Abstract
Computer simulations have been used to model infectious diseases to examine the outcomes of alternative strategies for managing their spread. Methicillin resistant Staphylococcus aureus (MRSA) skin and soft tissue infections have become prominent in many communities and efforts are underway to reduce the spread of this organism both in hospitals and communities. Currently, there are few tools for policy makers to use to examine the outcome of various choices when making decisions about MRSA. Using the example of MRSA, we describe, in this paper, a rigorous approach for development and validation of a tool that simulates the spread of MRSA infections. We used sensitivity analyses in a novel way and validated the simulation results against local data over time. Our approach for simulation development and validation is generalizeable to simulations of other diseases. © 2010 Elsevier Inc.