COVID-19 and Minimizing Micro-Spatial Interactions

Abstract

COVID-19, the novel coronavirus that has disrupted lives around the world, continues to challenge how humans interact in public and shared environments. Repopulating the micro-spatial setting of an office building, with virus spread and transmission mitigation measures, is critical for a return to normalcy. Advice from public health experts, such as maintaining physical distancing from others and well-ventilated spaces, are essential, yet there is a lack of sound guidance on configuring office usage that allows for a safe return of workers. This paper highlights the potential for decision-making and planning insights through location analytics, particularly within an office setting. Proposed is a spatial analytic framework addressing the need for physical distancing and limiting worker interaction, supported by geographic information systems, network science, and spatial optimization. The developed modeling approach addresses dispersion of assigned office spaces as well as associated movement within the office environment. This can be used to support the design and utilization of offices in a manner that minimizes the risk of COVID-19 transmission. Our proposed model produces two main findings: (1) that the consideration of minimizing potential interaction as an objective has implications for the safety of work environments, and (2) that current social distancing measures may be inadequate within office settings. Our results show that leveraging exploratory spatial data analyses through the integration of geographic information systems, network science, and spatial optimization, enables the identification of workspace allocation alternatives in support of office repopulation efforts.