A DISCRETE-TIME MODEL FOR THE STATISTICAL-ANALYSIS OF INFECTIOUS-DISEASE INCIDENCE DATA
A DISCRETE-TIME MODEL FOR THE STATISTICAL-ANALYSIS OF INFECTIOUS-DISEASE INCIDENCE DATA
复制标题
DOI：
10.2307/2532743
复制
发表时间：
1992-03-01
期刊：
影响因子：
1.9
通讯作者：
MONTO, AS
中科院分区：
文献类型：
--
作者：
RAMPEY, AH;LONGINI, IM;MONTO, AS
设计了一个离散时间模型，用于在抽样的家庭中按时间单位分布传染病病例。利用个人被识别的时间(例如，当疾病症状出现时)作为感染的标志，估计各种风险因素水平的从社区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极大似然方法。可根据易感程度和传染性程度对个人进行分类。该模型符合密歇根州特库姆塞鼻病毒流行的症状和病毒培养数据的组合。一般来说，人们观察到，感染风险的降低与年龄的增加有关。
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.