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Estimating the kernel parameters of premises-based stochastic models of farmed animal infectious disease epidemics using limited, incomplete, or ongoing data

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Rorres, Chris, Pelletier, Sky T. K., Keeling, Matthew James and Smith, Gary (2010) Estimating the kernel parameters of premises-based stochastic models of farmed animal infectious disease epidemics using limited, incomplete, or ongoing data. Theoretical Population Biology, Vol.78 (No.1). pp. 46-53. doi:10.1016/j.tpb.2010.04.003

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Official URL: http://dx.doi.org/10.1016/j.tpb.2010.04.003

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Abstract

Three different estimators are presented for the types of parameters present in mathematical models of animal epidemics. The estimators make use of the data collected during an epidemic, which may be limited, incomplete, or under collection on an ongoing basis. When data are being collected on an ongoing basis, the estimated parameters can be used to evaluate putative control strategies. These estimators were tested using simulated epidemics based on a spatial, discrete-time, gravity-type, stochastic mathematical model containing two parameters. Target epidemics were simulated with the model and the three estimators were implemented using various combinations of collected data to independently determine the two parameters. (C) 2010 Elsevier Inc. All rights reserved.

Item Type: Journal Article
Subjects: Q Science > QH Natural history > QH301 Biology
Q Science > QH Natural history > QH426 Genetics
Divisions: Faculty of Science > Mathematics
Journal or Publication Title: Theoretical Population Biology
Publisher: Academic Press
ISSN: 0040-5809
Official Date: August 2010
Dates:
DateEvent
August 2010Published
Volume: Vol.78
Number: No.1
Number of Pages: 8
Page Range: pp. 46-53
DOI: 10.1016/j.tpb.2010.04.003
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Restricted or Subscription Access
Funder: National Institute of General Medical Sciences
Grant number: 5U01GM-076426

Data sourced from Thomson Reuters' Web of Knowledge

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