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BMC Medicine
Published in: BMC Medicine 1/2011

Open Access 01-12-2011 | Research article

Simulation of an SEIR infectious disease model on the dynamic contact network of conference attendees

Authors: Juliette Stehlé, Nicolas Voirin, Alain Barrat, Ciro Cattuto, Vittoria Colizza, Lorenzo Isella, Corinne Régis, Jean-François Pinton, Nagham Khanafer, Wouter Van den Broeck, Philippe Vanhems

Published in: BMC Medicine | Issue 1/2011

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Abstract

Background

The spread of infectious diseases crucially depends on the pattern of contacts between individuals. Knowledge of these patterns is thus essential to inform models and computational efforts. However, there are few empirical studies available that provide estimates of the number and duration of contacts between social groups. Moreover, their space and time resolutions are limited, so that data are not explicit at the person-to-person level, and the dynamic nature of the contacts is disregarded. In this study, we aimed to assess the role of data-driven dynamic contact patterns between individuals, and in particular of their temporal aspects, in shaping the spread of a simulated epidemic in the population.

Methods

We considered high-resolution data about face-to-face interactions between the attendees at a conference, obtained from the deployment of an infrastructure based on radiofrequency identification (RFID) devices that assessed mutual face-to-face proximity. The spread of epidemics along these interactions was simulated using an SEIR (Susceptible, Exposed, Infectious, Recovered) model, using both the dynamic network of contacts defined by the collected data, and two aggregated versions of such networks, to assess the role of the data temporal aspects.

Results

We show that, on the timescales considered, an aggregated network taking into account the daily duration of contacts is a good approximation to the full resolution network, whereas a homogeneous representation that retains only the topology of the contact network fails to reproduce the size of the epidemic.

Conclusions

These results have important implications for understanding the level of detail needed to correctly inform computational models for the study and management of real epidemics.
Please see related article BMC Medicine, 2011, 9:88
Appendix
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Metadata
Title
Simulation of an SEIR infectious disease model on the dynamic contact network of conference attendees
Authors
Juliette Stehlé
Nicolas Voirin
Alain Barrat
Ciro Cattuto
Vittoria Colizza
Lorenzo Isella
Corinne Régis
Jean-François Pinton
Nagham Khanafer
Wouter Van den Broeck
Philippe Vanhems
Publication date
01-12-2011
Publisher
BioMed Central
Published in
BMC Medicine / Issue 1/2011
Electronic ISSN: 1741-7015
DOI
https://doi.org/10.1186/1741-7015-9-87

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