Modeling and Real-Time Prediction of Classical Swine Fever Epidemics

R. Meester; J. de Koning; M.C.M. de Jong; O. Diekmann

doi:10.1111/j.0006-341X.2002.00178.x

Modeling and Real-Time Prediction of Classical Swine Fever Epidemics

R. Meester, J. de Koning, M.C.M. de Jong, O. Diekmann

Research output: Contribution to journal › Article › Academic › peer-review

21 Citations (Scopus)

Abstract

We propose a new method to analyze outbreak data of an infectious disease such as classical swine fever. The underlying model is a two-type branching process. It is used to deduce information concerning the epidemic from detected cases. In particular, the method leads to prediction of the future course of the epidemic and hence can be used as a basis for control policy decisions. We test the model with data from the large 1997-1998 classical swine fever epidemic in The Netherlands. It turns out that our results are in good agreement with the data.

Original language	English
Pages (from-to)	178-184
Journal	Biometrics
Volume	58
Issue number	1
DOIs	https://doi.org/10.1111/j.0006-341X.2002.00178.x
Publication status	Published - 2002

Keywords

Branching process
Classical swine fever
EM algorithm
Maximum likelihood
Modeling of epidemics
Prediction of epidemics

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1111/j.0006-341X.2002.00178.x

Cite this

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KW - EM algorithm

KW - Maximum likelihood

KW - Modeling of epidemics

KW - Prediction of epidemics

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Modeling and Real-Time Prediction of Classical Swine Fever Epidemics

Abstract

Keywords

UN SDGs

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