School of Public Health, Xuzhou Medical University, Xuzhou, China.
School of Management, Xuzhou Medical University, Xuzhou, China.
Front Public Health. 2023 Feb 24;11:992197. doi: 10.3389/fpubh.2023.992197. eCollection 2023.
The resources available to fight an epidemic are typically limited, and the time and effort required to control it grow as the start date of the containment effort are delayed. When the population is afflicted in various regions, scheduling a fair and acceptable distribution of limited available resources stored in multiple emergency resource centers to each epidemic area has become a serious problem that requires immediate resolution.
This study presents an emergency medical logistics model for rapid response to public health emergencies. The proposed methodology consists of two recursive mechanisms: (1) time-varying forecasting of medical resources and (2) emergency medical resource allocation. Considering the epidemic's features and the heterogeneity of existing medical treatment capabilities in different epidemic areas, we provide the modified susceptible-exposed-infected-recovered (SEIR) model to predict the early stage emergency medical resource demand for epidemics. Then we define emergency indicators for each epidemic area based on this. By maximizing the weighted demand satisfaction rate and minimizing the total vehicle travel distance, we develop a bi-objective optimization model to determine the optimal medical resource allocation plan.
Decision-makers should assign appropriate values to parameters at various stages of the emergency process based on the actual situation, to ensure that the results obtained are feasible and effective. It is necessary to set up an appropriate number of supply points in the epidemic emergency medical logistics supply to effectively reduce rescue costs and improve the level of emergency services.
Overall, this work provides managerial insights to improve decisions made on medical distribution as per demand forecasting for quick response to public health emergencies.
应对疫情的资源通常是有限的,而且随着控制疫情的努力开始日期的推迟,所需的时间和精力也会增加。当疫情在不同地区爆发时,如何公平合理地分配存储在多个应急资源中心的有限可用资源,成为一个亟待解决的严重问题。
本研究提出了一种用于快速应对突发公共卫生事件的紧急医疗物流模型。所提出的方法由两个递归机制组成:(1)医疗资源的时变预测,(2)紧急医疗资源分配。考虑到疫情的特点和不同疫情地区现有医疗能力的异质性,我们提供了修正后的易感-暴露-感染-恢复(SEIR)模型来预测疫情早期的紧急医疗资源需求。然后,我们根据这个模型为每个疫情地区定义了紧急指标。通过最大化加权需求满意度和最小化总车辆行驶距离,我们开发了一个双目标优化模型来确定最佳的医疗资源分配计划。
决策者应根据实际情况在应急过程的各个阶段为参数赋予适当的值,以确保获得的结果是可行和有效的。在疫情应急医疗物流供应中设置适当数量的供应点,可以有效降低救援成本,提高应急服务水平。
总的来说,这项工作为改进医疗分配决策提供了管理方面的见解,以便根据需求预测快速应对突发公共卫生事件。