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.
Dokumententyp: | Paper |
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Publikationsform: | Preprint |
Keywords: | Conditional intensity function, Invasive meningococcal disease, Spatio-temporal point process, Stochastic epidemic modelling |
Fakultät: | Mathematik, Informatik und Statistik > Statistik > Technische Reports |
Themengebiete: | 500 Naturwissenschaften und Mathematik > 570 Biowissenschaften; Biologie |
URN: | urn:nbn:de:bvb:19-epub-11898-1 |
Bemerkung: | Article first published online: 9 OCT 2011 |
Sprache: | Englisch |
Dokumenten ID: | 11898 |
Datum der Veröffentlichung auf Open Access LMU: | 22. Nov. 2010, 16:46 |
Letzte Änderungen: | 04. Nov. 2020, 12:52 |