GERMS: an epidemiologic simulation tool for studying geographic and social effects on infection transmission

The analysis, surveillance and control of infectious diseases are important functions of public health organizations around the world. This article describes the design and implementation of a simulation toolkit called GERMS (Geographic-Environmental Reinfection Modeling Simulator) that includes several innovations for modeling infectious disease transmission. These tools address several important issues for understanding the epidemiology of sexually transmitted infections. The model accounts for realistic infection transmission systems by explicitly modeling (i) heterogeneous populations of individuals with varying social and geographic characteristics, (ii) complex interactions between individuals to characterize opportunities for transmission, (iii) infection characteristics, such as transmission probabilities and infection duration, and (iv) contact and infection histories. Since public health organizations collect and use information regarding infected individuals, including geographic location and partnership data, the tool is well-equipped to help evaluate the effectiveness of interventions based on that data. We outline design decisions and present the results of initial simulation analysis. We also discuss short-term goals for extending the simulation toolkit to address the specific needs of the Centers for Disease Control.