Smart Distance Lab: A new methodology for assessing social distancing interventions

In the wake of the COVID-19 pandemic, the central importance of human behaviour in mitigating the spread of the virus has become universally recognized. We present a methodology to systematically assess the effectiveness of behavioural interventions to stimulate social distancing. In addition, we demonstrate the feasibility of this framework in a large-scale natural experiment. In an experimental design, we varied behavioural interventions to evaluate the effect of face masks, walking directions, and immediate feedback on visitors’ contacts. We represent visitors as nodes, and their contacts as links in a contact network. Subsequently, we used network modelling to test for differences in these contact networks. We find no evidence that face masks influence social distancing, while unidirectional walking directions and buzzer feedback do positively impact social distancing. The presented methodology represents a practically feasible way to optimize social distancing interventions through scientific research and may directly inform policy.