ABSTRACT
SARS-CoV-2 is a contagious respiratory virus that has been discovered in sewage, human waste, and wastewater treatment facilities. Wastewater surveillance has been considered one of the lowest-cost means of testing for tracking the COVID-19 outbreak in communities. This paper highlights the dynamics of the virus's infection, persistence, and occurrence in wastewater treatment plants. Our aim is to develop and implement a mathematical model to infer the epidemic dynamics from the possible density of SARS-CoV-2 viral load in wastewater. We present a long-normal model and fractional order of susceptible-exposed-infected-recovery (SEIR) epidemic model for predicting the spread of the COVID-19 disease from the wastewater data. We study the dynamic properties of the fractional order SEIR model with respect to the fractional ordered values. The model is used to comprehend how the coronavirus spreads through wastewater treatment plants in Saudi Arabia. Our modeling approach can help with wastewater surveillance for early prediction and cost-effective monitoring of the epidemic outbreak in a situation of low testing capacity.