title: A spatial epidemic model for disease spread over a heterogeneous spatial support.
abstract: Data from the Iowa mumps epidemic of 2006 were collected on a spatial lattice over a regular temporal interval. Without access to a person-to-person contact graph, it is sensible to analyze these data as homogenous within each areal unit and to use the spatial graph to derive a contact structure. The spatio-temporal partition is fine, and the counts of new infections at each location at each time are sparse. Therefore, we propose a spatial compartmental epidemic model with general latent time distributions (spatial PS SEIR) that is capable of smoothing the contact structure, while accounting for spatial heterogeneity in the mixing process between locations. Because the model is an extension of the PS SEIR model, it simultaneously handles non-exponentially distributed latent and infectious time distributions. The analysis within focuses on the progression of the disease over both space and time while assessing the impact of a large proportion of the infected people dispersing at the same time because of spring break and the impact of public awareness on the spread of the mumps epidemic. We found that the effect of spring break increased the mixing rate in the population and that the spatial transmission of the disease spreads across multiple conduits.
authors.affiliation: Department of Applied Mathematics and Statistics, Colorado School of Mines, 1500 Illinois St., Golden, CO 80401, U.S.A.
authors.forename: Aaron T
authors.initials: AT
authors.lastname: Porter
authors.affiliation: Department of Biostatistics, The University of Iowa, 145 N. Riverside Dr., Iowa City, 52242, IA, U.S.A.
authors.forename: Jacob J
authors.initials: JJ
authors.lastname: Oleson
mesh_terms: D001499:Bayes Theorem; D003141:Communicable Diseases / Q000635:transmission*; D058872:Epidemics / Q000706:statistics & numerical data; D062305:Geographic Mapping; D006801:Humans; D007484:Iowa / Q000453:epidemiology; D008962:Models, Theoretical; D009107:Mumps / Q000453:epidemiology
keywords: Bayesian; SEIR; conditional autoregressive; mumps; rank reduction