Agent-based Simulation of Pedestrian Dynamics for Exposure Time Estimation in Epidemic Risk Assessment

Abstract

With the Corona Virus Disease 2019 (COVID-19) pandemic spreading across the world, protective measures for containing the virus are essential, especially as long as no vaccine or effective treatment is available. One important measure is the so-called physical distancing or social distancing. In this paper, we propose an agent-based numerical simulation of pedestrian dynamics in order to assess behaviour of pedestrians in public places in the context of contact-transmission of infectious diseases like COVID-19, and to gather insights about exposure times and the overall effectiveness of distancing measures. To abide the minimum distance of 1.5 m stipulated by the German government at an infection rate of 2%, our simulation results suggest that a density of one person per 16 m 2 or below is sufficient. The results of this study give insight about how physical distancing as a protective measure can be carried out more efficiently to help reduce the spread of COVID-19.

Model-based assessment of the risks of viral transmission in non-confined crowds

“…Otherwise, such an inversion (along with high risk estimates) is only found for our worstcase transmission models, in particular the model that we introduced to mimic the effect of a contagious patient sneezing every few minutes without covering his or her sneezes. These observations may therefore call for revisions of the widespread risk assessment method whereby a pedestrian is considered exposed to the disease as soon as he stands within a certain radius around an index patient (24,(27)(28)(29). On the other hand, allowing infections within groups, as we did for the cafés, does not dramatically change the picture, even though it substantially heightens the risks associated with sparse situations, for instance, the riverbank walkway.…”

“…However, the translation of these results into epidemiologically relevant predictions is uneasy, and trailing. Poles part from these microscopic studies, risk assessments at the scale of a facility or venue by means of agent-based pedestrian simulations (24,27,28) or large-scale experiments (29) resort to particularly crude assumptions with regard to viral transmission. Generally, an individual is considered exposed to the disease when he or she comes in a given radius (e.g., 2 meters) around an infected person, regardless of their orientations, overlooking that their head orientations control the direction in which respiratory droplets are expelled.…”

“…For the time being, there remains a gap between the thriving experimental and computational studies focused on measuring the emission and propagation of respiratory droplets (2,(14)(15)(16)(17)(18)(19)(20)(21) and the investigations of disease spread at larger scales (22)(23)(24). The former have shed light on the complex, turbulent…”

Social distancing in pedestrian dynamics and its effect on disease spreading

“…Here we consider all the agents to be of the same mass m, so without loss of generality, we set m = 1. Upon reaching their destination, agents are assigned with new random destinations as practiced in [13] to display a continuous motion of the agents resembling the movement in a closed environment, e.g., a mall, office, etc. Agents are also not allowed to exceed the speed limit v max = 2.…”

“…While this model has been widely implemented and studied, only recently it has been used to model transmission processes. For example [12] and [13] study the level of exposure of individuals to the infection, while [14][15][16] develop population level equations and [17][18][19] introduce agent based models to study the spreading in pedestrian dynamics.…”