Fractional Dynamics on Transmission of Oropouche Fever

Abstract

This study presents an enhanced fractional-order SEIR (Susceptible-Exposed- Infected-Recovered) model to analyse the transmission dynamics of Oropouche fever (Sloth Fever) an emerging arboviral disease. By incorporating memory effects through fractional calculus, the model better captures real-world disease progression. Traditional and enhanced fractional SEIR models are implemented using python with real epidemiological data. A comparative analysis highlights the fractional order and its advantage in modeling long-term persistence. Addi- tionally, a stability framework evaluates intervention strategies. Finally, the results indicate the enhanced fractional SEIR model offers superior predic- tive accuracy and flexibility, making it valuable for public health planning and outbreak mitigation.