title: Dynamic social networks and the implications for the spread of infectious disease.
abstract: Understanding the nature of human contact patterns is crucial for predicting the impact of future pandemics and devising effective control measures. However, few studies provide a quantitative description of the aspects of social interactions that are most relevant to disease transmission. Here, we present the results from a detailed diary-based survey of casual (conversational) and close contact (physical) encounters made by a small peer group of 49 adults who recorded 8,661 encounters with 3,528 different individuals over 14 non-consecutive days. We find that the stability of interactions depends on the intimacy of contact and social context. Casual contact encounters mostly occur in the workplace and are predominantly irregular, while close contact encounters mostly occur at home or in social situations and tend to be more stable. Simulated epidemics of casual contact transmission involve a large number of non-repeated encounters, and the social network is well captured by a random mixing model. However, the stability of the social network should be taken into account for close contact infections. Our findings have implications for the modelling of human epidemics and planning pandemic control policies based on social distancing methods.
authors.affiliation: Mathematics Institute and Department of Biological Sciences, University of Warwick, Coventry CV4 7AL, UK. jonathan.read@liverpool.ac.uk
authors.forename: Jonathan M
authors.initials: JM
authors.lastname: Read
authors.forename: Ken T D
authors.initials: KT
authors.lastname: Eames
authors.forename: W John
authors.initials: WJ
authors.lastname: Edmunds
mesh_terms: D000328:Adult; D003141:Communicable Diseases / Q000635:transmission*; D016358:Contact Tracing; D004196:Disease Outbreaks / Q000517:prevention & control*; D018562:Disease Transmission, Infectious; D006801:Humans; D008954:Models, Biological; D012944:Social Support