The HEP-CE (Hepatitis C Cost Effectiveness) model is a Markov
chain Monte Carlo health state-transition model which simulates the spread and
treatment of Hepatitis C Virus (HCV) in the United States. The model uses
values and information derived from a variety of sources, including clinical
data and relevant literature. HEP-CE is used to model the efficacy and
cost-effectiveness of treatments, policies, and interventions aimed at
controlling the HCV epidemic on a population-wide basis by understanding the
effects of changes on individual persons' quality of life.
The HEP-CE model you see here is a refactor of an earlier
version of the model. This new,
improved version attempts to improve upon key pain points in the previous
incarnation, namely:
- Converting to a Discrete Event Simulation structure
- Improving readability
- Simplify input file structure
This recapitulation of HEP-CE iterates across timesteps and events rather than
over person lives, as past versions did. Each timestep (month), the simulated
population is subjected to discrete events. Measurables are stored at the
individual Person level and are written to a table at the end of the simulation.
At the top level, the model is broken down into three categories of events:
- Person-Level Events
- Clinical Events
- Calculation Events
These categories are further broken into discrete events:
- Person-Level Events:
- Aging
- Drug Behavior Changes
- Acute HCV Clearance
- Liver Disease Progression
- Infections
- Overdose
- Death
- Clinical Events:
- HCV Screening
- Linking to Care
- Voluntary Relinking to Care
- Fibrosis Staging
- Treatment
- Calculation Events:
- Transmission (PreVenT)
- DataManagement
- GoogleTest/
gtest(optional, used for unit testing) - Ninja
- spdlog
- SQLiteCpp
Ensure that you have Ninja available in your environment, then run the following commands.
git clone [email protected]:SyndemicsLab/hep-ce
cd hep-ce
cmake --workflow --preset gcc-release