A Model of Artificial Prevention and Control Measures for COVID⁃19 Isolation and Reception and Cure Based on Discrete Grids.

ABSTRACT

With the outbreak of coronavirus disease 2019 (COVID ‐19) in the world, researches on the related epidemic situation are also constantly increasing. However, the current researches focus more on the predic‐ tion analysis and the researches on epidemic situation prevention and control measures, remain at the statis‐ tical level and the model parameters lack spatiotemporal evolution description. This paper introduces the granularity and virtual real line of the boundary of the discrete grid to describe the tightness of physical isola‐ tion measures and the connectivity and isolation of adjacent spaces separately and designs the medical recep‐ tion and cure model under the discrete grid based on the spatial autocorrelation between the medical bed ad‐ mission capacity and the grid. Furthermore, the LSEIR (logistic‐susceptible‐exposed‐infected‐removed) epi‐ demic model is used to construct the artificial prevention and control measures model of physical isolation and medical reception and cure under the discrete grid, which provides an effective method to analyze and assess the impacts of the artificial prevention and control measures model of physical isolation and medical reception and cure on the spread and prevention and control of the epidemic situation. The original spatio‐ temporal evolution of COVID ‐19 epidemic situation in Wuhan, China was simulated with the early data of epidemic of the United States, Germany, Spain, and the United Kingdom, the experimental analysis result of epidemic situation data in Wuhan, China shows that physical isolation measures have a very obvious effect on reducing the peak value of infected population, advancing the peak of the inflection point and shortening the duration of the epidemic situation;medical reception and cure measures can effectively re‐ duce the peak value of the infected population in the early stage of the epidemic, but has no significant im‐ pact on the advance of the peak inflection point and the shortening of the epidemic duration;the model can analyze and assess the impacts of physical isolation and medical reception and cure measures on the epidem ‐ ic situation from both quantitative and qualitative perspectives, which has high rationality and correctness. (English) [ABSTRACT FROM AUTHOR] 随着新型冠状病毒肺炎（coronavirus disease 2019，COVID‐19）疫情在全世界的暴发，与疫情相关的研 究不断增加，但目前的研究更多关注的是预测分析方面，与疫情防控措施有关的研究基本停留在统计学层面， 且模型参数缺乏时空演变描述。为此，引入离散格网的粒度和边界虚实线分别描述物理隔离措施的松紧程度 及相邻空间的联通性和隔离性，以病床收治能力与格网之间的空间自相关性为基础设计了离散格网下的医疗 收治模型，进而利用 LSEIR (logistic‐susceptible‐exposed‐infected‐removed)传染病模型构建了离散格网下的物 理隔离与医疗收治人为防控措施模型，该模型为分析和评估物理隔离与医疗收治人为防控措施对疫情传播和 防控的影响提供了一种有效的方法。分别以美国、德国、西班牙和英国的疫情初期数据模拟了中国武汉市 COVID‐19 疫情的原始传播态势，通过对武汉地区疫情数据的实验分析可以得到，物理隔离措施对降低感染 人群峰值、提前峰值拐点以及缩短疫情的持续时间有非常明显的作用；医疗收治措施在疫情初期可有效降低 感染人群峰值，而对峰值拐点的提前和疫情持续时间的缩短没有较大影响；该模型能够从定量和定性两个角 度实现物理隔离和医疗收治措施对疫情影响的量化分析与评估，具有较高的合理性和正确性。 (Chinese) [ABSTRACT FROM AUTHOR] Copyright of Geomatics & Information Science of Wuhan University is the property of Geomatics & Information Science of Wuhan University and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)