Abstract
We performed large-scale numerical simulations using a composite model to investigate the infection spread in a supermarket during a pandemic. The model is composed of the social force, purchasing strategy and infection transmission models. Specifically, we quantified the infection risk for customers while in a supermarket that depended on the number of customers, the purchase strategies and the physical layout of the supermarket. The ratio of new infections compared to sales efficiency (earned profit for customer purchases) was computed as a factor of customer density and social distance. Our results indicate that the social distance between customers is the primary factor influencing infection rate. Supermarket layout and purchasing strategy do not impact social distance and hence the spread of infection. Moreover, we found only a weak dependence of sales efficiency and customer density. We believe that our study will help to establish scientifically-based safety rules that will reduce the social price of supermarket business.
Highlights
Coronavirus 2019 disease (COVID-19), which is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first reported in humans in late 2019 and the World Health Organization declared it a pandemic in March 2020
The coronavirus spreads by contact and through airborne respiratory droplets and a complete lockdown, which enforces isolation and social distancing, is the most effective means to slow the spread
The time spent in a supermarket comprises a time spent in shopping room and a time spent at the cash desk, including a queue. For fixed parameters, such as the geometry and area of the shopping room, number of cashiers and time spent at the cash desk, the average time T0 is some function of the density ρ and desired social distance r0
Summary
Coronavirus 2019 disease (COVID-19), which is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first reported in humans in late 2019 and the World Health Organization declared it a pandemic in March 2020. 4m 0.1 s 4h velocity relaxation time, Eq (3) module of the desired velocity, Eq (3) maximal actual velocity factor for vdes in the entrance zones (“E”) factor for vdes in a queue (“:”) factor for vdes in slow motion zones (“.”) velocity recovery factor, Eq (7) inter-person repulsion force amplitude, Eqs (4) and (5) inter-person relaxation distance, Eqs (4) and (5) magnitude of the chirality force, Eq (6) chirality force cutoff distance, Eq (6) mean number of purchases in the purchase list standard deviation for number of purchases forward prediction time (see Rules for the change of vdes) probability to turn left/right, approaching wall or obstacle probability to change the direction in a crossroad zone downtime factor for a customer patience, Eq (8) the threshold level of a customer patience coefficient for isotropic term, Eq (9)
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