一种考虑感染诊断不确定性的里德-弗罗斯特模型。
A Reed-Frost model taking into account uncertainties in the diagnostic of the infection.
作者信息
De Menezes Renée X, Ortega Neli R S, Massad Eduardo
机构信息
Department of Medical Statistics, Leiden University Medical Centre, Postbus 9604, 2300 RC Leiden, The Netherlands.
出版信息
Bull Math Biol. 2004 Jul;66(4):689-706. doi: 10.1016/j.bulm.2003.10.003.
In this paper, we model the epidemic course of a pathogen infection within a semi-closed group which generates clinical signals which do not necessarily permit its ready and certain identification. Typical examples of such a pathogen are influenza-type viruses. We allow for time-varying infectivity levels among individuals, and model the probability of infection per contact as a function of the clinical signals. In order to accomplish this, we introduce a modified chain-binomial Reed-Frost model. We obtain an expression for the basic reproduction ratio and determine conditions which guarantee that the epidemic does not survive in the long-term. These conditions being functions of the signal's distribution, they can be used to design and evaluate interventions, such as treatment protocols.
在本文中，我们对病原体在半封闭群体中的感染过程进行建模，该群体产生的临床信号不一定能使其被轻易且确定地识别。此类病原体的典型例子是流感病毒。我们考虑个体间随时间变化的感染性水平，并将每次接触的感染概率建模为临床信号的函数。为实现这一点，我们引入了一种改进的链二项式里德 - 弗罗斯特模型。我们得到了基本再生数的表达式，并确定了保证疫情不会长期持续的条件。这些条件是信号分布的函数，可用于设计和评估干预措施，如治疗方案。
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