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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 |
|---|---|
| Form of publication: | Preprint |
| Keywords: | Conditional intensity function, Invasive meningococcal disease, Spatio-temporal point process, Stochastic epidemic modelling |
| Faculties: | Mathematics, Computer Science and Statistics > Statistics > Technical Reports |
| Subjects: | 500 Science > 570 Life sciences; biology |
| URN: | urn:nbn:de:bvb:19-epub-11898-1 |
| Annotation: | Article first published online: 9 OCT 2011 |
| Language: | English |
| Item ID: | 11898 |
| Date Deposited: | 22. Nov 2010, 16:46 |
| Last Modified: | 04. Nov 2020, 12:52 |
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