The CEPAC model is a computer-based, state-transition, Monte Carlo simulation model of the progression and outcomes of HIV disease. A “State-transition” model characterizes each patient’s progression as a sequence of monthly transitions from one “health state” to another. A “Monte Carlo” simulation uses a random number generator to generate one hypothetical patient at a time and draw from a set of transition probabilities to determine the occurrence of clinical events and health-state transitions experienced by the patient. The model uses a 1-month cycle length to reflect a realistic duration in which important events occur. Clinical events (e.g., acute opportunistic infections) and health-state transitions (e.g., changes in CD4 count or HIV RNA levels) are governed by probabilities estimated from clinical trials and epidemiologic datasets.
At the outset of any simulation, an initial cohort size and input parameters are defined including age, sex, CD4 count, and HIV RNA distribution. Also defined are probability distributions for various clinical events such as opportunistic infection and entrance to or dropping out of care for different patient states. From this distribution of demographic and clinical data, each patient’s clinical course is tracked from entry into the model until death. A running tally is maintained of all clinical events and of the cumulative cost and health-related quality of life (or “utility”) associated with the months in each health state. This process is repeated until the entire cohort has passed through the model, at which point overall performance measures such as average survival, quality-adjusted life expectancy, and per-patient cost are computed.
Health states are descriptive of the patient’s current health, relevant history, quality of life, and resource utilization patterns. They are designed to be predictive of clinical prognosis, including disease progression, immunologic deterioration, development and relapse of opportunistic infections, medication toxicity, response to ART (Antiretroviral Therapy), and mortality. The model defines four general categories of HIV health states: primary infection, chronic infection, acute event, and death. Patients usually reside in the chronic state, where immunologic deterioration occurs. Patients who develop an acute event (either an opportunistic infection or medication toxicity) temporarily move to an acute health state, where resource consumption and mortality rates increase while quality of life decreases. While death may occur from any health state, mortality rates from a given health state are based upon acute event history, CD4 cell count, and age, gender and race-specific non-HIV causes.
The HIV Dynamic Epidemic Framework (H-DEF) model, peer-reviewed and published adjunct to the CEPAC model, was recently developed to simulate dynamic population-level HIV transmission over time. Using CEPAC model output on survival and infectivity of a cohort of HIV-infected patients as well as data on population dynamics for the setting of interest, H-DEF is able to predict HIV infections in a susceptible population to make long-term projections of an evolving epidemic.
A more detailed look at the CEPAC model can be found in the following PDFs:
- CEPAC model flowcharts(CEPAC-US and CEPAC-International; CEPAC-Pediatrics): A detailed look at how each patient transitions through the model
- CEPAC model user's guide(CEPAC-US and CEPAC-International; CEPAC-Pediatrics): A comprehensive description of model structure, types of input data and approaches to model use
- CEPAC literature review protocol: An overview of where and how we get our input data
A more detailed look at the HDEF model can be found in the following PDFs: