GLEaM has been used in a new publication comparing the performance of  large-scale computational approaches to  the modeling of infectious disease spreading The detailed results can be found in the manuscript:

Comparing large-scale computational approaches to epidemic modeling: agent-based versus structured metapopulation models
Marco Ajelli, Bruno Gonçalves, Duygu Balcan, Vittoria Colizza, Hao Hu, Jose J Ramasco, Stefano Merler and Alessandro Vespignani
BMC Infectious Diseases 2010, 10:190.

In recent years, two major classes of methodologies emerged in the large-scale and spatial spreading simulation of influenza-like-illnesses (ILIs) and other emerging infectious diseases. The first one is the very accurate epidemic description with agent-based models, which keep track of each individual in the population in an extremely detailed way. The second scheme relies on metapopulation structured models that considers in a detailed way the long range mobility scheme at the inter-population level while using coarse-grained techniques at the intra-population level. It is clearly important to assess the level of agreement that the two different approaches can provide on the quantities accessible in both cases and the respective data needed and computational costs associated.

Snapshots of the epidemic evolution in GLEaM (top) and in the agent-based model (bottom) at three different timesteps of the simulation with R0=1.9. Maps report the average number of cases at the resolution scale of the Italian municipalities.

The paper by Ajelli and co-workers contains the first side-by-side comparison of the results obtained with an Agent-Based model and metapopulation approach offered GLEaM. The two models are carefully calibrated in order to simulate an epidemic described by the same natural history and key parameters.  The country used for the study is Italy, a large European country that provides the necessary geographical and population heterogeneity to assess the models performance in the case of highly structured populations. For the sake of clarity, the two models consider a hypothetical influenza pandemic event for which the same parameterization and initial conditions in the far east. Both models, despite the difference in the data integration and model structure, provide epidemic profiles with spatio-temporal patterns in very good agreement.

The good agreement of the two approaches reinforces the message that computational approaches are stable with respect to different data integration strategies and modeling assumption.The presented results hint to the possibility of combining the two methodologies in order to devise multiscale approaches that use the data parsimony of the metapopulation approaches at the global level and the high resolution of the agent-based model in specific locations of interest where detailed data are available.

The Public Edition of the GLEaMviz Simulator becomes available.

The GLEaMviz Simulator is a software system with an intuitive and flexible GUI for the simulation of emerging infectious diseases spreading across the world, that we developed during the last 2 years. The software system levers on GLEaM, and its design maximizes 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 geotemporal evolution of the disease.

Download the GLEaMviz Simulator and explore your global epidemic simulations!

The software is based on a Client-server system. The Client can be installed on the user’s local machine, and it allows the user to setup the simulations that will be executed on the server, thus avoiding specific requirements for large computational capabilities on the user’s side. The Client consists of four principal components: 1) the main window with the Simulations History; 2) the Compartmental Model Builder; 3) the Simulation Wizard; and 4) the Visualization Windows. The main workflow and the role of the components are outlined in the diagram in the Figure below.

Overview of the workflow of the GLEaMviz Simulator.

The GLEaMviz Simulator Client uses the Adobe AIR 1.5 runtime and can thus be installed on recent versions of the following operating systems: Windows, Mac OS X,  Linux. The Public Edition of the client available from http://www.gleamviz.org/simulator/ is pre-configured to use the GLEaMviz server made available by gleamviz.org. There is thus no need to install the server in order to use this client. However, in order to avoid an overload on this server, a number of limitations are enforced in this setup. Research groups interested in an unlimited version of the GLEaMviz system are invited to contact us at info@gleamviz.org.

Check out all the software features at the GLEaMviz Simulator webpage!

The Global Epidemic and Mobility (GLEaM) computational platform has been developed over many years and it has been used mostly for research purposes. The final goal of this project is however the development of a computational tool to be used to forecast and anticipate the spreading of emerging diseases, as we have attempted and documented on this site and the ensuing scientific publications for the 2009 H1N1 pandemic. On the other hand, the use of such a tool cannot be limited to a few research groups with specific computational skills and  we are working to make the GLEaM platform available to the scientific community at large. In particular we aim at developing an easy to use interface to the software.

For this purpose, we developed the GLEaMviz Simulator, which is a software that allows the simulation and visualization of the spread of epidemics at the worldwide scale. It allows the user to specify and remotely execute simulations, and retrieve and visualize the results. The Simulation Engine is based on GLEaM, and the Client is made of different components that enable a customizable compartmentalization to describe a specific infection dynamics, the set up of a specific simulation initialization (e.g. time and place of seed event in the world, presence or not of prior immunity, presence of seasonal effects, etc.), the remote execution of GLEaM simulations and the visualization of the results in forms of maps and plots for different geographic areas and levels of resolutions chosen by the user.

The Software architecture ensures great flexibility and maintainability as well as high speed in large-scale simulations. The Client is user-friendly and meant to be used to produce global simulations based on GLEaM with no specific knowledge on coding/modeling needed.
Have a look at this video presenting an overview of the GLEaMviz Simulator.

GLEaMviz Simulator Overview from GLEaMviz on Vimeo.

Developing the GLEaMviz simulator faces us with several computational challenges and requires to analyze the specific use of the simulator in the context of different decision making processes  (crisis rooms, public health planning, research etc.).  For this reason we are partnering with the JOINT RESEARCH CENTER (JRC) of the European Commission at Ispra, Italy. The Joint Research Centre is a research based policy support organisation and an integral part of the European Commission. The mission of the JRC is to provide customer-driven scientific and technical support for the conception, development, implementation and monitoring of EU policies. As a service of the European Commission, the JRC functions as a reference centre of science and technology for the Union. The objective of the collaboration is to share tools, including the GLEaM paltform to improve models for crisis management and decision making of emerging public health threats. We are proud to announce that the first version of the GLEaMviz Simulator has been released to JRC where usability tests have been started.

