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

  • University of Hassan II Casablanca

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

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
StatePublished - 2020

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

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

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