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. 2018 Dec;77(6-7):1629-1648.
doi: 10.1007/s00285-017-1203-9. Epub 2018 Jan 13.

The parameter identification problem for SIR epidemic models: identifying unreported cases

Pierre Magal  1   2 , Glenn Webb  3
Affiliations

The parameter identification problem for SIR epidemic models: identifying unreported cases

Pierre Magal et al. J Math Biol. 2018 Dec.

Abstract

A SIR epidemic model is analyzed with respect to identification of its parameters, based upon reported case data from public health sources. The objective of the analysis is to understand the relation of unreported cases to reported cases. In many epidemic diseases the ratio of unreported to reported cases is very high, and of major importance in implementing measures for controlling the epidemic. This ratio can be estimated by the identification of parameters for the model from reported case data. The analysis is applied to three examples: (1) the Hong Kong seasonal influenza epidemic in New York City in 1968-1969, (2) the bubonic plague epidemic in Bombay, India in 1906, and (3) the seasonal influenza epidemic in Puerto Rico in 2016-2017.

Keywords: Epidemic models; Reported cases; Transmission rate; Unreported cases.

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