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

Autor: Ciro Cattuto, Vittoria Colizza, Wouter Van den Broeck, Lorenzo Isella, Alain Barrat, Philippe Vanhems, Jean-François Pinton, Juliette Stehlé, Nagham Khanafer, Nicolas Voirin, Corinne Régis
Přispěvatelé: Centre de Physique Théorique - UMR 6207 (CPT), Université de la Méditerranée - Aix-Marseille 2-Université de Provence - Aix-Marseille 1-Université de Toulon (UTLN)-Centre National de la Recherche Scientifique (CNRS), Centre de Physique Théorique - UMR 7332 (CPT), Aix Marseille Université (AMU)-Université de Toulon (UTLN)-Centre National de la Recherche Scientifique (CNRS), CPT - E5 Physique statistique et systèmes complexes, Aix Marseille Université (AMU)-Université de Toulon (UTLN)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Université de Toulon (UTLN)-Centre National de la Recherche Scientifique (CNRS), Service d'Hygiène, Epidémiologie et Prévention [Hôpital Edouard Herriot - HCL], Hôpital Edouard Herriot [CHU - HCL], Hospices Civils de Lyon (HCL)-Hospices Civils de Lyon (HCL), Laboratoire de Biométrie et Biologie Evolutive - UMR 5558 (LBBE), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS), Data Science Laboratory, Institute for Scientific Interchange (ISI) Foundation, Epidémiologie des maladies infectieuses et modélisation (ESIM), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut National de la Santé et de la Recherche Médicale (INSERM), Computational Epidemiology Laboratory (CERL), ISI Foundation Institute for Scientific Interchange, Laboratoire de Physique de l'ENS Lyon (Phys-ENS), École normale supérieure de Lyon (ENS de Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Centre National de la Recherche Scientifique (CNRS), This project was partly supported by La Société Française d'Hygiène Hospitalière and GOJO France. This study was partly supported by a grant of the Programme de Recherche, A(H1N1) co-ordinated by the Institut de Microbiologie et Maladies Infectieuses., Centre National de la Recherche Scientifique (CNRS)-Université de Toulon (UTLN)-Université de Provence - Aix-Marseille 1-Université de la Méditerranée - Aix-Marseille 2, École normale supérieure - Lyon (ENS Lyon)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon, École normale supérieure - Lyon (ENS Lyon)-Université Claude Bernard Lyon 1 (UCBL), BMC, Ed.
Jazyk: angličtina
Rok vydání: 2011
Předmět:
Physics - Physics and Society
Computer science
Population
lcsh:Medicine
FOS: Physical sciences
Physics and Society (physics.soc-ph)
computer.software_genre
Quantitative Biology - Quantitative Methods
01 natural sciences
Dynamic contact
03 medical and health sciences
Empirical research
[SDV.MHEP.MI]Life Sciences [q-bio]/Human health and pathology/Infectious diseases
[SDV.BBM.GTP]Life Sciences [q-bio]/Biochemistry
Molecular Biology/Genomics [q-bio.GN]
0103 physical sciences
Radio-frequency identification
010306 general physics
education
Quantitative Methods (q-bio.QM)
030304 developmental biology
Medicine(all)
0303 health sciences
Computational model
education.field_of_study
business.industry
lcsh:R
General Medicine
3. Good health
Homogeneous
Software deployment
Infectious disease (medical specialty)
FOS: Biological sciences
[SDV.MHEP.MI] Life Sciences [q-bio]/Human health and pathology/Infectious diseases
[SDV.BBM.GTP] Life Sciences [q-bio]/Biochemistry
Molecular Biology/Genomics [q-bio.GN]
Data mining
business
computer
Zdroj: BMC Medicine
BMC Medicine, 2011, 9 (1), pp.87. ⟨10.1186/1741-7015-9-87⟩
BMC Medicine, BioMed Central, 2011, 9 (1), pp.87. ⟨10.1186/1741-7015-9-87⟩
BMC Medicine, Vol 9, Iss 1, p 87 (2011)
ISSN: 1741-7015
Popis: 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
Databáze: OpenAIRE
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