A space-time conditional intensity model for infectious disease occurence

Meyer, Sebastian; Elias, Johannes and Höhle, Michael (2010): A space-time conditional intensity model for infectious disease occurence. Department of Statistics: Technical Reports, No.95

Abstract

A novel point process model continuous in space-time is proposed for infectious disease data. Modelling is based on the conditional intensity function (CIF) and extends an additive-multiplicative CIF model previously proposed for discrete space epidemic modelling. Estimation is performed by means of full maximum likelihood and a simulation algorithm is presented. The particular application of interest is the stochastic modelling of the transmission dynamics of the two most common meningococcal antigenic sequence types observed in Germany 2002–2008. 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. Application is promoted by an implementation in the R package RLadyBug.

• Item Type: Paper (Technical Report)
• Keywords: Conditional intensity function, Invasive meningococcal disease, Spatio-temporal point process, Stochastic epidemic modelling
• Subjects: Mathematics, Computer Science and Statistics > Statistics > Technical Reports
• Dewey Classification: 300 Social sciences > 310 General statistics; 600 Natural sciences and mathematics > 510 Mathematics; 600 Natural sciences and mathematics > 570 Life sciences