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基于SEIR模型的数字化技术在重大疫情应急预案中的应用

Apply the SEIR Model to Producing Digitalized Emergency Plans against Major Epidemics.
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摘要 目的:本文采用SEIR(Susceptible-Exposed-Infected-Recovered)模型模拟我国传染病暴发、传播及流行机制,应用数字化仿真技术以解决传统重大疫情应急预案更新不及时、多使用场景难以同时适用以及医疗资源分配不均衡等问题。方法:以2022年8月1日-8月20日的密接、次密接及康复者数据为基础,设计干预函数,拟合流行病学特征参数,构建改进SEIR模型,并使用MATLAB软件搭建数字化仿真环境生成《新型冠状病毒肺炎诊疗方案(试行第九版)》应急预案内容。结果:在疫苗接种率从89.7%提升到95.0%以上,携带者数量可减少约37.9%。对密接者采取14日集中隔离+6日居家健康监测和对次密接者采取14日居家健康监测的防控策略,本地感染者数量最多可下降60.0%。将感染者集中救治时间由14天降至7天,可最多节约7.6%的床位。结论:数字化技术生成的应急预案,可快速指导政策制定者适时调整疫苗接种、密接和次密接隔离时间及感染者集中治疗时间等策略,以实现精准高效防控。 Objective The SEIR(Susceptible-Exposed-Infected-Recovered)simulate can model the outbreak,spread and epidemic mechanism of infectious disease in the paper,the digitalized technology based on SEIR model can solve the problem of untimely updates of traditional major epidemic emergency plans,the difficulty of simultaneously applying to multiple usage sce⁃narios and the unbalanced distribution of medical resources.Methods Based on the primary contacts,secondary contacts and the recovered data collected from August 1 to August 20 in 2022,an intervention function is designed to fit epidemiological character⁃istic parameters and construct an improved SEIR model.The study uses MATLAB software to build a digital simulation environ⁃ment to generate the content of the emergency plan for the“Diagnosis and Treatment Protocol for COVID-19(Trial Version 9)”.Results When the vaccination rate exceeds 95.0%,a reduction of approximately 37.9%in the number of carriers can be observed compared to 89.7%.Close contacts undergo a 14-day period of centralized isolation followed by 6-day home health monitoring,while second-close contacts undergo 14-day home health monitoring.As a result,the number of locally infected individuals has decreased by up to 60.0%.Shortening the centralized treatment duration for infected patients from 14 days to 7 days can lead to a saving of up to 7.6%of beds.Conclusions The utilization of digital technology in generating emergency plans enables policymak⁃ers to promptly adapt strategies like vaccination,isolation of close contacts and sub-close contacts,and centralized treatment time of the infected.It also enables precise and efficient prevention and control measures to be achieved in a timely manner.
作者 杨利超 赵泽惠 胡梦之 张鹤立 伍丽群 庄诺亚 梁万年 朱纪明 Yang lichao(School of Pudic Health Suzhou Medical College of Soochow University,Suzhou,P.R.china)
出处 《中国卫生事业管理》 北大核心 2023年第11期801-808,共8页 Chinese Health Service Management
基金 国家自然科学基金“复合型公共卫生事件暴发的风险评估及医疗资源保障优化体系建设”(72091514) 深圳市“医疗卫生三名工程”项目资助(20212001132) 清华大学万科公共卫生与健康学院科研基金“基于边缘计算技术和人工智能算法的新冠肺炎(COVID-19)防控管理模式研究”(2022BH013) 比尔及梅琳达·盖茨基金会“提升公卫应急反应能力的健康体系整合项目”(INV-018302)。
关键词 重大疫情 改进SEIR模型 数字化 实验环境 应急预案 Major epidemics Modified SEIR Model Digitalization Generation platform Automatic emergency plans
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