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Strategy for Locating People to Reduce the Transmission of COVID-19 Using Different Interference Measures

Author

Listed:
  • Brenda Valenzuela-Fonseca

    (School of Industrial Engineering, Universidad del Bío-Bío, Concepción 4030000, Chile)

  • Rodrigo Linfati

    (Department of Industrial Engineering, Universidad del Bío-Bío, Concepción 4030000, Chile)

  • John Willmer Escobar

    (Department of Accounting and Finance, Universidad del Valle, Cali 760001, Colombia)

Abstract

COVID-19 is generally transmitted from person to person through small droplets of saliva emitted when talking, sneezing, coughing, or breathing. For this reason, social distancing and ventilation have been widely emphasized to control the pandemic. The spread of the virus has brought with it many challenges in locating people under distance constraints. The effects of wakes between turbines have been studied extensively in the literature on wind energy, and there are well-established interference models. Does this apply to the propagation functions of the virus? In this work, a parallel relationship between the two problems is proposed. A mixed-integer linear programming (MIP) model and a mixed-integer quadratic programming model (MIQP) are formulated to locate people to avoid the spread of COVID-19. Both models were constructed according to the distance constraints proposed by the World Health Organization and the interference functions representing the effects of wake between turbines. Extensive computational tests show that people should not be less than two meters apart, in agreement with the adapted Wells–Riley model, which indicates that 1.6 to 3.0 m (5.2 to 9.8 ft) is the safe social distance when considering the aerosol transmission of large droplets exhaled when speaking, while the distance can be up to 8.2 m (26 ft) if all the droplets in a calm air environment are taken into account.

Suggested Citation

  • Brenda Valenzuela-Fonseca & Rodrigo Linfati & John Willmer Escobar, 2022. "Strategy for Locating People to Reduce the Transmission of COVID-19 Using Different Interference Measures," Sustainability, MDPI, vol. 14(1), pages 1-19, January.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:1:p:529-:d:717497
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    References listed on IDEAS

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    1. Ndaïrou, Faïçal & Area, Iván & Nieto, Juan J. & Torres, Delfim F.M., 2020. "Mathematical modeling of COVID-19 transmission dynamics with a case study of Wuhan," Chaos, Solitons & Fractals, Elsevier, vol. 135(C).
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    Cited by:

    1. Chung-Kwan Lo & Xiaowei Huang & Ka-Luen Cheung, 2022. "Toward a Design Framework for Mathematical Modeling Activities: An Analysis of Official Exemplars in Hong Kong Mathematics Education," Sustainability, MDPI, vol. 14(15), pages 1-17, August.

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