Modeling and Simulation of Susceptible - Exposed – Infected – Recovered – Vaccinated - Susceptible Model of Influenza

Abstract

Influenza, surpassing all other respiratory diseases in both morbidity and mortality, annually triggers seasonal epidemics responsible for approximately 500,000 global deaths. Mathematical epidemic models serve as valuable tools for forecasting potential outbreaks and predicting the trajectory of the disease. This paper represents a comprehensive SEIRVS model tailored to the context of Influenza transmission dynamics in North Macedonia. In this paper the classical Susceptible- Exposed- Infectious- Recovered (SEIR) model is enhanced by incorporating vaccination and a death compartment while examining their impact on the spread of Influenza through the population. Simulations are conducted using data from the 2022/2023 season, focusing on a case study of North Macedonia. The simulations were conducted utilizing both the actual vaccination rate in N. Macedonia for that season and an increased vaccination rate to observe the influence of vaccination. The simulation results emphasize the need to increase the vaccination rate. The findings contribute valuable insights for public health planning and policy making.