Title |
Simulation of an SEIR infectious disease model on the dynamic contact network of conference attendees
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Published in |
BMC Medicine, July 2011
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DOI | 10.1186/1741-7015-9-87 |
Pubmed ID | |
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 |
Abstract |
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. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
France | 4 | 22% |
Belgium | 2 | 11% |
United Kingdom | 2 | 11% |
United States | 2 | 11% |
Japan | 1 | 6% |
Unknown | 7 | 39% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 10 | 56% |
Scientists | 7 | 39% |
Practitioners (doctors, other healthcare professionals) | 1 | 6% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 9 | 3% |
France | 4 | 2% |
Italy | 3 | 1% |
United Kingdom | 2 | <1% |
Portugal | 1 | <1% |
Sweden | 1 | <1% |
Germany | 1 | <1% |
India | 1 | <1% |
Spain | 1 | <1% |
Other | 1 | <1% |
Unknown | 241 | 91% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 73 | 28% |
Researcher | 48 | 18% |
Student > Master | 30 | 11% |
Professor > Associate Professor | 17 | 6% |
Professor | 13 | 5% |
Other | 52 | 20% |
Unknown | 32 | 12% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 41 | 15% |
Agricultural and Biological Sciences | 37 | 14% |
Physics and Astronomy | 33 | 12% |
Mathematics | 24 | 9% |
Medicine and Dentistry | 22 | 8% |
Other | 54 | 20% |
Unknown | 54 | 20% |