Behavioral effects of anti-pandemic preventive measures: a VR study

During the COVID-19 pandemic, a variety of public health measures aimed at decreasing transmission between people sharing public spaces, including social distancing and the use of face masks. However the behavioral consequences of these policies on human navigation are mostly unknown. Using virtual reality, we investigated how some common preventive measures influenced how people navigate near other people. Participants (N=29) traversed virtual rooms containing virtual people(“agents”) while we manipulated their mask status, the mask status of the agents, and the perceived environmental safety (high/low community vaccination rates). We found that initial path selection was primarily determined by agent mask-wearing, with participants more likely to pass in front of masked than unmasked agents. The perception of environmental safety predominantly governed subsequent interpersonal distance, with closer proximity maintained in high-vaccination contexts. The participants’ own mask status was the least influential, suggesting that navigational choices were driven by external risk assessment rather than personal protection. We observed clear risk compensation: subjects generally reduced interpersonal distance in safer conditions (whether environmental, agent masking, or personal masking). Bayesian model comparisons favored a three-factor additive model, indicating independent rather than interactive influences on behavior. These findings reveal the interplay of decisions underlying pandemic-era social navigation, and highlight the importance of accounting for risk compensation in public health interventions.