COVID-19 indoor exposure levels: An analysis of foot traffic scenarios within an academic building

Abstract

Minimizing all aspects of COVID-19 exposure is a high priority as universities prepare to reopen. One of those aspects includes developing protocols for interior spaces such as academic buildings. This paper applies mathematical modeling to investigate different virus exposure levels due to traffic patterns within academic buildings. The assumption used are: 1) Risk of infection is a product of exposure rate and time and 2) the exposure rate decreases with distance. One-way vs. two-way pedestrian traffic scenarios within hallways were modeled and analyzed for various configurations. The underlying assumption that a small exposure to a large number of people is similar to a large exposure to a few people is the driver to minimize exposures levels in all aspects. The analysis indicates that minimizing the time spent in passing between classes is the driving factor in minimizing risk, and one-way traffic may increase the time required to pass between classes. While the case presented is limited, the modeled approaches are intended to provoke future research that can be extended and applied to larger populations to help provide decision makers with more rigorous tools to shape future policies regarding traffic flow within buildings.