IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v19y2022i18p11264-d909265.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/19/18/11264/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/19/18/11264/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hainan Huang & Weifan Chen & Tian Xie & Yaoyao Wei & Ziqing Feng & Weijiong Wu, 2021. "The Impact of Individual Behaviors and Governmental Guidance Measures on Pandemic-Triggered Public Sentiment Based on System Dynamics and Cross-Validation," IJERPH, MDPI, vol. 18(8), pages 1-25, April.
    2. Fang Xu & Mengfan Yan & Lun Wang & Shaojian Qu, 2022. "The Robust Emergency Medical Facilities Location-Allocation Models under Uncertain Environment: A Hybrid Approach," Sustainability, MDPI, vol. 15(1), pages 1-23, December.
    3. Iustina Alina Boitan & Emilia Mioara Campeanu & Sanja Sever Malis, 2021. "Economic Sentiment Perceptions During COVID-19 Pandemic – A European Cross-Country Impact Assessment," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 23(Special15), pages 982-982, November.
    4. Zijing Ye & Ruisi Li & Jing Wu, 2022. "Dynamic Demand Evaluation of COVID-19 Medical Facilities in Wuhan Based on Public Sentiment," IJERPH, MDPI, vol. 19(12), pages 1-22, June.
    5. Qiang Wang & Min Su & Min Zhang & Rongrong Li, 2021. "Integrating Digital Technologies and Public Health to Fight Covid-19 Pandemic: Key Technologies, Applications, Challenges and Outlook of Digital Healthcare," IJERPH, MDPI, vol. 18(11), pages 1-50, June.
    6. Lidia Perenc & Justyna Podgórska-Bednarz & Agnieszka Guzik & Mariusz Drużbicki, 2023. "Impact of the COVID-19 Pandemic on the Level of Anxiety and Depression in Caregivers of Children Benefiting from Neurorehabilitation Services," IJERPH, MDPI, vol. 20(5), pages 1-19, March.
    7. 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).
    8. Luanying Li & Lin Hua & Fei Gao, 2022. "What We Ask about When We Ask about Quarantine? Content and Sentiment Analysis on Online Help-Seeking Posts during COVID-19 on a Q&A Platform in China," IJERPH, MDPI, vol. 20(1), pages 1-19, December.
    9. Kundu, Tanmoy & Sheu, Jiuh-Biing & Kuo, Hsin-Tsz, 2022. "Emergency logistics management—Review and propositions for future research," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 164(C).
    10. Ye, Jihong & Jiang, Wei & Yang, Xinxiang & Hong, Bingyuan, 2023. "Emergency materials response framework for petrochemical enterprises based on multi-objective optimization," Energy, Elsevier, vol. 269(C).
    11. Wen-zhong Shi & Fanxin Zeng & Anshu Zhang & Chengzhuo Tong & Xiaoqi Shen & Zhewei Liu & Zhicheng Shi, 2022. "Online public opinion during the first epidemic wave of COVID-19 in China based on Weibo data," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-10, December.
    12. Israel Edem Agbehadji & Bankole Osita Awuzie & Alfred Beati Ngowi, 2021. "COVID-19 Pandemic Waves: 4IR Technology Utilisation in Multi-Sector Economy," Sustainability, MDPI, vol. 13(18), pages 1-20, September.
    13. Adnan Muhammad Shah & Rizwan Ali Naqvi & Ok-Ran Jeong, 2021. "Detecting Topic and Sentiment Trends in Physician Rating Websites: Analysis of Online Reviews Using 3-Wave Datasets," IJERPH, MDPI, vol. 18(9), pages 1-25, April.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:19:y:2022:i:18:p:11264-:d:909265. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.