The GLEAM Simulator system consists of the GLEAM Server and the GLEAMviz Client application.
The GLEAM Server uses GLEAM as the engine to perform the simulations. This server runs on high-performance computers managed by the GLEAM project.
The GLEAMviz Client is a desktop application through which users interact with the GLEAM Server. It provides a simple, intuitive and visual way to set up simulations, develop disease models, and evaluate simulation results using a variety of maps, charts and data analysis tools.
You can install and test a public version of the GLEAMviz desktop application on your computer today!
The GLEAMviz desktop application is the main interface through which users interact with the GLEAM engine. This desktop application provides a simple, intuitive and visual way to set up simulations, develop disease models, and evaluate simulation results using a variety of maps, charts and data analysis tools.
Before putting the GLEAM engine to work, you must first define the epidemic model and configure the simulation scenario. To help non-technical experts, GLEAMviz provides an intuitive graphical interface to make this modeling processes straightforward and flexible.
Once defined, simulations can be submitted to the GLEAM engine that then performs the complicated statistical calculations. Once complete, the results are retrieved and stored by the Simulation Manager. This module also manages archived simulations and results, and allows you to inspect epidemic models, export data and launch visualizations.
Visualisation and analysis
GLEAMviz offers three types of visualization. The first shows the spread of the infection on a zoomable 2D map while charts show the number of new cases at various levels of detail.
The following movie demonstrates the animated visualisation of the epidemic spreading over time.
A second mapping displays the spread of the infection on an interactive 3D globe. This interface provides you with a concise global overview of the spread.
The following movie demonstrates the animated visualisation of the epidemic spreading and the initial seeding over time.
The third option highlights how the structure of the airport network influences the notion of distance. It remaps all the transportation hubs according to the time it takes for the infection to reach them from the moment of outbreak.
We regularly add new features and refine our modeling interface and visualizations, and our charting capabilities.