Schmidt Philip J
Risk Anal. 2015 Jul;35(7):1364-83. doi: 10.1111/risa.12323. Epub 2014 Dec 17.
Two forms of single-hit infection dose-response models have previously been developed to assess available data from human feeding trials and estimate the norovirus dose-response relationship. The mechanistic interpretations of these models include strong assumptions that warrant reconsideration: the first study includes an implicit assumption that there is no immunity to Norwalk virus among the specific study population, while the recent second study includes assumptions that such immunity could exist and that the nonimmune have no defensive barriers to prevent infection from exposure to just one virus. Both models addressed unmeasured virus aggregation in administered doses. In this work, the available data are reanalyzed using a generalization of the first model to explore these previous assumptions. It was hypothesized that concurrent estimation of an unmeasured degree of virus aggregation and important dose-response parameters could lead to structural nonidentifiability of the model (i.e., that a diverse range of alternative mechanistic interpretations yield the same optimal fit), and this is demonstrated using the profile likelihood approach and by algebraic proof. It is also demonstrated that omission of an immunity parameter can artificially inflate the estimated degree of aggregation and falsely suggest high susceptibility among the nonimmune. The currently available data support the assumption of immunity within the specific study population, but provide only weak information about the degree of aggregation and susceptibility among the nonimmune. The probability of infection at low and moderate doses may be much lower than previously asserted, but more data from strategically designed dose-response experiments are needed to provide adequate information.
此前已开发出两种单剂量感染剂量反应模型,用于评估人体喂养试验中的现有数据,并估计诺如病毒的剂量反应关系。这些模型的机理解释包含一些值得重新审视的强烈假设:第一项研究隐含假设特定研究人群对诺沃克病毒没有免疫力,而最近的第二项研究则假设这种免疫力可能存在,并且非免疫人群没有防御屏障来防止仅接触一种病毒就被感染。两个模型都考虑了给药剂量中未测量的病毒聚集情况。在这项工作中,我们使用第一个模型的推广形式重新分析了现有数据,以探究这些先前的假设。据推测,对未测量的病毒聚集程度和重要剂量反应参数进行同时估计可能会导致模型的结构不可识别性(即,多种不同的替代机理解释会产生相同的最优拟合),这通过轮廓似然法和代数证明得到了验证。还证明了省略免疫参数会人为夸大估计的聚集程度,并错误地表明非免疫人群易感性高。目前可得的数据支持特定研究人群中存在免疫力的假设,但仅提供了关于非免疫人群中聚集程度和易感性的微弱信息。低剂量和中等剂量下的感染概率可能远低于先前断言的,但需要更多来自精心设计的剂量反应实验的数据来提供充分信息。