Modeling Epidemiologic Typing Data and Likelihood Inference for Disease Spread
该研究提出了一个流行病学分型数据模型，并开发了似然比方法来评估这些数据作为疾病传播证据的强度，适用于传染病流行病学研究者判断分型证据的可靠性。
Abstract A model for epidemiologic typing data is introduced, and likelihood ratio methods are developed for evaluating these data as evidence about disease spread. The observed data consist of microorganism subtypes from an index case of infectious disease, cases clustered with the index case, and a reference sample. The likelihood methods are evaluated via probabilities of observing epidemiologic subtypes that represent strong and sometimes misleading evidence favoring one hypothesis over another. A general bound is identified for the probability of observing strong evidence favoring a close epidemiologic relationship between the index and cluster cases vis-à-vis no relationship when in fact there is none. The advantages of this approach versus alternate approaches to measuring the strength of typing evidence are discussed.