twinSIR: Individual-level epidemic modeling for a fixed population with known distances

The availability of geocoded health data and the inherent temporal structure of communicable diseases have led to an increased interest in statistical models and software for spatio-temporal data with epidemic features. The R package surveillance can handle various levels of aggregation at which infective events have been recorded. This vignette illustrates the analysis of individual-level surveillance data for a fixed population, of which the complete SIR event history is assumed to be known. Typical applications for the multivariate, temporal point process model “twinSIR” of Höhle (2009) include the spread of infectious livestock diseases across farms, household models for childhood diseases, and epidemics across networks. We first describe the general modeling approach and then exemplify data handling, model fitting, and visualization for a particularly well-documented measles outbreak among children of the isolated German village Hagelloch in 1861.