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用于 COVID-19 应急资源协调和后续响应的智能机制。

An Intelligent Mechanism for COVID-19 Emergency Resource Coordination and Follow-Up Response.

机构信息

School of Management, Shenyang University of Technology, Shenyang 110870, China.

School of Management, Jinan University, Guangzhou 510632, China.

出版信息

Comput Intell Neurosci. 2022 Jun 20;2022:2005188. doi: 10.1155/2022/2005188. eCollection 2022.

DOI:10.1155/2022/2005188
PMID:35747718
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9210128/
Abstract

As a serious emergency in 2020, COVID-19 had a great impact on people's lives. In this paper, short-term and long-term response to emergency supplies needs after the outbreak of COVID-19 in a region is studied. Firstly, a comparative study of different regional resource coordination options in the early stages of COVID-19 is conducted using a multiobjective decision-making approach to arrive at the optimal solution. Then, a system dynamics model is established for the follow-up development of the epidemic, to predict the long-term development trend of the epidemic, and to study the urgency of the needs of different materials in different periods. The results show that time and satisfaction are the two most important indicators in the decision-making of the material deployment programme in the early stages of an outbreak. In the long-term control of the epidemic, the number of patients with minor illnesses generally peaks around 20 days, while the number of patients with severe illnesses generally peaks around 40 days, providing a focus for the supply of supplies at different times in the actual development of the epidemic, in order to better and more effectively control the epidemic and reduce inefficient consumption of supplies.

摘要

作为 2020 年的一项严重突发事件,COVID-19 对人们的生活产生了巨大影响。本文研究了 COVID-19 爆发后一个地区对紧急物资需求的短期和长期应对。首先,采用多目标决策方法对 COVID-19 早期不同地区资源协调方案进行了比较研究,得出了最优解。然后,建立了一个系统动力学模型来预测疫情的后续发展,以研究不同时期不同物资需求的紧迫性。结果表明,时间和满意度是疫情早期物资调配方案决策中最重要的两个指标。在疫情的长期控制中,轻症患者的数量一般在 20 天左右达到峰值,而重症患者的数量一般在 40 天左右达到峰值,为疫情实际发展过程中不同时期的物资供应提供了重点,以便更好、更有效地控制疫情,减少物资的低效消耗。

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