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On the Effectiveness of the Measures in Supermarkets for Reducing Contact among Customers during COVID-19 Period

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  • Qiancheng Xu

    (Institute for Advanced Simulation, Forschungszentrum Jülich, 52425 Jülich, Germany)

  • Mohcine Chraibi

    (Institute for Advanced Simulation, Forschungszentrum Jülich, 52425 Jülich, Germany)

Abstract

The spread of the COVID-19 virus had a huge impact on human life on the global scale. Many control measures devoted to decrease contact among people have been adopted to slow down the transmission of the disease. A series of measures have been taken in supermarkets, which include restricting the number of customers, keeping social distance, and entering with a shopping cart. In this work, we investigate with numerical simulations the effectiveness of these measures in reducing the contact among customers. Several scenarios with different control measures are designed for numerical analysis. The movements of customers in a supermarket are simulated by a microscopic model for pedestrian dynamics. Moreover, an index based on the distance between customers is defined to measure the degree of contact and therefore evaluate it quantitatively. The effect of these measures on the average contact degree of each customer is explored, and the spatial distribution of the contact among customers in the supermarket is shown in a qualitative way. Simulation results show that except shopping cart measure, the other two measures are effective in reducing contact among customers.

Suggested Citation

  • Qiancheng Xu & Mohcine Chraibi, 2020. "On the Effectiveness of the Measures in Supermarkets for Reducing Contact among Customers during COVID-19 Period," Sustainability, MDPI, vol. 12(22), pages 1-14, November.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:22:p:9385-:d:443418
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    References listed on IDEAS

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    1. David Berger & Kyle Herkenhoff & Chengdai Huang & Simon Mongey, 2022. "Testing and Reopening in an SEIR Model," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 43, pages 1-21, January.
    2. Xu, Qiancheng & Chraibi, Mohcine & Tordeux, Antoine & Zhang, Jun, 2019. "Generalized collision-free velocity model for pedestrian dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    3. David Berger & Kyle Herkenhoff & Chengdai Huang & Simon Mongey, 2022. "Testing and Reopening in an SEIR Model," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 43, pages 1-21, January.
    4. Bosina, Ernst & Weidmann, Ulrich, 2017. "Estimating pedestrian speed using aggregated literature data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 468(C), pages 1-29.
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    Cited by:

    1. Małgorzata Dudzińska & Marta Gwiaździńska-Goraj & Aleksandra Jezierska-Thöle, 2022. "Social Factors as Major Determinants of Rural Development Variation for Predicting Epidemic Vulnerability: A Lesson for the Future," IJERPH, MDPI, vol. 19(21), pages 1-24, October.
    2. Tomasz Antczak & Bartosz Skorupa & Mikolaj Szurlej & Rafal Weron & Jacek Zabawa, 2021. "Simulation modeling of epidemic risk in supermarkets: Investigating the impact of social distancing and checkout zone design," WORking papers in Management Science (WORMS) WORMS/21/05, Department of Operations Research and Business Intelligence, Wroclaw University of Science and Technology.
    3. Cui, Hongjun & Xie, Jinping & Zhu, Minqing & Tian, Xiaoyong & Wan, Ce, 2022. "Virus transmission risk of college students in railway station during Post-COVID-19 era: Combining the social force model and the virus transmission model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 608(P1).

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