  At the time of this article, COVID-19 has been transmitted to more than 42
million people and resulted in more than 673,000 deaths across the United
States. Throughout this pandemic, public health authorities have monitored the
results of diagnostic testing to identify hotspots of transmission. Such
information can help reduce or block transmission paths of COVID-19 and help
infected patients receive early treatment. However, most current schemes of
test site allocation have been based on experience or convenience, often
resulting in low efficiency and non-optimal allocation. In addition, the
historical sociodemographic patterns of populations within cities can result in
measurable inequities in access to testing between various racial and income
groups. To address these pressing issues, we propose a novel test site
allocation scheme to (a) maximize population coverage, (b) minimize prediction
uncertainties associated with projections of outbreak trajectories, and (c)
reduce inequities in access. We illustrate our approach with case studies
comparing our allocation scheme with recorded allocation of testing sites in
Georgia, revealing increases in both population coverage and improvements in
equity of access over current practice.
