A space-time conditional intensity model for invasive meningococcal disease occurrence

TL;DR

This paper introduces a new space-time point process model for understanding the transmission dynamics of invasive meningococcal disease, accounting for type and age, with practical implementation in R.

Contribution

It presents a novel continuous space-time conditional intensity model for meningococcal disease, incorporating type-specific spread behavior and providing a comprehensive regression framework.

Findings

Type-specific basic reproduction numbers were estimated.

The model captures spread behavior dependent on type and age.

Implementation available in R package surveillance.

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. Modelling 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 behaviour 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 modelling, simulation and inference of self-exciting spatio-temporal point processes based on the CIF. Usability of the modelling in biometric practice is promoted by an implementation in the R package surveillance.