Title:  “Modeling of epidemics: from the physics of reaction-diffusion processes to infectious disease forecast”

Abstract:

Mathematical and computational methods have gained importance in the public-health domain, especially in epidemic modeling, by providing quantitative analysis in support of the policy-making processes. At the same time, the epidemic modeling metaphor has been introduced to describe a wide array of different phenomena. The spread of information, cultural norms, and social behavior can be all conceptually modeled as a contagion process. Although the basic mechanisms of each phenomenon are different, their effective mathematical description often defines similar constitutive equations and dynamical behaviors framed in the general theory of reaction-diffusion processes. In this lecture I will review the theoretical framework developed in recent years to understand the dynamic of reaction-diffusion processes in expanded schemes that explicitly include the many realistic features that characterize human mobility behavior, and complex interactions patterns. I will also discuss how this framework is at the core of data-driven computational approaches that, through the integration of large-scale data sets and the explicit simulation of entire populations down to the scale of single individuals, are successfully used in the analysis and forecast of real epidemics.