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\begin{document}

\title{Conformable mathematical modeling of the COVID-19 transmission dynamics:
A more general study}



\author[1]{Hayman Thabet}%
\author[2]{Subhash Kendre}%
\affil[1]{Brown University}%
\affil[2]{Savitribai Phule Pune University}%


\vspace{-1em}



  
  \date{May 27, 2024}


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\begin{abstract}
Many challenges are still faced in bridging the gap between Mathematical
modeling and biological sciences. Measuring population immunity to
assess the epidemiology of health and disease is a challenging task and
is currently an active area of research. However, to meet these
challenges, mathematical modeling is an effective technique in shaping
the population dynamics that can help disease control. In this paper, we
introduce a Susceptible-Infected-Recovered (SIR) model and a
Susceptible-Infected-Recovered-Exposed-Deceased (SEIRD) model based on
conformable space-time PDEs for the Coronavirus Disease 2019 (COVID-19)
pandemic. As efficient analytical tools, we present new modifications
based on the fractional exponential rational function method (ERFM) and
an analytical technique based on the Adomian decomposition method for
obtaining the solutions for the proposed models. These analytical
approaches are more efficious for obtaining analytical solutions for
nonlinear systems of partial differential equations (PDEs) with
conformable derivatives. The interesting result of this paper is that it
yields new exact and approximate solutions to the proposed COVID-19
pandemic models with conformable space-time partial derivatives%
\end{abstract}%



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