Abstract
Simulation models for disease propagation have been widely used over the last several years. Such models allow one to study and evaluate the potential impacts of various government intervention policies. However, due to the lack of common guidelines, researchers have built simulation models separately and often in isolation, resulting in the repeated re-invention of the wheel. This paper provides a broad review of disease propagation simulation models. We discuss methods for generating susceptible populations, the choice of influenza transmission parameters, and various mitigation strategies. Our aim is to provide the information needed for researchers, practitioners, and decision makers to build simulation models for influenza propagation in particular (and disease propagation in general), and to use these models to better understand diseases, analyze people's behaviors, and identify appropriate intervention strategies.
Acknowledgments
We thank Paul Goldsman and Azhar Nizam for stimulating conversations and helpful suggestions. We also thank the editor and referees for their timely comments and suggestions.