Global Epidemic and Mobility Model: GLEaM
We are working on the development and refinement of computational techniques for the in-silico simulation of the spatial spreading of infectious diseases in structured populations. The Global Epidemic and mobility (GLEaM) model we have developed is a discrete stochastic epidemic computational model based on a meta-population approach in which the world is defined in geographical census areas connected in a network of interactions by human travel fluxes corresponding to transportation infrastructures and mobility patterns. The model includes a multiscale mobility model integrating different layer of transportation networks ranging from the long range airline connections to the short range daily commuting pattern.
While the model is being developed and tested in the context of emerging diseases such as new pandemic strains, it considers different transportation and interaction layers and distinguishes the mobility modeling from the dynamical process mediated by the human dynamics. This allows the integration of different processes of social contagion that are not necessarily of biological origin. Given the multitude of scale and mobility layer existing in the GLEaM model, the process of interest can be studied on a wide range of scales ranging from small administrative units (counties, municipalities) to worldwide.
Recently we are working also on a software system with an intuitive and flexible GUI for the simulation of emerging infectious diseases spreading across the world. The software system levers on GLEaM, and its design maximizes the flexibility in the definition of the disease compartmental model and in the configuration of the simulation scenario, allowing the user to set a variety of parameters, from compartment-specific features, to transition values, to environmental effects. The output of the simulation is then provided in terms of a dynamic map visualization and sets of charts to quantitatively describe the geo-temporal evolution of the disease.
More information on the model and publicly available software tool can be found on the project webpage www.gleamviz.org.
We are working on the development and refinement of computational techniques for the in-silico simulation of the spatial spreading of infectious diseases in structured populations. The Global Epidemic and mobility (GLEaM) model we have developed is a discrete stochastic epidemic computational model based on a meta-population approach in which the world is defined in geographical census areas connected in a network of interactions by human travel fluxes corresponding to transportation infrastructures and mobility patterns. The model includes a multiscale mobility model integrating different layer of transportation networks ranging from the long range airline connections to the short range daily commuting pattern.
While the model is being developed and tested in the context of emerging diseases such as new pandemic strains, it considers different transportation and interaction layers and distinguishes the mobility modeling from the dynamical process mediated by the human dynamics. This allows the integration of different processes of social contagion that are not necessarily of biological origin. Given the multitude of scale and mobility layer existing in the GLEaM model, the process of interest can be studied on a wide range of scales ranging from small administrative units (counties, municipalities) to worldwide.
Recently we are working also on a software system with an intuitive and flexible GUI for the simulation of emerging infectious diseases spreading across the world. The software system levers on GLEaM, and its design maximizes the flexibility in the definition of the disease compartmental model and in the configuration of the simulation scenario, allowing the user to set a variety of parameters, from compartment-specific features, to transition values, to environmental effects. The output of the simulation is then provided in terms of a dynamic map visualization and sets of charts to quantitatively describe the geo-temporal evolution of the disease.
More information on the model and publicly available software tool can be found on the project webpage www.gleamviz.org.
