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

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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DOI:
10.1016/j.tpb.2010.04.003
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发表时间:
2010-08
影响因子:
1.4
通讯作者:
Smith, Gary
Smith, Gary
中科院分区:
生物学4区
文献类型:
--
作者:
Rorres, Chris;Pelletier, Sky T. K.;Keeling, Matt J.;Smith, Gary

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对动物流行病数学模型中存在的参数类型提出了三种不同的估计器。估算者使用流行病期间收集的数据,这些数据可能有限、不完整或正在持续收集。当持续收集数据时,估计的参数可用于评估假定的控制策略。使用基于包含两个参数的空间、离散时间、重力型随机数学模型的模拟流行病对这些估计进行了测试。用该模型模拟了目标流行病,并使用收集数据的不同组合实现了三个估计器,以独立确定两个参数。
Three different estimators are presented for the types of parameters present in mathematical models of animal epidemics. The estimators make use of 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.
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