title: A space-time conditional intensity model for invasive meningococcal disease occurrence.
abstract: A novel point process model continuous in space-time is proposed for quantifying the transmission dynamics of the two most common meningococcal antigenic sequence types observed in Germany 2002-2008. Modeling is based on the conditional intensity function (CIF), which is described by a superposition of additive and multiplicative components. As an epidemiological interesting finding, spread behavior was shown to depend on type in addition to age: basic reproduction numbers were 0.25 (95% CI 0.19-0.34) and 0.11 (95% CI 0.07-0.17) for types B:P1.7-2,4:F1-5 and C:P1.5,2:F3-3, respectively. Altogether, the proposed methodology represents a comprehensive and universal regression framework for the modeling, simulation, and inference of self-exciting spatiotemporal point processes based on the CIF. Usability of the modeling in biometric practice is promoted by an implementation in the R package surveillance.
authors: Department of Psychiatry and Psychotherapy, Ludwig-Maximilians-Universität, 80336 München, Germany. Sebastian.Meyer@med.uni-muenchen.de
authors: Sebastian
authors: S
authors: Meyer
authors: Johannes
authors: J
authors: Elias
authors: Michael
authors: M
authors: Höhle
mesh_terms: D000465:Algorithms; D000942:Antigens, Bacterial / Q000235:genetics; D001699:Biometry / Q000379:methods*; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D058872:Epidemics / Q000706:statistics & numerical data; D005858:Germany / Q000453:epidemiology; D006801:Humans; D015994:Incidence; D008589:Meningococcal Infections / Q000453:epidemiology* / Q000382:microbiology / Q000635:transmission; D015233:Models, Statistical; D009345:Neisseria meningitidis / Q000145:classification / Q000235:genetics / Q000276:immunology; D013269:Stochastic Processes
chemical_list: D000942:Antigens, Bacterial