School of Resources and Environmental Engineering, Wuhan University of Technology, No. 122, Luoshi Road, Hongshan District, Wuhan, Hubei Province, People's Republic of China.
Wuhan Transportation Planning and Design Co., Ltd., Huijin Plaza, 1268 Jinghan Avenue, Jiang'an District, Wuhan, Hubei Province, People's Republic of China.
BMC Health Serv Res. 2021 Sep 13;21(1):959. doi: 10.1186/s12913-021-06831-4.
The current 2019 coronavirus disease (COVID-19) pandemic is hitting citizen's life and health like never before, with its significant loss to human life and a huge economic toll. In this case, the fever clinics (FCs) were still preserved as one of the most effective control measures in China, but this work is based on experience and lacks scientific and effective guidance. Here, we use travel time to link facilities and populations at risk of COVID-19 and identify the dynamic allocation of patients' medical needs, and then propose the optimized allocation scheme of FCs.
We selected Shenzhen, China, to collect geospatial resources of epidemic communities (ECs) and FCs to determine the ECs' cumulative opportunities of visiting FCs, as well as evaluate the rationality of medical resources in current ECs. Also, we use the Location Set Covering Problem (LSCP) model to optimize the allocation of FCs and evaluate efficiency.
Firstly, we divide the current ECs into 3 groups based on travel time and cumulative opportunities of visiting FCs within 30 min: Low-need communities (22.06%), medium-need communities (59.8%), and high-need communities (18.14%) with 0,1-2 and no less than 3 opportunities of visiting FCs. Besides, our work proposes two allocation schemes of fever clinics through the LSCP model. Among which, selecting secondary and above hospitals as an alternative in Scheme 1, will increase the coverage rate of hospitals in medium-need and high-need communities from 59.8% to 80.88%. In Scheme 2, selecting primary and above hospitals as an alternative will increase the coverage rate of hospitals in medium-need and high-need communities to 85.29%, with the average travel time reducing from 22.42 min to 17.94 min.
The optimized allocation scheme can achieve two objectives: a. equal access to medical services for different types of communities has improved while reducing the overutilization of high-quality medical resources. b. the travel time for medical treatment in the community has reduced, thus improving medical accessibility. On this basis, during the early screening in prevention and control of the outbreak, the specific suggestions for implementation in developing and less developed countries are made.
当前的 2019 冠状病毒病(COVID-19)大流行前所未有地影响着公民的生活和健康,造成了巨大的生命损失和经济损失。在这种情况下,发热门诊(FC)仍然是中国最有效的控制措施之一,但这项工作是基于经验,缺乏科学有效的指导。在这里,我们使用旅行时间将设施与 COVID-19 风险人群联系起来,并确定患者医疗需求的动态分配,然后提出 FC 的优化配置方案。
我们选择中国深圳,收集疫情社区(EC)和 FC 的地理空间资源,以确定 EC 访问 FC 的累计机会,并评估当前 EC 中医疗资源的合理性。此外,我们使用位置集覆盖问题(LSCP)模型来优化 FC 的分配并评估效率。
首先,我们根据旅行时间和 30 分钟内访问 FC 的累计机会,将当前 EC 分为 3 组:低需求社区(22.06%)、中需求社区(59.8%)和高需求社区(18.14%),分别有 0、1-2 和不少于 3 次访问 FC 的机会。此外,我们的工作通过 LSCP 模型提出了两种 FC 分配方案。其中,在方案 1 中选择二级及以上医院作为替代方案,将中需求和高需求社区的医院覆盖率从 59.8%提高到 80.88%。在方案 2 中,选择一级及以上医院作为替代方案,将中需求和高需求社区的医院覆盖率提高到 85.29%,平均就诊时间从 22.42 分钟缩短到 17.94 分钟。
优化的分配方案可以实现两个目标:a. 不同类型社区的医疗服务均等化得到改善,同时减少了高质量医疗资源的过度利用。b. 社区就医的出行时间减少,提高了医疗的可及性。在此基础上,针对发展中国家和欠发达国家的早期防控筛查,提出了具体的实施建议。