Solutions to SIR/SEIR epidemic models with exponential series: Numerical and non numerical approaches.

This study revisits the mathematical SIR/SEIR epidemic models, aiming to introduce novel exponential-type series solutions. Beyond standard non-dimensionalization, we implement a successful rescaling technique that reduces the parameter count in classical epidemiology. Consequently, solutions for the SIR model are determined solely by the basic reproduction number and initial infected fractions. Similarly, the SEIR model requires only the transmission-to-recovery ratio and initial exposed fractions. We present both numerical and non numerical solutions, alongside elucidating the limitations on the existence of exponential-type series solutions. Our analysis reveals that these solutions are valid under two key conditions: endemic situations and early epidemic stages, where the basic reproduction number is close to one. We graphically illustrate the range of physical parameters guaranteeing the existence of non numerical exponential series solutions. However, for epidemic/pandemic outbreaks with significantly higher reproduction numbers, achieving complete convergence of the exponential series across the entire physical domain becomes impossible. In such cases, we divide the exponential series solution into two zones: from initial time to peak time and from peak time to the final epidemic time. For the first zone, where convergence is slow, we successfully employ Padé approximants to accelerate the convergence of the series. This accelerated solution is then smoothly joined to the second zone solution once the peak time is identified within the first region. The presented non numerical solutions are envisioned to serve as valuable benchmarks for testing and enhancing other numerical approaches used to solve epidemic models and their variants.