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The coronavirus disease 2019 (COVID-19) pandemic has created unprecedented healthcare emergencies across the globe. The World Health Organization (WHO) has proposed social distancing (SD) as a prudent measure to contain the pandemic and, hence, governments have been enacting lockdowns of varied nature. These lockdowns, causing economic and social strain, warrant the development of quantitative models to optimally manage the pandemic. Similarly, extensive testing aids in early detection and isolation, hence containing the spread of the pandemic. Compartment epidemiology models have been used extensively in modeling such infectious diseases. This paper attempts to utilize the modified Susceptible-Exposed-Infectious-Recovered (SEIR) model incorporating the SD, testing, and infectiousness of exposed and infectious compartments to study the COVID-19 pandemic in Saudi Arabia. Saudi Arabia has put restrictions on the movement of people in different phases to ascertain SD. Time-dependent parameters based on the timeline of restrictions and testing in Saudi Arabia have been introduced to capture SD and testing. The arrived model has been validated through statistical tests. The   \begin{document}R_{0}\end{document}   (R naught), basic reproduction number, value has ranged between 0.6014 and 2.7860 with an average of 1.4904 and currently holds at 0.8952. In the absence of SD and testing measures, the model predicts the threshold herd immunity to be 69.31% and   \begin{document}R_{0}\end{document}   value as 3.26. Further, scenario analysis has been conducted for alleviating the SD measure. The results show that early lifting of all restrictions may undo all efforts in the containment of the COVID-19 pandemic. The outcome of results will help policymakers and medical practitioners prepare better to manage the pandemic and lockdown.

COVID-19 Modeling in Saudi Arabia Using the Modified Susceptible-Exposed-Infectious-Recovered (SEIR) Model