We describe ISIS, a high-performance-computing-based application to support computational epidemiology of infectious diseases. ISIS has been developed over the last seven years in close coordination with public health and policy experts. It has been used in a number of important federal planning and response exercises. ISIS grew out of years of experience in developing and using HPC-oriented models of complex socially coupled systems. This identified the guiding principle that complex models will be used by domain experts only if they can do realistic analysis without becoming computing experts.

Using ISIS, one can carry out detailed computational experiments as they pertain to planning and response in the event of a pandemic. ISIS is designed to support networked epidemiology -- study of epidemic processes over social contact networks. The current system can handle airborne infectious diseases such as influenza, pertussis, and smallpox. ISIS is comprised of the following basic components: (i) a web app that serves as the user-interface, (ii) a middleware that coordinates user interaction via the web app with backend models and databases, (iii) a backend computational modeling framework that is comprised of highly resolved epidemic simulations combined with highly realistic control strategies that include pharmaceutical as well as non-pharmaceutical interventions and (iv) a backend data management framework that manages complex unstructured and semi-structured data.

ISIS has been used in over a dozen case studies defined by the DoD, DHHS, NIH, BARDA and NSC. We describe three recent studies illustrating the use of ISIS in real-world settings:(i) uses of ISIS during the H1N1 pandemic, Cii) supporting a US military planning exercise, and (iii) distribution of limited stockpile of pharmaceuticals using public and private outlets.