Statistical estimation of parameters in a disease transmission model:: analysis of a Cryptosporidium outbreak
Statistical estimation of parameters in a disease transmission model:: analysis of a Cryptosporidium outbreak
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DOI：
10.1002/sim.1258
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发表时间：
2002-12-15
影响因子：
2
通讯作者：
Eisenberg, JNS
中科院分区：
文献类型：
--
作者：
Brookhart, MA;Hubbard, AE;Eisenberg, JNS
人口动态模型是研究流行病和其他复杂人口过程的常用工具，是隐式非线性数学方程。由于与可能是未识别的高维参数和难以最大化的复杂似然函数相关联的问题，基于这种模型的推断可能是困难的。为了解决1993年密尔沃基隐孢子虫爆发的数学模型中的参数估计的共线性的不可识别性的问题，我们研究了约束配置文件似然方法的效用。该方法用于研究来自数学模型的两个感兴趣的参数：（i）二次传输的速率;（ii）由于水处理故障导致的一次传输的成比例增加。这些参数的估计值强烈依赖于隐孢子虫流行病学的知之甚少的方面，如无症状的比例和人口免疫状态。我们的分析表明，疾病传播模型和约束轮廓似然过程的组合提供了一个有效的方法来推断和估计的重要参数调节传染病爆发。版权所有（C）2002约翰威利父子有限公司
Population dynamic models, commonly used tools in the study of epidemics and other complex population processes, are implicit non-linear mathematical equations. Inference based on such models can be difficult due to the problems associated with high dimensional parameters that may be non-identified and complex likelihood functions that are difficult to maximize. To address a problem of non-identifiability due to collinearity of parameter estimates in a mathematical model of the 1993 Milwaukee Cryptosporidium parvum outbreak, we examined the utility of a constrained profile likelihood approach. This method was used to study two parameters of interest from the mathematical model: (i) the rate of secondary transmission; (ii) the proportional increase in primary transmission due to water treatment failure. The estimated values of these parameters were shown to depend strongly on poorly understood aspects of Cryptosporidium epidemiology such as asymptomatic proportion and the population immune status. Our analysis demonstrated that the combination of a disease transmission model and a constrained profile likelihood procedure provides an effective approach for inference and estimation of important parameters regulating infectious disease outbreaks. Copyright (C) 2002 John Wiley Sons, Ltd.