Fractional modelling of COVID-19 transmission incorporating asymptomatic and super-spreader individuals.

Publication date: Feb 01, 2025

The COVID-19 pandemic has presented unprecedented challenges worldwide, necessitating effective modelling approaches to understand and control its transmission dynamics. In this study, we propose a novel approach that integrates asymptomatic and super-spreader individuals in a single compartmental model. We highlight the advantages of utilizing incommensurate fractional order derivatives in ordinary differential equations, including increased flexibility in capturing disease dynamics and refined memory effects in the transmission process. We conduct a qualitative analysis of our proposed model, which involves determining the basic reproduction number and analysing the disease-free equilibrium’s stability. By fitting the proposed model with real data from Portugal and comparing it with existing models, we demonstrate that the incorporation of supplementary population classes and fractional derivatives significantly improves the model’s goodness of fit. Sensitivity analysis further provides valuable insights for designing effective strategies to mitigate the spread of the virus.

Concepts Keywords
Advantages Asymptomatic individuals
Biosci Asymptomatic Infections
Covid Basic Reproduction Number
Math COVID-19
Virus COVID-19
Epidemiological Models
Humans
Mathematical Concepts
Mathematical modelling
Models, Biological
Pandemics
Portugal
SARS-CoV-2
Super-spreaders

Semantics

Type Source Name
disease MESH COVID-19
disease IDO process
pathway REACTOME Reproduction
disease MESH Asymptomatic Infections

Original Article

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