期刊文献+

基于真实世界数据的修正SEIR模型应用于疫情防控研究

Application of Modified SEIR Model in Epidemic Prevention and Control:a Real World Study
下载PDF
导出
摘要 背景奥密克戎在世界各地广泛传播,深圳作为连接国内外交通的重要枢纽,自2022年2月以来持续受其影响,感染者数量迅速增加。目的构建修正的易感-暴露-感染-康复(SEIR)模型,为深圳市疫情防控工作提供具有应用价值的政策参考和建议,以缓解防控压力。方法在传统SEIR传染病动力学模型基础上,针对奥密克戎传播速度快、隐匿性高、人群普遍易感等流行病学特征,引入具有政策性特征的组别,即密接者、次密接者、入深隔离者和携带者组别,构建修正SEIR模型,拟合2022-02-18—28的深圳疫情数据确定修正模型的相关参数。结果该模型的预测数据与2022-03-01—04的实际数据基本一致,为预测疫情后续发展提供了可靠依据;进一步预测了2022-03-05—19的疫情发展趋势,从疫情防控的人工干预程度、介入时间及床位数、隔离房间数等医疗卫生资源需求等方面为深圳后续的疫情防控措施提供了指导。结论修正SEIR模型在疫情发展预测、防控措施制定和调整及医疗资源配置等方面具有重要实用价值。 Background The Severe Acute Respiratory Syndrome Coronavirus 2 Omicron variant(SARS-CoV-2,Omicron)has been widely spread around the world.Since February 2022,Shenzhen was continuously affected by it as a major hub connecting domestic and international transportation,resulting in rapidly increasing number of infected cases.Objective To construct a modified susceptible-exposed-infected-recovered(SEIR)model for providing policy references and suggestions with applied value for epidemic prevention and control in Shenzhen,China,so as to alleviate the pressure of prevention and control.Methods This study developed a modified SEIR model targeting the epidemiological characteristics of the Omicron variant such as rapid transmission,high concealment,and general susceptibility of the population,introducing groups with policy characteristics as close contacts,secondary contacts,quarantined individuals and carriers,based on traditional SEIR model of infectious disease dynamics.The relevant parameters of the modified model were determined by fitting the Shenzhen epidemic data of February 18 to 28,2022.Results The predicted data of the model were basically consistent with the actual data from March 01 to 04,2022,providing a reliable basis for predicting the subsequent development of the epidemic.Subsequently,the Omicron variant outbreak in Shenzhen between 5 to 19 March 2022 was forecasted through this modified model to provide guidance for epidemic prevention and control measures in terms of the degree and time of manual intervention in epidemic prevention and control,and healthcare resource requirements such as patient beds and isolation rooms.Conclusion The modified SEIR model developed in this study has proved its practical value in forecasting epidemic development,formulating and adjusting epidemic control measures,and allocating health resources.
作者 杨利超 曾华堂 胡梦之 伍丽群 田倩男 韦亮州 朱纪明 梁万年 YANG Lichao;ZENG Huatang;HU Mengzhi;WU Liqun;TIAN Qiannan;WEI Liangzhou;ZHU Jiming;LIANG Wannian(Vanke School of Public Health,Tsinghua University,Beijing 100084,China;Shenzhen Health Development Research and Data Management Center,Shenzhen 518028,China;Institute for Healthy China,Tsinghua University,Beijing 100084,China)
出处 《中国全科医学》 北大核心 2024年第1期118-124,共7页 Chinese General Practice
基金 国家自然科学基金资助项目(72091514) 深圳市“医疗卫生三名工程”项目资助(20212001132) 清华大学卫健学院博士后科研专项(2022BH013) 比尔及梅琳达·盖茨基金会项目资助(INV-018302)。
关键词 新型冠状病毒感染 奥密克戎 修正SEIR模型 预测 政策建议 医疗资源配置 COVID-19 Omicron Modified SEIR model Forecasting Policies Health resources allocation
  • 相关文献

参考文献10

二级参考文献41

  • 1STEVEN RILEY. Transmission Dynamics of the Etiological Agent of SARS in Hong Kong: Impact of Public Health Interventions [ EB \ OL ]. http:∥www. sciencexpress. org/23 May 2003/Page 1/10. 1126/science. 1086478, 2003,5.23.
  • 2MARC LIPSITCH. Transmission Dynamics and Control of Severe Acute Respiratory Syndrome[ EB\OL]. http:∥www. sciencexpress. org/23 May2003/Page 2/10. 1126/science. 1086925, 2003,5.23.
  • 3CHOWELL G. SARS outbreaks in Ontario, Hong Kong and Singapore: the role of diagnosis and isolation as a control mechanism[ J ]. Journal of Theoretical Biology, 2003,224( 1 ) :1 -8.
  • 4CLARKE F H, LEDYAEV YU S, STERN R J, et al. Nonsmooth Analysis and Control Theory[ M]. New York: Springer, 1998.
  • 5ZHANG Juan, MA Zhi - en. Global dynamics of an SEIR epidemic model with saturating contact rate[ J]. Mathematical Biosciences, 2003,185(1) :15 -32.
  • 6POLAK ELIJAH. Optimization Algorithms and Consistent Approximations[ M ]. New York: Springer, 1997.
  • 7周涛,刘权辉,杨紫陌,廖敬仪,杨可心,白薇,吕欣,张伟.新型冠状病毒肺炎基本再生数的初步预测[J].中国循证医学杂志,2020,20(3):359-364. 被引量:168
  • 8中国疾病预防控制中心新型冠状病毒肺炎疫情防控技术组,冯子健,陈秋兰,冯录召,李中杰,黎舒,秦颖,王晴,杨孝坤,殷文武,张慕丽,张婷,安志杰,李媛秋,吴丹,尹遵栋,俞海亮,陈伟,夏愔愔,张若尘,Lance Rodewald.新型冠状病毒肺炎疫情紧急研究议程:传播和非药物缓疫策略[J].中华流行病学杂志,2020,41(2):135-138. 被引量:36
  • 9中华预防医学会新型冠状病毒肺炎防控专家组,李立明,梁晓峰,姜庆五,汪华,王波,杨维中,王充,刘霞,吴凡,张志杰,陈峰,赵杨,魏永越,沈思鹏,郝元涛,杜志成,唐金陵,任军,毕振强,邓瑛,王岚.新型冠状病毒肺炎流行病学特征的最新认识[J].中华流行病学杂志,2020,41(2):139-144. 被引量:665
  • 10中国疾病预防控制中心新型冠状病毒肺炎应急响应机制流行病学组,张彦平.新型冠状病毒肺炎流行病学特征分析[J].中华流行病学杂志,2020,41(2):145-146. 被引量:1632

共引文献237

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部