Abstract

Background: Computational models play an increasingly important role in the assessment and control of public health crises, as demonstrated during the 2009 H1N1 influenza pandemic. Much research has been done in recent years in the development of sophisticated data-driven models for realistic computer-based simulations of infectious disease spreading. However, only a few computational tools are presently available for assessing scenarios, predicting epidemic evolutions, and managing health emergencies that can benefit a broad audience of users including policy makers and health institutions.

Results: We present "GLEaMviz", a publicly available software system that simulates the spread of emerging human-to-human infectious diseases across the world. The GLEaMviz tool comprises three components: the client application, the proxy middleware, and the simulation engine. The latter two components constitute the GLEaMviz server. The simulation engine leverages on the Global Epidemic and Mobility (GLEaM) framework, a stochastic computational scheme that integrates worldwide high-resolution demographic and mobility data to simulate disease spread on the global scale. The GLEaMviz design aims at maximizing flexibility in defining the disease compartmental model and configuring the simulation scenario; it allows the user to set a variety of parameters including: compartment-specific features, transition values, and environmental effects. The output is a dynamic map and a corresponding set of charts that quantitatively describe the geo-temporal evolution of the disease. The software is designed as a client-server system. The multi-platform client, which can be installed on the user's local machine, is used to set up simulations that will be executed on the server, thus avoiding specific requirements for large computational capabilities on the user side.

Conclusions: The user-friendly graphical interface of the GLEaMviz tool, along with its high level of detail and the realism of its embedded modeling approach, opens up the platform to simulate realistic epidemic scenarios. These features make the GLEaMviz computational tool a convenient teaching/training tool as well as a first step toward the development of a computational tool aimed at facilitating the use and exploitation of computational models for the policy making and scenario analysis of infectious disease outbreaks.

Notes

Originally published in BMC Infectious Diseases 2011, 11:37. doi:10.1186/1471-2334-11-37

This work has been partially funded by the NIH R21-DA024259 award, the Lilly Endowment grant 2008 1639-000 and the DTRA-1-0910039 award to AV; the EC-ICT contract no. 231807 (EPIWORK) to AV, VC, and WVdB; the EC-FET contract no.233847 (DYNANETS) to AV and VC; the ERC Ideas contract n.ERC-2007-Stg204863 (EPIFOR) to VC, CG, and MQ.

Dr. Vespignani is affiliated with Northeastern University as of the time of deposit.

Keywords

pandemic influenza, networks, predictability, strategies, mobility, impact, model, GLEaMviz, software

Subject Categories

Influenza, Epidemics

Disciplines

Physics

Publisher

BioMedCentral

Publication Date

2-2-2011

Rights Information

© 2011 Broeck et al; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Rights Holder

Broeck et al.

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This file includes information for installing the GLEaMviz Client and details of the features of its various components.

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Additional Files

fig1.pdf (128 kB)
Figure 1

fig2.pdf (2483 kB)
Figure 2

fig3.pdf (2945 kB)
Figure 3

fig4.pdf (526 kB)
Figure 4

fig5.PDF (202 kB)
Figure 5

fig6.PNG (490 kB)
Figure 6

fig7.PNG (199 kB)
Figure 7

fig8.PNG (1502 kB)
Figure 8

fig9.PNG (105 kB)
Figure 9

fig10.PDF (89 kB)
Figure 10

additional file.doc (67 kB)
This file includes information for installing the GLEaMviz Client and details of the features of its various components.

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