Applied Research Associates, Inc., Arlington Division, Arlington, VA, USA.
Coleman Scientific Consulting, Groton, NY, USA.
Risk Anal. 2018 Aug;38(8):1685-1700. doi: 10.1111/risa.12995. Epub 2018 Apr 25.
Military health risk assessors, medical planners, operational planners, and defense system developers require knowledge of human responses to doses of biothreat agents to support force health protection and chemical, biological, radiological, nuclear (CBRN) defense missions. This article reviews extensive data from 118 human volunteers administered aerosols of the bacterial agent Francisella tularensis, strain Schu S4, which causes tularemia. The data set includes incidence of early-phase febrile illness following administration of well-characterized inhaled doses of F. tularensis. Supplemental data on human body temperature profiles over time available from de-identified case reports is also presented. A unified, logically consistent model of early-phase febrile illness is described as a lognormal dose-response function for febrile illness linked with a stochastic time profile of fever. Three parameters are estimated from the human data to describe the time profile: incubation period or onset time for fever; rise time of fever; and near-maximum body temperature. Inhaled dose-dependence and variability are characterized for each of the three parameters. These parameters enable a stochastic model for the response of an exposed population through incorporation of individual-by-individual variability by drawing random samples from the statistical distributions of these three parameters for each individual. This model provides risk assessors and medical decisionmakers reliable representations of the predicted health impacts of early-phase febrile illness for as long as one week after aerosol exposures of human populations to F. tularensis.
军事健康风险评估人员、医疗规划人员、作战规划人员和防御系统开发人员需要了解人类对生物威胁剂剂量的反应,以支持部队健康保护和化学、生物、放射性、核(CBRN)防御任务。本文综述了 118 名人类志愿者吸入弗朗西斯氏菌属细菌剂福氏志贺氏菌菌株 Schu S4 气溶胶的广泛数据,该菌可引起兔热病。数据集包括在吸入剂量特征良好的福氏志贺氏菌后早期发热性疾病的发生率。还提供了从去识别病例报告中获得的随时间变化的人体温度曲线的补充数据。将描述一种早期发热性疾病的统一、逻辑一致的模型,作为与发热随机时间曲线相关的发热性疾病的对数正态剂量反应函数。从人体数据中估计了三个参数来描述时间曲线:发热的潜伏期或发病时间;发热的上升时间;和最高体温。对每个参数都进行了吸入剂量依赖性和变异性的描述。这些参数通过从每个个体的这三个参数的统计分布中抽取随机样本,为暴露人群的反应建立了一个随机模型,从而纳入了个体间的变异性。该模型为风险评估人员和医疗决策者提供了在人类暴露于福氏志贺氏菌后的长达一周内,对早期发热性疾病的预测健康影响的可靠表示。