%0 Journal Article
%T 基于污水流行病原理的病毒检测点选址问题研究——以湖南省娄底市为例<br>Research on the Location of Virus Detection Points Based on the Principle of Sewage Epidemic—Taking Loudi City, Hunan Province as an Example
%A 邓润婕
%A 罗志军
%A 杨佳
%J Pure Mathematics
%P 3236-3245
%@ 2160-7605
%D 2023
%I Hans Publishing
%R 10.12677/PM.2023.1311337
%X 近年来，我国的公共卫生事件具有明显的突发性、不确定性等特点，对于突发性的病毒，当病毒大规模爆发时，污水流行病学(WEB)作为临床监测的补充方法，相比血常规、特异性血清检查和核酸检测等常规检测方法有着更简便、广泛和接近实时监测的优点，对于区域疾病监测有着广泛的应用前景。该项技术取决于污水收集系统等基础设施的发展与完善，然而我国在该方面的研究、应用起步较晚，目前我国有关污水病毒检测的研究取样范围大多局限于一两座污水处理厂，同时也没有标准化的WBE应用方案。基于此，本文以湖南省娄底市为例，考虑各社区人口分布以及建设成本，结合WBE的三阶段处理效率，即对象释放效率、管道输送效率、检测回收效率，先后通过K-means聚类模型和TOPSIS综合评价法，研究娄底市区常规污水疾病采样点的优化选址问题。<br />
In recent years, China’s public health events have obvious suddenness, uncertainty and other characteristics, for sudden viruses, when the virus large-scale outbreak, wastewater based epide-miology (WEB) as a supplementary method of clinical surveillance, compared with routine detec-tion methods such as blood routine, specific serum test and nucleic acid detection has the ad-vantages of simpler, extensive and near-real-time monitoring, for regional disease surveillance has a wide application prospects. The technology depends on the development and improvement of infrastructure such as sewage collection systems, but China’s research and application in this area started late, and most of the research and sampling scope of sewage virus detection in China is limited to one or two sewage treatment plants, and there is no standardized WBE application program. Based on this, this paper takes Loudi City as the object, combined with the three-stage treatment efficiency of WBE, namely object release efficiency, pipeline transportation efficiency, and detection and recovery efficiency, and successively uses K-means clustering model and TOPSIS comprehensive evaluation method to study the optimal site selection of conventional sewage dis-ease sampling points in Loudi urban area.
%K 污水流行病，病毒检测点，K-Means聚类，TOPSIS综合评价法<br>Sewage Epidemic
%K Virus Detection Points
%K K-Means Clustering
%K TOPSIS Comprehensive Evaluation Method
%U http://www.hanspub.org/journal/PaperInformation.aspx?PaperID=75761