittler JE. (submitted). Sexual network structure, HIV prevalence, and the evolution of set point viral load.

Herbeck et al. HIV population-level adaptation can rapidly diminish the impact of a partially effective vaccine.

• (Complete Herbeck et al. paper at the Vaccine (journal) website)

Mittler et al. Agent-based network model predicts strong benefits to youth-centered HIV treatment-as-prevention efforts.