Modeling the Dynamics of Hepatitis C Transmission Using Fractional Order Approaches and Physics-Informed Neural Networks - Takeaways - MDSpire

Modeling the Dynamics of Hepatitis C Transmission Using Fractional Order Approaches and Physics-Informed Neural Networks

  • By

  • Vetrivel Muthupandi

  • Arul Joseph Gnanaprakasam

  • Salah Boulaaras

  • February 24, 2026

  • 0 min

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  • 1

    Hepatitis C virus (HCV) affects 58 million globally, with significant morbidity and mortality, particularly in low-income countries like Zimbabwe.

  • 2

    Zimbabwe struggles to meet WHO's HCV elimination goals, with only 16% diagnosed and 0.69% receiving treatment among the infected population.

  • 3

    Directly acting antivirals (DAAs) are effective but remain inaccessible due to high costs and limited healthcare resources in Zimbabwe.

  • 4

    Fractional-order dynamics are crucial for modeling HCV transmission, capturing the memory effects of past infections and treatment responses.

  • 5

    The Caputo–Fabrizio derivative is preferred for modeling HCV due to its ability to represent the rapid decay of past influences on disease progression.

Original Source(s)

Modeling the Dynamics of Hepatitis C Transmission Using Fractional Order Approaches and Physics-Informed Neural Networks

  • by Vetrivel Muthupandi, Arul Joseph Gnanaprakasam, Salah Boulaaras

  • February 24, 2026

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