Parameters’ estimation, sensitivity analysis and model uncertainty for an influenza a mathematical model: Case of Morocco

Bidah Sara, Zakary Omar, Tridane Abdessamad, Rachik Mostafa, Ferjouchia Hanane

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)

Abstract

In this paper, we consider a SEIS model type compartmental model to explore the evolution of the Influenza epidemic in Morocco. To consider a more realistic model we consider the seasonality of parameters, by considering time-dependent infection rate, time-dependent recovery rate, and time-dependent intervention rate. The next-generation matrix method is used to compute the threshold of equilibria’s stability R0. Based on real data of Influenza epidemic A infections in Morocco from the month of December 2018 to the month of March 2019 published by the Influenza Laboratory Surveillance Information system, we estimate the model parameters. In order to identify the most influential parameter in the proposed model, we carry out the local sensitivity analysis. We calculate sensitivity indices based on the estimated parameters which identify the most influential parameters. We perform also the uncertainty analysis to determine the relationship between the different parameters of the model.

Original languageEnglish
Article number57
Pages (from-to)1-22
Number of pages22
JournalCommunications in Mathematical Biology and Neuroscience
Volume2020
DOIs
Publication statusPublished - 2020

Keywords

  • Estimation of parameters
  • Influenza A
  • Mathematical model
  • Model uncertainty
  • Pandemic
  • Sensitivity analysis

ASJC Scopus subject areas

  • General Neuroscience
  • General Biochemistry,Genetics and Molecular Biology
  • Applied Mathematics

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