Fractional modelling of COVID-19 transmission incorporating asymptomatic and super-spreader individuals
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arXiv
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| Hauptverfasser: | , , , , |
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| Format: | Preprint |
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2025
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| author | Khalighi, Moein Lahti, Leo Ndaïrou, Faïçal Rashkov, Peter Torres, Delfim F. M. |
| author_facet | Khalighi, Moein Lahti, Leo Ndaïrou, Faïçal Rashkov, Peter Torres, Delfim F. M. |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2501_03428 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Fractional modelling of COVID-19 transmission incorporating asymptomatic and super-spreader individuals Khalighi, Moein Lahti, Leo Ndaïrou, Faïçal Rashkov, Peter Torres, Delfim F. M. Populations and Evolution Dynamical Systems Physics and Society 92D30, 34C60, 34A08, 26A33 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. |
| title | Fractional modelling of COVID-19 transmission incorporating asymptomatic and super-spreader individuals |
| topic | Populations and Evolution Dynamical Systems Physics and Society 92D30, 34C60, 34A08, 26A33 |
| url | https://arxiv.org/abs/2501.03428 |