What is keeping us busy: we are now fine tuning the Software to include additional details and improve its usability.

We plan to post soon the first public release of the Client of the GLEaMviz Simulator. More info will soon be available on this website. Stay tuned!

The 22nd edition of the Edinburgh International Science Festival, running from April 3 to 17, 2010, features a special event, Meet the Medics and Vets, with the contribution of:

Epidemic Planet - explore how H1N1 influenza travels around the world and how intervention measures may help

Epidemic Planet  is the visualization application developed in the context of the GLEaMviz project, which enables its users to interactively compare and learn about the effect of a number of intervention scenarios on a pandemic, simulated using GLEaM. Its first public appearance was at the 3 months long INFECTIOUS Art & Science exhibition at the Science Gallery, Trinity College, Dublin, Ireland.

In collaboration with the British Society for Immunology, Epidemic Planet lands at the Edinburgh International Science Festival. In this installation, visitors will observe the evolution of the 2009 H1N1 influenza pandemic since its early origin in Mexico, and will discover how the air traffic and commuting flows determined the spreading patterns of the flu worldwide.

Moreover, through a large screen coupled with a touch-screen interface, visitors will be able to explore different scenarios of propagation of the H1N1 pandemic according to different initial conditions (what if the flu started in Edinburgh? what if it were more contagious?) and different intervention measures. In this way, they will learn how the flights ban or the early distribution of vaccines could have affected the spreading of the pandemic.

The venue of the Epidemic Planet exhibition will be Hawthornden Court, in the National Museum of Scotland. Check out the programme of the Festival!

Come and visit the Epidemic Planet in Edinburgh!

The February 2010 issue of Physics World presents a special focus on Complexity and challenges in Network Science. From mapping the rise of the field, to examples of applications rooted in our everyday life, to charting the field’s possible future evolution, the special issue explores the key topics of Network Science - a field where physicists have been playing a major role.

Physics World, February 2010 issue.

The Flu Fighters.

A special feature is dedicated to infectious diseases, how they rapidly spread in our modern society, and what weapons we have nowadays to fight them.  The article titled The Flu Fighters by Vittoria Colizza and Alessandro Vespignani describes the contribution of physicists to an interdisciplinary area where complex systems are the main ingredients, and modeling human behavior and biological contagion is the ultimate challenge. The cover of the special issue shows an illustration by B. Goncalves et al. of the multiscale worldwide mobility networks used in the GLEaM model.

PNAS cover image.

In the issue of December the 22nd of the Proceedings of the National Academy of Sciences, we publish a paper that discusses the interplay of human mobility patterns like those between local metropolitan commuters and long-range airline travelers during a global epidemic. The image of the worldwide mobility network constructed in our paper has been featured in the cover of the journal.

Multiscale mobility networks and the spatial spreading of infectious diseases.
D.Balcan, V. Colizza, B. Gonçalves, H. Hu, J. J. Ramasco, A. Vespignani
Proc Natl Acad Sci U S A 106, 21484-21489 (2009).

In the paper we detail the definition of the worldwide multiscale mobility network at the core of the Global Epidemic and Mobility (GLEaM) model and discuss the data integration process and the statistical analysis that allow its construction.

Have a look at this video presenting an overview of the GLEaM model.

We also tackle some general theoretical questions that concerns the basic understanding of the spatial spread of infectious diseases on the large scale:
i)    Is there a most relevant mobility scale in the definition of the global epidemic pattern?
ii)    At which level of resolution of the epidemic behavior a given mobility scale starts to be relevant and to which extent?

In order to fully consider the effect of multiscale mobility processes we first integrate data of commuting patterns in five different continents with the airline transportation database and then develop a time-scale separation technique for evaluating the force of infection due to different mobility couplings and simulate global pandemics with tunable reproductive ratios. The results obtained from the full multiscale mobility network are compared to the simulations in which only the large scale coupling of the airline transportation network is included. Our analysis shows that while commuting flows are, on average, one order of magnitude larger than the long-range airline traffic, the global spatio-temporal patterns of disease spreading are mainly determined by the airline network. Short-range commuting interactions have on the other hand a role in defining a larger degree of synchronization of nearby subpopulations and specific regions which can be considered weakly connected by the airline transportation system.

It also is possible to show that short-range mobility has an impact in the definition of the subpopulation infection hierarchy. In other words, global disease outbreaks tend to touch down at major travel hubs, generally major airport locations and spread out like a wave that follow local commuting patterns. The findings of the paper open the path to quantitative approximation schemes that calibrate the level of data resolution and the needed computational resources with respect to the accuracy in the description of the epidemics.

The techniques developed here allow for an understanding of the level of data integration required to obtain reliable results in large scale modeling of infectious diseases and have already have contributed to the improvement of the computational model we use to provide estimates and projections of the H1N1 pandemic.

Airneth is a worldwide scientific network for aviation research and policy, which has started a series of columns by its fellows, in which they touch upon their current research and/or aviation projects.

In a special issue Airneth Column, titled  “People interact. They travel. And diseases might travel with them”, Vittoria Colizza discusses the effects of travel flows on epidemic phenomena.

In the figure below the arrows represent the seeding of countries by infected travelers, during the early outbreak of the new H1N1 influenza, and the color code indicates the time of seeding.

Global invasion of the H1N1 influenza by air travel during the early outbreak.