The Modeling of Global Epidemics: Stochastic Dynamics and Predictability
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The global spread of emergent diseases is inevitably entangled with the structure of the population flows among different geographical regions. The airline transportation network in particular shrinks the geographical space by reducing travel time between the world's most populated areas and defines the main channels along which emergent diseases will spread. In this paper, we investigate the role of the large-scale properties of the airline transportation network in determining the global propagation pattern of emerging diseases. We put forward a stochastic computational framework for the modeling of the global spreading of infectious diseases that takes advantage of the complete International Air Transport Association 2002 database complemented with census population data. The model is analyzed by using for the first time an information theory approach that allows the quantitative characterization of the heterogeneity level and the predictability of the spreading pattern in presence of stochastic fluctuations. In particular we are able to assess the reliability of numerical forecast with respect to the intrinsic stochastic nature of the disease transmission and travel flows. The epidemic pattern predictability is quantitatively determined and traced back to the occurrence of epidemic pathways defining a backbone of dominant connections for the disease spreading. The presented results provide a general computational framework for the analysis of containment policies and risk forecast of global epidemic outbreaks.
KeywordsComplex networks Epidemiology
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- Anderson, R.M., May, R.M., 1992. Infectious Diseases in Humans. Oxford University Press, Oxford, p. 4Google Scholar
- Baroyan, O.V., Genchikov, L.A., Rvachev, L.A., Shashkov, V.A., 1969. An attempt at large-scale influenza epidemic modelling by means of a computer. Bull. Int. Epidemiol. Assoc. 18, 22–31.Google Scholar
- Flahault, A., Valleron, A.-J., 1991. A method for assessing the global spread of HIV-1 infection based on air-travel. Math. Pop. Studies 3, 1–11.Google Scholar
- Gardiner W.C., 2004. Handbook of Stochastic Methods for Physics, Chemistry and Natural Sciences, 3rd ed. Springer, New York.Google Scholar
- Hethcote, H.W., Yorke, J.A., 1984. Gonnorhea: Transmission Dynamics and Control. Lecture Notes in Biomathematics 56. Springer-Verlag, Berlin.Google Scholar
- Institute of Medicine 1992. Emerging Infections: Microbial Threats to Health in the United States. National Academy Press, Washington, DC.Google Scholar
- Lee, L., 1999. Paper presented in the 37th Annual Meeting of the Association for Computational Linguistics, pp. 25–32.Google Scholar
- Marro, J., Dickman, R., 1998. Nonequilibrium Phase Transitions and Critical Phenomena. Cambridge University Press, Cambridge, UK.Google Scholar
- Pastor-Satorras, R., Vespignani, A., 2003. Evolution and Structure of the Internet: A Statistical Physics Approach. Cambridge University Press, Cambridge, UK.Google Scholar
- Zipf, G.K., 1949. Human Behavior and the Principle of Least Efforts. Addison-Wesley, Reading, MA.Google Scholar