Department of Epidemiology, University of Michigan, Ann Arbor, MI 48109, USA.
J R Soc Interface. 2011 Apr 6;8(57):506-17. doi: 10.1098/rsif.2010.0491. Epub 2010 Nov 10.
The most commonly used dose-response models implicitly assume that accumulation of dose is a time-independent process where each pathogen has a fixed risk of initiating infection. Immune particle neutralization of pathogens, however, may create strong time dependence; i.e. temporally clustered pathogens have a better chance of overwhelming the immune particles than pathogen exposures that occur at lower levels for longer periods of time. In environmental transmission systems, we expect different routes of transmission to elicit different dose-timing patterns and thus potentially different realizations of risk. We present a dose-response model that captures time dependence in a manner that incorporates the dynamics of initial immune response. We then demonstrate the parameter estimation of our model in a dose-response survival analysis using empirical time-series data of inhalational anthrax in monkeys in which we find slight dose-timing effects. Future dose-response experiments should include varying the time pattern of exposure in addition to varying the total doses delivered. Ultimately, the dynamic dose-response paradigm presented here will improve modelling of environmental transmission systems where different systems have different time patterns of exposure.
最常用的剂量反应模型隐含地假设剂量的积累是一个与时间无关的过程,其中每个病原体都有固定的感染风险。然而,免疫粒子对病原体的中和作用可能会产生强烈的时间依赖性;也就是说,时间上聚集的病原体比长时间低水平暴露的病原体更有可能克服免疫粒子。在环境传播系统中,我们预计不同的传播途径会引起不同的剂量-时间模式,从而可能会产生不同的风险实现。我们提出了一种剂量反应模型,以一种包含初始免疫反应动态的方式来捕捉时间依赖性。然后,我们使用猴子吸入性炭疽的经验时间序列数据在剂量反应生存分析中演示了我们模型的参数估计,我们发现了轻微的剂量-时间效应。未来的剂量反应实验除了改变总剂量外,还应包括改变暴露的时间模式。最终,这里提出的动态剂量反应范式将改进不同系统具有不同暴露时间模式的环境传播系统的建模。