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As of December 2020, the COVID-19 pandemic has infected over 75 millionpeople, making it the deadliest pandemic in modern history. This study developsa novel compartmental epidemiological model specific to the SARS-CoV-2 virusand analyzes the effect of common preventative measures such as testing,quarantine, social distancing, and vaccination. By accounting for the mostprevalent interventions that have been enacted to minimize the spread of thevirus, the model establishes a paramount foundation for future mathematicalmodeling of COVID-19 and other modern pandemics. Specifically, the modelexpands on the classic SIR model and introduces separate compartments forindividuals who are in the incubation period, asymptomatic, tested-positive,quarantined, vaccinated, or deceased. It also accounts for variable infection,testing, and death rates. I first analyze the outbreak in Santa Clara County,California, and later generalize the findings. The results show that, althoughall preventative measures reduce the spread of COVID-19, quarantine and socialdistancing mandates reduce the infection rate and subsequently are the mosteffective policies, followed by vaccine distribution and, finally, publictesting. Thus, governments should concentrate resources on enforcing quarantineand social distancing policies. In addition, I find mathematical proof that therelatively high asymptomatic rate and long incubation period are drivingfactors of COVID-19's rapid spread.

A Novel Compartmental Approach to Modeling COVID-19 Disease Dynamics and Analyzing the Effect of Common Preventative Measures