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基于主体模型的特定暴露时间内通过社区卫生服务中心评估进行病毒检测模拟——以武汉为例

Agent-Based Simulation of Virus Testing in Certain-Exposure Time through Community Health Service Centers' Evaluation-A Case Study of Wuhan.

作者信息

Zhou Xingyu, Zhao Jie, Zheng Duanya, Yu Yang, Liu Lingbo

机构信息

Department of Urban Planning, Wuhan Planning & Design Institute, Wuhan 430014, China.

Department of Urban Planning, School of Urban Design, Wuhan University, Wuhan 430072, China.

出版信息

Healthcare (Basel). 2021 Nov 8;9(11):1519. doi: 10.3390/healthcare9111519.

DOI:10.3390/healthcare9111519
PMID:34828565
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8617634/
Abstract

Short-term and large-scale full-population virus testing is crucial in containing the spread of the COVID-19 pandemic in China. However, the uneven distribution of health service facilities in terms of space and size may lead to prolonged crowding during testing, thus increasing the chance of virus cross-infection. Therefore, appropriate control of crowd exposure time in large-scale virus testing should be an important goal in the layout of urban community health facilities. This paper uses the Quanta concept and Wells-Riley model to define the "certain-exposure time" under low cross-infection rate. Then, an agent-based simulation model was used to simulate the reasonable screening efficiency of community health service facilities during certain-exposure time at different stages of the COVID-19 pandemic and under different screening processes. Eventually, the screening efficiency was evaluated for all community health service centers in Wuhan. During the early period of the pandemic, 23.13% of communities failed to complete virus testing of community residents within 2 h of certain-exposure time, leaving approximately 56.07% of the population unscreened; during the later period of the COVID-19 pandemic, approximately 53% of communities and 75% of residents could not be screened. The results can pinpoint the distribution of community health service centers with inadequate screening capacity, facilitate targeted policymaking and planning, and effectively curb COVID-19 cross-infection during screening.

摘要

短期大规模全员病毒检测对于遏制新冠疫情在中国的传播至关重要。然而,医疗卫生服务设施在空间和规模上分布不均,可能导致检测期间人群长时间聚集,从而增加病毒交叉感染的几率。因此,在大规模病毒检测中合理控制人群暴露时间应成为城市社区卫生设施布局的一个重要目标。本文运用量子概念和威尔斯-莱利模型来定义低交叉感染率下的“特定暴露时间”。然后,使用基于智能体的模拟模型,模拟新冠疫情不同阶段以及不同筛查流程下社区卫生服务设施在特定暴露时间内的合理筛查效率。最终,对武汉市所有社区卫生服务中心的筛查效率进行了评估。在疫情初期特定暴露时间的2小时内,23.13%的社区未能完成社区居民的病毒检测,约56.07%的人口未接受筛查;在新冠疫情后期,约53%的社区和75%的居民无法得到筛查。研究结果能够精准找出筛查能力不足的社区卫生服务中心的分布情况,有助于针对性地制定政策和规划,并有效遏制筛查期间的新冠交叉感染。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4759/8617634/8c91360e23fb/healthcare-09-01519-g012.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4759/8617634/8f0f51bc1c45/healthcare-09-01519-g008.jpg
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