Title: Heterogeneities in contact and their effect on disease spreading: two examples
- When:
- Monday, August 6, 2012, 11:00 am - 12:00 pm
- Where:
- 10th fl CR (1026)
- Speaker:
- Andrea Apolloni
- Description:
- Postdoc Interview candidate
Host: Kristina Lerman
Abstract: Abstract
For a long period of time Kermack McKendrick S.I.R. model has been used to study the diusion of influenza like illness in a closed population. Individuals are divided in three compartments (Susceptible, Infectious and Recovered) and the dynamics of the epidemics is described in terms of a set of dierential equation. The main assumption relies on the
homogeneous mixing among individuals.However recent works has shown contact network are highly heterogeneous and this fact has dramatically effects on the diusions of epidemics. Many models have been developed to study the topological characteristics of network and how they in influence the dynamics of the processes defined over them. In most of the cases, theoretical analysis has been limited to the study of static networks. This is a good approximation when we consider processes that operate on a time-scale much smaller than the network's evolution. However, when the process has a time-scale comparable to that of the network's evolution, for example in the cases of bluetooth worm diffusion, epidemics and rumors spreading, only numerical approaches are possible. In this talk I present some results from studies on the eects of contact heterogeneities on the diffusion of in influenza like illness either at local either at world-wide scale. In the first case using synthetic populations that evaluate vaccine policy as well as diusion of information by word of mouth in an urban area. This approach uses an agent based model where individuals are endowed with demographic characteristics and a routine of activities drawn from surveys.
Links among individuals are creating only when they share the same location at the same time. The model achieves a second-to-second timescale, thus network topology changes rapidly. This kind of representation is highly detailed and due to the absence of any a priori dynamic can be considered as a proxy to reality. In the second case, a more accurate meta-population model, that takes account of contact heterogeneities in a city, is used to study under which conditions an epidemic seeded in a city can spread through all the worldwide network.Bio: Andrea Apolloni took his Ph.D. in high energy theoretical at Turin University (IT), defending a thesis about new phase transition in large-N Yang Mills theory.Since 2007 has been working on complex system and diffusion processes over evolving network, first as a post doc at Virginia Tech, then at ENS-Lyon France and since November 2011 at I.S.I. Turin. His main activities include: optimal vaccine distribution; simulation of epidemics spreading at worldwide level; study of obesity spreading among american teenagers; analysis of scientific collaboration network; theoretical model of diffusion processes over evolving network.
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