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Keywords:

  • Conditional intensity function;
  • Infectious disease surveillance data;
  • Spatiotemporal point process;
  • Stochastic epidemic modeling

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.