title: The dynamic nature of contact networks in infectious disease epidemiology.
abstract: Although contact network models have yielded important insights into infectious disease transmission and control throughout the last decade, researchers have just begun to explore the dynamic nature of contact patterns and their epidemiological significance. Most network models have assumed that contacts are static through time. Developing more realistic models of the social interactions that underlie the spread of infectious diseases thus remains an important challenge for both data gatherers and modelers. In this article, we review some recent data-driven and process-driven approaches that capture the dynamics of human contact, and discuss future challenges for the field.
authors.affiliation: Center for Infectious Disease Dynamics, The Pennsylvania State University, University Park, PA, USA. shweta@sbansal.com
authors.forename: Shweta
authors.initials: S
authors.lastname: Bansal
authors.forename: Jonathan
authors.initials: J
authors.lastname: Read
authors.forename: Babak
authors.initials: B
authors.lastname: Pourbohloul
authors.forename: Lauren Ancel
authors.initials: LA
authors.lastname: Meyers
mesh_terms: D003141:Communicable Diseases / Q000453:epidemiology*; D006801:Humans; D007398:Interpersonal Relations; D008954:Models, Biological; D013223:Statistics as Topic