COVID-19 has disproportionately decimated demand for commercial aviation and hospitality industries. Falling to their lowest levels in decades, air carriers’ route networks, fleet sizes, workforces, and seat-miles collectively and massively regressed in 2020. Much like the aviation industry evolved to emergent security threats in the wake of the 9/11 terror attacks, airlines and airports must now adapt to ever-present public health concerns. Research on the quantitative and qualitative factors contributing to aviation disease transmission, as well as air travel volume predictions over the foreseeable future, is of paramount interest to governments, citizens, airlines, and airports worldwide. Utilizing public databases and building upon prior research methods, this study aims to determine the strength and directionality of correlation between air traffic and coronavirus prevalence. The relationship between passenger throughput and coronavirus cases in the U.S. from March 2020 to March 2021 is numerically modeled, yielding insight into traveler health risk sensitivities, travel ban and quarantine policies, and the eventual recovery of the aviation industry. Statistical analysis is performed with stationarity testing, causality testing and an Auto-Regressive Integrated Moving Average (ARIMA) algorithm.  This study seeks to evaluate disease spread against air travel volumes so that aviation industry may prepare to counteract financial disasters and once again reach new heights.