On Fuzzy and Crisp Solutions of a Novel Fractional Pandemic Model

Kalpana Umapathy, Balaganesan Palanivelu, Víctor Leiva, Prasantha Bharathi Dhandapani, Cecilia Castro

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


Understanding disease dynamics is crucial for accurately predicting and effectively managing epidemic outbreaks. Mathematical modeling serves as an essential tool in such understanding. This study introduces an advanced susceptible, infected, recovered, and dead (SIRD) model that uniquely considers the evolution of the death parameter, alongside the susceptibility and infection states. This model accommodates the varying environmental factors influencing disease susceptibility. Moreover, our SIRD model introduces fractional changes in death cases, which adds a novel dimension to the traditional counts of susceptible and infected individuals. Given the model’s complexity, we employ the Laplace-Adomian decomposition method. The method allows us to explore various scenarios, including non-fuzzy non-fractional, non-fuzzy fractional, and fuzzy fractional cases. Our methodology enables us to determine the model’s equilibrium positions, compute the basic reproduction number, confirm stability, and provide computational simulations. Our study offers insightful understanding into the dynamics of pandemic diseases and underscores the critical role that mathematical modeling plays in devising effective public health strategies. The ultimate goal is to improve disease management through precise predictions of disease behavior and spread.

Original languageEnglish
Article number528
JournalFractal and Fractional
Issue number7
StatePublished - Jul 2023


  • Laplace-Adomian
  • decomposition
  • epidemic models
  • fractional changes
  • stability


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