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A Space–Time Conditional Intensity Model for Invasive Meningococcal Disease Occurrence

Authors

  • Sebastian Meyer,

    Corresponding author
    1. Department of Psychiatry and Psychotherapy, Ludwig-Maximilians-Universität, 80336 München, Germany
    2. Department of Statistics, Ludwig-Maximilians-Universität, 80539 München, Germany
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  • Johannes Elias,

    1. German Reference Centre for Meningococci, University of Würzburg, 97080 Würzburg, Germany
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  • Michael Höhle

    Corresponding author
    1. Department of Statistics, Ludwig-Maximilians-Universität, 80539 München, Germany
    2. Department for Infectious Disease Epidemiology, Robert Koch Institute, 13086 Berlin, Germany
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email:Sebastian.Meyer@med.uni-muenchen.de

email: HoehleM@rki.de

Abstract

Summary 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.

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