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Modeling, analysis and prediction of new variants of covid-19 and dengue co-infection on complex network

  • Baba Ghulam Shah Badshah University
  • International College of Engineering
  • International Center for Basic and Applied Sciences

Research output: Contribution to journalArticlepeer-review

84 Scopus citations

Abstract

Recently, four new strains of SARS-COV-2 were reported in different countries which are mutants and considered as 70% more dangerous than the existing covid-19 virus. In this paper, hybrid mathematical models of new strains and co-infection in Caputo, Caputo-Fabrizio, and Atangana-Baleanu are presented. The idea behind this co-infection modeling is that, as per medical reports, both dengue and covid-19 have similar symptoms at the early stages. Our aim is to evaluate and predict the transmission dynamics of both deadly viruses. The qualitative study via stability analysis is discussed at equilibria and reproduction number R0 is computed. For the numerical purpose, Adams-Bashforth-Moulton and Newton methods are employed to obtain the approximate solutions of the proposed model. Sensitivity analysis is carried out to assessed the effects of various biological parameters and rates of transmission on the dynamics of both viruses. We also compared our results with some reported data against infected, recovered, and death cases.

Original languageEnglish
Article number111008
JournalChaos, Solitons and Fractals
Volume150
DOIs
StatePublished - Sep 2021

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

  • Covid-19
  • Dengue
  • Optimization
  • Predictor-corrector scheme
  • Stability analysis

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