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Updated: Sep 20, 2025

Author Spotlight: Advancements in Multiplex Detection of Respiratory Viruses
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A memory effect model to predict COVID-19: analysis and simulation.

Aatif Ali1, Abdelouahed Alla Hamou2, Saeed Islam1

  • 1Department of Mathematics, Abdul Wali Khan University Mardan, Khyber Pakhtunkhwa, Pakistan.

Computer Methods in Biomechanics and Biomedical Engineering
|June 9, 2022
PubMed
Summary

Testing asymptomatic individuals exposed to COVID-19 is crucial. Mathematical modeling shows reducing social contact rates and increasing isolation of infected individuals can help eliminate the pandemic.

Keywords:
COVID-19Caputoasymptomatic testingfractional estimationnon-pharmaceutical interventionssimulationstability

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Area of Science:

  • Epidemiology
  • Mathematical Biology
  • Infectious Disease Modeling

Background:

  • Centers for Disease Control and Prevention (CDC) recommended testing asymptomatic close contacts.
  • Asymptomatic transmission is a significant driver of COVID-19 spread.
  • Understanding population-level impacts of interventions is vital.

Purpose of the Study:

  • To develop a mathematical model for evaluating COVID-19 population-level impact.
  • To assess the effects of contact rates (social distancing) and isolation rates.
  • To analyze transmission dynamics using fractional calculus.

Main Methods:

  • A deterministic system of nonlinear differential equations was proposed.
  • Least squares curve fitting used COVID-19 data from Pakistan (Oct 2020 - Apr 2021).
  • Fractional derivatives (Caputo) and the fractional-order Adams-Bashforth method were employed.

Main Results:

  • The model was fitted and parameterized using real-world pandemic data.
  • Fractional calculus captured biological processes with memory effects.
  • Analysis derived the reproduction number and stability conditions.

Conclusions:

  • Non-pharmaceutical interventions (NPIs) like social distancing and isolation are effective.
  • Reducing contact rates and increasing isolation can lead to pandemic elimination.
  • The study highlights the importance of targeted testing and isolation strategies.