Arbeitspapier
A statistical framework for the analysis of multivariate infectious disease surveillance data
A framework for the statistical analysis of counts from infectious disease surveillance database is proposed. In its simplest form, the model can be seen as a Poisson branching process model with immigration. Extensions to include seasonal effects, time trends and overdispersion are outlined. The model is shown to provide an adequate fit and reliable one-step-ahead prediction intervals for a typical infectious disease surveillance time series. Furthermore, a multivariate formulation is proposed, which is well suited to capture space-time interactions caused by the spatial spread of a disease over time. analyses of uni- and multivariate times series on several infectious diseases are described. All analyses have been done using general optimization routines where ML estimates and corresponding standard errors are readily available.
- Sprache
-
Englisch
- Erschienen in
-
Series: Discussion Paper ; No. 402
- Thema
-
Branching Process with Immigration
Infectious Disease Surveillance
Maximum Likelihood
Multivariate Time Series of Counts
Observation-driven
Parameter-driven
Space-Time-Models
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Held, Leonhard
Höhle, Michael
Hofmann, Mathias
- Ereignis
-
Veröffentlichung
- (wer)
-
Ludwig-Maximilians-Universität München, Sonderforschungsbereich 386 - Statistische Analyse diskreter Strukturen
- (wo)
-
München
- (wann)
-
2004
- DOI
-
doi:10.5282/ubm/epub.1772
- Handle
- URN
-
urn:nbn:de:bvb:19-epub-1772-2
- Letzte Aktualisierung
-
10.03.2025, 11:42 MEZ
Datenpartner
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Held, Leonhard
- Höhle, Michael
- Hofmann, Mathias
- Ludwig-Maximilians-Universität München, Sonderforschungsbereich 386 - Statistische Analyse diskreter Strukturen
Entstanden
- 2004
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