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识别 SIR 传染病模型中的未报告病例数。

Identifying the number of unreported cases in SIR epidemic models.

机构信息

Normandie University, UNIHAVRE, LMAH, FR-CNRS-3335, ISCN, Le Havre, France.

University of Bordeaux, CNRS, Bordeaux INP, IMB, UMR, Talence, France.

出版信息

Math Med Biol. 2020 May 29;37(2):243-261. doi: 10.1093/imammb/dqz013.

Abstract

An SIR epidemic model is analysed with respect to the identification of its parameters and initial values, based upon reported case data from public health sources. The objective of the analysis is to understand the relationship of unreported cases to reported cases. In many epidemic diseases the reported cases are a small fraction of the unreported cases. This fraction can be estimated by the identification of parameters for the model from reported case data. The analysis is applied to the Hong Kong seasonal influenza epidemic in New York City in 1968-1969.

摘要

基于公共卫生来源的报告病例数据,对 SIR 传染病模型进行了参数和初始值的识别分析。该分析的目的是了解报告病例与未报告病例之间的关系。在许多传染病中,报告病例只是未报告病例的一小部分。通过从报告病例数据中确定模型的参数,可以估计这个比例。该分析应用于 1968-1969 年香港季节性流感在纽约市的流行。

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