Human salmonellosis: Estimation of dose-illness from outbreak data
Human salmonellosis: Estimation of dose-illness from outbreak data
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DOI：
10.1111/j.1539-6924.2008.01038.x
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发表时间：
2008-04-01
期刊：
影响因子：
3.8
通讯作者：
Mintiens, Koen
中科院分区：
文献类型：
--
作者：
Bollaerts, Kaatje;Aerts, Marc;Mintiens, Koen
对摄入的微生物数量与感染、疾病或死亡率等特定结果之间的关系进行量化是定量风险评估的一个关键方面。确定这种剂量-反应模型的一个主要问题是是否有适当的数据。人类喂养试验一直受到批评，因为只有年轻健康的志愿者被选中参加，低剂量，因为经常发生在真实的生活中，通常不被考虑。流行病学爆发数据被认为更有价值，但更容易受到数据不确定性的影响。在这篇文章中，我们根据世界卫生组织讨论的20次沙门氏菌爆发的数据建立了剂量-疾病关系模型。特别是，我们使用广义线性混合模型和剂量的分数多项式模型的剂量-疾病的关系。对分数多项式模型进行了修改，以满足Teunis等人提出的不同类型的剂量-疾病模型的特性。在这些模型中，将宿主易感性（易感人群与正常人群）的差异建模为固定效应，而将血清型和食物基质的差异建模为随机效应。此外，两个引导程序。第一个过程占随机变化，而第二个过程占随机变化和数据的不确定性。分析表明，当病原体-食物基质组合毒性极强时，易感人群在低剂量水平下患病的可能性较高，而当组合毒性较低时，在高剂量水平下患病的可能性较高。此外，分析表明，免疫力存在于正常人群中，但不存在于易感人群中。
The quantification of the relationship between the amount of microbial organisms ingested and a specific outcome such as infection, illness, or mortality is a key aspect of quantitative risk assessment. A main problem in determining such dose-response models is the availability of appropriate data. Human feeding trials have been criticized because only young healthy volunteers are selected to participate and low doses, as often occurring in real life, are typically not considered. Epidemiological outbreak data are considered to be more valuable, but are more subject to data uncertainty. In this article, we model the dose-illness relationship based on data of 20 Salmonella outbreaks, as discussed by the World Health Organization. In particular, we model the dose-illness relationship using generalized linear mixed models and fractional polynomials of dose. The fractional polynomial models are modified to satisfy the properties of different types of dose-illness models as proposed by Teunis et al. Within these models, differences in host susceptibility (susceptible versus normal population) are modeled as fixed effects whereas differences in serovar type and food matrix are modeled as random effects. In addition, two bootstrap procedures are presented. A first procedure accounts for stochastic variability whereas a second procedure accounts for both stochastic variability and data uncertainty. The analyses indicate that the susceptible population has a higher probability of illness at low dose levels when the combination pathogen-food matrix is extremely virulent and at high dose levels when the combination is less virulent. Furthermore, the analyses suggest that immunity exists in the normal population but not in the susceptible population.