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An Advanced Study of Urban Emergency Medical Equipment Logistics Distribution for Different Levels of Urgency Demand

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  • Yongqiang Zhao

    (School of Modern Post, Xi’an University of Posts & Telecommunications, Xi’an 710061, China)

  • Liwei Zhang

    (School of Modern Post, Xi’an University of Posts & Telecommunications, Xi’an 710061, China)

Abstract

At the early stage of a major public health emergency outbreak, there exists an imbalance between supply and demand in the distribution of emergency supplies. To improve the efficiency of emergency medical service equipment and relieve the treatment pressure of each medical treatment point, one of the most important factors is the emergency medical equipment logistics distribution. Based on the actual data of medical equipment demand during the epidemic and the characteristics of emergencies, this study proposed an evaluation index system for emergency medical equipment demand point urgency, based on the number of patients, the number of available inpatient beds, and other influencing factors as the index. An urban emergency medical equipment distribution model considering the urgency of demand, the distribution time window, and vehicle load was constructed with the constraints. Wuhan, Hubei Province, China, at the beginning of the outbreak was selected as a validation example, and the Criteria Importance Though Intercriteria Correlation (CRITIC) method and the genetic algorithm were used to simulate and validate the model with and without considering the demand urgency. The results show that under the public health emergencies, the distribution path designed to respond to different levels of urgency demand for medical equipment is the most efficient path and reduces the total distribution cost by 5%.

Suggested Citation

  • Yongqiang Zhao & Liwei Zhang, 2022. "An Advanced Study of Urban Emergency Medical Equipment Logistics Distribution for Different Levels of Urgency Demand," IJERPH, MDPI, vol. 19(18), pages 1-16, September.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:18:p:11264-:d:909265
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    References listed on IDEAS

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    1. Zhu, Bangren & Zheng, Xinqi & Liu, Haiyan & Li, Jiayang & Wang, Peipei, 2020. "Analysis of spatiotemporal characteristics of big data on social media sentiment with COVID-19 epidemic topics," Chaos, Solitons & Fractals, Elsevier, vol. 140(C).
    2. Liu, Jia & Bai, Jinyu & Wu, Desheng, 2021. "Medical supplies scheduling in major public health emergencies," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 154(C).
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