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首页> 外文期刊>Journal of applied statistics >Inference for serological surveys investigating past exposures to infections resulting in long-lasting immunity - an approach using finite mixture models with concomitant information
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Inference for serological surveys investigating past exposures to infections resulting in long-lasting immunity - an approach using finite mixture models with concomitant information

机译：血清学调查的推论，以调查过去的感染导致长期的免疫力-一种使用有限混合模型和相应信息的方法

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摘要

This paper is concerned with developing a latent class mixture modelling technique which efficiently exploits data from serological surveys aiming to investigate past exposures to infections resulting in long-term or life-lasting immunity. Mixture components featured by antibody assays' distribution are associated with the serological groups in the population, whilst the probability mixture that an individual belongs to the positive serological group is regarded as an age-dependent prevalence. The latter embeds a mechanistic model which explains the infection process, accounting for heterogeneities, contact patterns in the population and incorporating elements of study design. A Bayesian framework for statistical inference using Markov chain Monte Carlo estimation methods naturally accommodates missing responses in the data and allows straightforward assessement of uncertainties in nonlinear models. The applicability of the method is illustrated by investigating past exposure to varicella zoster virus infection in pre-school children, using data from a large scale UK cohort study which included a cross-sectional serological survey based on oral fluid samples.
机译：本文涉及开发一种潜在类别的混合物建模技术，该技术可有效利用血清学调查中的数据，旨在调查过去暴露于感染的长期或持久免疫能力。抗体测定分布特征的混合物成分与人群中的血清学组相关，而个体属于阳性血清学组的概率混合物被视为年龄依赖性患病率。后者嵌入了一个机械模型，该模型解释了感染过程，解释了异质性，人群中的接触方式以及纳入了研究设计的要素。使用马尔可夫链蒙特卡洛估计方法的贝叶斯统计推断框架自然可以容纳数据中缺失的响应，并可以直接评估非线性模型中的不确定性。通过使用大规模英国队列研究的数据（包括基于口腔液样本的横断面血清学调查），调查学龄前儿童过去对水痘带状疱疹病毒感染的暴露情况，说明了该方法的适用性。

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