New GLEaMviz Simulator release and BMC publication about this publicly available software system

The GLEaMviz Simulator is a publicly available software system for exploring realistic epidemic spreading scenarios at the global scale. A new release of this system now offers an improved interface for the visualization of the results of simulations. The following movie provides some examples of how this new visualization shows the number of new cases at the cell-level, instead of the less detailed basin-level incidence representation used in the previous versions. The user can also choose other quantities to visualize.

The visualization can be extensively customized by clicking on the gear icon in the navigation interface, which opens up the configuration interface. The user can, for example, select from a number of backdrop maps onto which the visualization is projected, details of which are shown in the following figure. The option shown in the left panel is based on the NASA Blue Marble map, while the other two options provide a more neutral base onto which the cell-level cases can be inspected with greater visual accuracy.

Samples of the three backdrop maps from which the user can choose.

Samples of the three backdrop maps from which the user can choose.

The GLEaMviz Simulator is discussed in great detail in this new publication:

The GLEaMviz computational tool, a publicly available software to explore realistic epidemic spreading scenarios at the global scale.
Wouter Van den Broeck, Corrado Gioannini, Bruno Goncalves, Marco Quaggiotto, Vittoria Colizza, Alessandro Vespignani
BMC Infectious Diseases, 11:37 (2011)

The paper discusses the objectives and functionalities offered by this software system, comparing these with similar publicly available software tools. A detailed description of the implementation of both the client-side and server-side components that comprise the complete system are given, and a realistic simulation example and its results are discussed.

With this new release and this publication we hope to further our objective of providing public access to sophisticated computational models in teaching/training settings and in the use and exploitation of large-scale simulations in public health scenario analysis. In particular our focus is on the simulation of emerging ILI infectious diseases at the global scale based on a detailed data-driven spatial epidemic and mobility model that offers an innovative solution in terms of flexibility, realism, and computational efficiency.

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