Simulation and Mathematical Modeling
Simulation and Mathematical Modeling (SMM) will be performed in collaboration with Dr. Olivia Keiser, Institute of Social and Preventive Medicine, University of Bern, Switzerland and Dr. Janne Estill, Institute of Social and Preventive Medicine, University of Bern, Switzerland.
The mathematical models we develop are disease progression, state-transition Monte Carlo simulation models that characterize progression of a disease or health condition from a particular state to the final outcome of concern. The progression of a disease or condition is represented with stages (disease or health states) and transitions. The stages describe the patient’s health, current and previous (history), other co-morbidities, disability, injury, social characteristics, overall and specific quality of life, and utilization of health care. Transitions occur from one stage to another. These mathematical models are designed to be predictive of clinical prognosis, including disease progression, immunologic deterioration, development and relapse of opportunistic infections, medication toxicity, response to therapy, and mortality. The models are parameterized using data from literature and also from individual patient data or programmatic data. Varying the data parameters of the independent variables, the outcomes can be compared between different interventions.