Rampey A H, Longini I M, Haber M, Monto A S
Lilly Research Laboratories, Division of Eli Lilly and Company, Indianapolis, Indiana 46285.
Biometrics. 1992 Mar;48(1):117-28.
A discrete-time model is devised for the per-time-unit distribution of infectious disease cases in a sample of households. Using the time at which an individual is identified (e.g., when illness symptoms appear) as a marker for being infected, the probabilities of becoming infected from the community or from a single infectious household member are estimated for various risk factor levels. Maximum likelihood procedures for estimating the model parameters are given. An individual may be classified with regard to level of susceptibility and level of infectiousness. The model is fitted to a combination of symptom and viral culture data from a rhinovirus epidemic in Tecumseh, Michigan. In general, it is observed that decreasing risk of infection is associated with increasing age.
设计了一个离散时间模型，用于研究家庭样本中传染病病例的单位时间分布。以个体被识别的时间（例如，出现疾病症状时）作为感染的标志，针对不同风险因素水平，估计从社区感染或从单个感染家庭成员感染的概率。给出了估计模型参数的最大似然法。个体可根据易感性水平和传染性水平进行分类。该模型与密歇根州蒂康塞鼻病毒流行期间的症状和病毒培养数据相结合进行拟合。一般来说，可以观察到感染风险的降低与年龄的增加有关。
