Abstract
This study introduces a SIR (Susceptible-Infectious-Recovered) model using fractional derivatives to assess the population's hesitancy to the COVID-19 vaccination campaign in Portugal. Leveraging the framework developed by Angstmann [1], our approach incorporates fractional derivatives to best describe the nuanced dynamics of the vaccination process. We begin by examining the qualitative properties of the proposed model. To substantiate the inclusion of fractional derivatives, empirical data along with statistical criteria are applied. Numerical simulations are performed to compare both integer and fractional order models. An epidemiological interpretation for the fractional order of the model is provided, in the context of a vaccination campaign.
| Original language | English |
|---|---|
| Pages (from-to) | 608-620 |
| Number of pages | 13 |
| Journal | Applied Numerical Mathematics |
| Volume | 207 |
| DOIs | |
| Publication status | Published - Jan 2025 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- COVID-19
- Fractional derivatives
- SIR model
- Vaccine hesitancy
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