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Tags for studying the spread of epidemics

Date:
July 24, 2011
Source:
CNRS (Délégation Paris Michel-Ange)
Summary:
Participants in a congress were asked to wear a tag for two days in order to study their movements and interactions within a population. The data, collected by a French-Italian team, makes it possible to envisage the simulation of the spread of infection risks within a population, or even the optimization of the response to the expansion of an epidemic.
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Participants in a congress were asked to wear a tag for two days in order to study their movements and interactions within a population. The data, collected by a French-Italian team including researchers from CNRS, Inserm, the Université Claude Bernard Lyon1 and the CHU de Lyon, makes it possible to envisage the simulation of the spread of infection risks within a population, or even the optimization of the response to the expansion of an epidemic.

The results of this work are published in BMC Medicine.

Until now, data concerning the dynamic of contacts was vague: it was often assumed that within a group, each individual could be confronted with another according to an average estimation of the frequency and duration of contacts. In the case of an infectious risk, the determined probability of infection was consequently not representative: in fact, in epidemiology, a single contact lasting one minute does not have the same impact as a repeated or longer contact.

As part of the SocioPatterns project, a team gathering physicists and epidemiologists from CNRS laboratories and other organizations took the opportunity of a two-day congress to measure the contacts between the 500 participants, each of whom agreed to wear a RFID (radiofrequency identification device). These tags made it possible to detect when two individuals were close together and faced each other. The devices were able to intercommunicate through the emission of very low intensity waves (1,000 times weaker than a mobile telephone) at a distance comprised between 1 and 2 meters. After collecting and processing the data by computer, the researchers succeeded in modeling the dynamic of contacts.

This has enabled the team to precisely define the relations between individuals in terms of temporal data, namely duration and frequency. Modeling the dynamic of actual interactions in a population makes it possible to simulate the spread of infection and, in the long term, envisage a better response in the event of an epidemic. To refine the model, the team intends to gather complementary information, which is why contacts between pupils at a school are currently being analyzed and the measurement infrastructure has already been deployed for a study in a hospital in Rome. In the future, it will be possible to envisage integrating this new inter-tag communication within businesses or in new technologies, since smartphones are already very well equipped with sensors.

Note: The team headed on the French side by Alain Barrat of the Centre de Physique Théorique (CNRS/Université de la Méditerranée /Université de Provence/Université du Sud-Toulon-Var), Jean-François Pinton of the Laboratoire de Physique de l'ENS de Lyon (CNRS/ENS Lyon/Université Claude Bernard Lyon 1), Philippe Vanhems of the Laboratoire de Biométrie et Biologie Evolutive (CNRS/Université Claude Bernard Lyon 1/Inria/VetAgro Sup), Vittoria Colizza of the Laboratoire Epidémiologie, Système d'Information, Modélisation (Inserm/UPMC) and on the Italian side by Ciro Cattuto (ISI Foundation, Turin).


Story Source:

Materials provided by CNRS (Délégation Paris Michel-Ange). Note: Content may be edited for style and length.


Journal Reference:

  1. Juliette Stehle, Nicolas Voirin, Alain Barrat, Ciro Cattuto, Vittoria Colizza, Lorenzo Isella, Corinne Regis, Jean-Francois Pinton, Nagham Khanafer, Wouter Van den Broeck, Philippe Vanhems. Simulation of an SEIR infectious disease model on the dynamic contact network of conference attendees. BMC Medicine, 2011; 9 (1): 87 DOI: 10.1186/1741-7015-9-87

Cite This Page:

CNRS (Délégation Paris Michel-Ange). "Tags for studying the spread of epidemics." ScienceDaily. ScienceDaily, 24 July 2011. <www.sciencedaily.com/releases/2011/07/110722130259.htm>.
CNRS (Délégation Paris Michel-Ange). (2011, July 24). Tags for studying the spread of epidemics. ScienceDaily. Retrieved July 17, 2024 from www.sciencedaily.com/releases/2011/07/110722130259.htm
CNRS (Délégation Paris Michel-Ange). "Tags for studying the spread of epidemics." ScienceDaily. www.sciencedaily.com/releases/2011/07/110722130259.htm (accessed July 17, 2024).

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