title: Incorporating social contact data in spatio-temporal models for infectious disease spread.
abstract: Routine public health surveillance of notifiable infectious diseases gives rise to weekly counts of reported cases-possibly stratified by region and/or age group. We investigate how an age-structured social contact matrix can be incorporated into a spatio-temporal endemic-epidemic model for infectious disease counts. To illustrate the approach, we analyze the spread of norovirus gastroenteritis over six age groups within the 12 districts of Berlin, 2011-2015, using contact data from the POLYMOD study. The proposed age-structured model outperforms alternative scenarios with homogeneous or no mixing between age groups. An extended contact model suggests a power transformation of the survey-based contact matrix toward more within-group transmission.
authors.affiliation: Institute of Medical Informatics, Biometry, and Epidemiology, Friedrich-Alexander-Universität Erlangen-Nürnberg,Waldstraße 6, DE-91054 Erlangen, Germanyseb.meyer@fau.de.
authors.forename: Sebastian
authors.initials: S
authors.lastname: Meyer
authors.affiliation: Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Hirschengraben 84, CH-8001 Zürich, Switzerland.
authors.forename: Leonhard
authors.initials: L
authors.lastname: Held
mesh_terms: D001604:Berlin / Q000453:epidemiology; D003141:Communicable Diseases / Q000635:transmission*; D058872:Epidemics / Q000706:statistics & numerical data*; D062665:Epidemiological Monitoring; D005759:Gastroenteritis / Q000453:epidemiology; D006801:Humans; D015233:Models, Statistical
keywords: Age-structured contact matrix; Areal count time series; Endemic-epidemic modeling; Infectious disease epidemiology; Norovirus gastroenteritis; Norwalk virus; Spatio-temporal surveillance data