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

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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.

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Notes

  1. www.salud.gov.pr/Estadisticas-Registros-y-Publicaciones/EstadisticasInfluenza/InformeInfluenzaSemana26-2017.pdf (2017).

  2. www.salud.gov.pr/Estadisticas-Registros-y-Publicaciones/EstadisticasInfluenza/InformeInfluenzaSemana39-2015.pdf (2015).

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Correspondence to Pierre Magal.

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This article is dedicated to the memory of Karl Hadeler.

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Magal, P., Webb, G. The parameter identification problem for SIR epidemic models: identifying unreported cases. J. Math. Biol. 77, 1629–1648 (2018). https://doi.org/10.1007/s00285-017-1203-9

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  • DOI: https://doi.org/10.1007/s00285-017-1203-9

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