Suruchi Deodhar

Learn More
We describe the design and prototype implementation of I<scp>ndemics</scp> (&lowbar;Interactive; Epi&lowbar;demic; &lowbar;Simulation;)&#8212;a modeling environment utilizing high-performance computing technologies for supporting complex epidemic simulations. I<scp>ndemics</scp> can support policy analysts and epidemiologists interested in planning and(More)
We present an integrated interactive modeling environment to support public health epidemiology. The environment combines a high resolution individual-based model with a user-friendly Web-based interface that allows analysts to access the models and the analytics backend remotely from a desktop or a mobile device. The environment is based on a loosely(More)
Public health policy decision makers need analytical and interactive features in epidemic simulation systems, along with the ability to simulate disease propagation over large scale populations, ranging over millions of individuals. To fulfill these requirements, we decided to re-engineer existing epidemiological software systems and integrate them together(More)
Realistic agent-based epidemic simulations usually involve a large scale social network containing individual details. The co-evolution of epidemic dynamics and human behavior requires the simulation systems to compute complex real-world interventions. Calls from public health policy makers for executing such simulation studies during a pandemic typically(More)
Public health decision makers need access to high resolution situation assessment tools for understanding the extent of various epidemics in different regions of the world. In addition, they need insights into the future course of epidemics by way of forecasts. Such forecasts are essential for planning the allocation of limited resources and for(More)
  • 1