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<identifier>oai:HAL:hal-00624364v1</identifier>
<datestamp>2017-12-21</datestamp>
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<publisher>HAL CCSD</publisher>
<title lang=en>Social network analysis in epidemiology: Current trends and perspectives</title>
<creator>Stattner, Erick</creator>
<creator>Vidot, Nicolas</creator>
<contributor>Laboratoire de Mathématiques Informatique et Applications (LAMIA) ; Université des Antilles et de la Guyane (UAG)</contributor>
<description>International audience</description>
<source>2011 Fifth International Conference on Research Challenges in Information Science (RCIS)</source>
<source>Research Challenges in Information Science</source>
<coverage>Gosier, Guadeloupe</coverage>
<contributor>IEEE</contributor>
<identifier>hal-00624364</identifier>
<identifier>https://hal.archives-ouvertes.fr/hal-00624364</identifier>
<source>https://hal.archives-ouvertes.fr/hal-00624364</source>
<source>IEEE. Research Challenges in Information Science, 2011, Gosier, Guadeloupe. pp.1-11, 2011, 〈10.1109/RCIS.2011.6006866〉</source>
<identifier>DOI : 10.1109/RCIS.2011.6006866</identifier>
<relation>info:eu-repo/semantics/altIdentifier/doi/10.1109/RCIS.2011.6006866</relation>
<language>en</language>
<subject lang=en>Spread of disease</subject>
<subject lang=en>Social Network</subject>
<subject lang=en>Epidemics</subject>
<subject lang=en>Infectious disease</subject>
<subject lang=en>Link Mining</subject>
<subject>[INFO.INFO-MO] Computer Science [cs]/Modeling and Simulation</subject>
<type>info:eu-repo/semantics/conferenceObject</type>
<type>Conference papers</type>
<description lang=en>The increasing development of world trade has promoted the spread of diseases. Recent events, like the H1N1 outbreak and spread, have confirmed this tendency. Everyone could observe that this kind of infectious disease often has the ability to cross countries borders and spread rapidly. Preventing, monitoring and controlling the outbreak of these diseases have appeared to be a public health problem of primary importance for years. However, although numerous works have been conducted in order to understand and study epidemics, this subject remains a topical issue because of the complexity of the phenomena. In this paper, we present new opportunities offered by the field of social networks for understanding the spread of infectious diseases. This work focuses both on techniques already used in epidemiology, and very recent works in social network analysis that open new perspectives. We give an overview of methods currently used to model and study the spread of diseases and future directions that the social network approach allows to glimpse.</description>
<date>2011</date>
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