基于入侵模型和动态模型的SARS-CoV-2基因组最优控制策略

IF 4.8 1区 医学 Q1 INFECTIOUS DISEASES
Jia Rui, Jin-Xin Zheng, Jin Chen, Hongjie Wei, Shanshan Yu, Zeyu Zhao, Xin-Yi Wang, Mu-Xin Chen, Shang Xia, Ying Zhou, Tianmu Chen, Xiao-Nong Zhou
{"title":"基于入侵模型和动态模型的SARS-CoV-2基因组最优控制策略","authors":"Jia Rui,&nbsp;Jin-Xin Zheng,&nbsp;Jin Chen,&nbsp;Hongjie Wei,&nbsp;Shanshan Yu,&nbsp;Zeyu Zhao,&nbsp;Xin-Yi Wang,&nbsp;Mu-Xin Chen,&nbsp;Shang Xia,&nbsp;Ying Zhou,&nbsp;Tianmu Chen,&nbsp;Xiao-Nong Zhou","doi":"10.1186/s40249-022-01039-y","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>There is a raising concern of a higher infectious Omicron BA.2 variant and the latest BA.4, BA.5 variant, made it more difficult in the mitigation process against COVID-19 pandemic. Our study aimed to find optimal control strategies by transmission of dynamic model from novel invasion theory.</p><p><strong>Methods: </strong>Based on the public data sources from January 31 to May 31, 2022, in four cities (Nanjing, Shanghai, Shenzhen and Suzhou) of China. We segmented the theoretical curves into five phases based on the concept of biological invasion. Then, a spatial autocorrelation analysis was carried out by detecting the clustering of the studied areas. After that, we choose a mathematical model of COVID-19 based on system dynamics methodology to simulate numerous intervention measures scenarios. Finally, we have used publicly available migration data to calculate spillover risk.</p><p><strong>Results: </strong>Epidemics in Shanghai and Shenzhen has gone through the entire invasion phases, whereas Nanjing and Suzhou were all ended in the establishment phase. The results indicated that Rt value and public health and social measures (PHSM)-index of the epidemics were a negative correlation in all cities, except Shenzhen. The intervention has come into effect in different phases of invasion in all studied cities. Until the May 31, most of the spillover risk in Shanghai remained above the spillover risk threshold (18.81-303.84) and the actual number of the spillovers (0.94-74.98) was also increasing along with the time. Shenzhen reported Omicron cases that was only above the spillover risk threshold (17.92) at the phase of outbreak, consistent with an actual partial spillover. In Nanjing and Suzhou, the actual number of reported cases did not exceed the spillover alert value.</p><p><strong>Conclusions: </strong>Biological invasion is positioned to contribute substantively to understanding the drivers and mechanisms of the COVID-19 spread and outbreaks. After evaluating the spillover risk of cities at each invasion phase, we found the dynamic zero-COVID strategy implemented in four cities successfully curb the disease epidemic peak of the Omicron variant, which was highly correlated to the way to perform public health and social measures in the early phases right after the invasion of the virus.</p>","PeriodicalId":13587,"journal":{"name":"Infectious Diseases of Poverty","volume":null,"pages":null},"PeriodicalIF":4.8000,"publicationDate":"2022-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9701379/pdf/","citationCount":"6","resultStr":"{\"title\":\"Optimal control strategies of SARS-CoV-2 Omicron supported by invasive and dynamic models.\",\"authors\":\"Jia Rui,&nbsp;Jin-Xin Zheng,&nbsp;Jin Chen,&nbsp;Hongjie Wei,&nbsp;Shanshan Yu,&nbsp;Zeyu Zhao,&nbsp;Xin-Yi Wang,&nbsp;Mu-Xin Chen,&nbsp;Shang Xia,&nbsp;Ying Zhou,&nbsp;Tianmu Chen,&nbsp;Xiao-Nong Zhou\",\"doi\":\"10.1186/s40249-022-01039-y\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>There is a raising concern of a higher infectious Omicron BA.2 variant and the latest BA.4, BA.5 variant, made it more difficult in the mitigation process against COVID-19 pandemic. Our study aimed to find optimal control strategies by transmission of dynamic model from novel invasion theory.</p><p><strong>Methods: </strong>Based on the public data sources from January 31 to May 31, 2022, in four cities (Nanjing, Shanghai, Shenzhen and Suzhou) of China. We segmented the theoretical curves into five phases based on the concept of biological invasion. Then, a spatial autocorrelation analysis was carried out by detecting the clustering of the studied areas. After that, we choose a mathematical model of COVID-19 based on system dynamics methodology to simulate numerous intervention measures scenarios. Finally, we have used publicly available migration data to calculate spillover risk.</p><p><strong>Results: </strong>Epidemics in Shanghai and Shenzhen has gone through the entire invasion phases, whereas Nanjing and Suzhou were all ended in the establishment phase. The results indicated that Rt value and public health and social measures (PHSM)-index of the epidemics were a negative correlation in all cities, except Shenzhen. The intervention has come into effect in different phases of invasion in all studied cities. Until the May 31, most of the spillover risk in Shanghai remained above the spillover risk threshold (18.81-303.84) and the actual number of the spillovers (0.94-74.98) was also increasing along with the time. Shenzhen reported Omicron cases that was only above the spillover risk threshold (17.92) at the phase of outbreak, consistent with an actual partial spillover. In Nanjing and Suzhou, the actual number of reported cases did not exceed the spillover alert value.</p><p><strong>Conclusions: </strong>Biological invasion is positioned to contribute substantively to understanding the drivers and mechanisms of the COVID-19 spread and outbreaks. After evaluating the spillover risk of cities at each invasion phase, we found the dynamic zero-COVID strategy implemented in four cities successfully curb the disease epidemic peak of the Omicron variant, which was highly correlated to the way to perform public health and social measures in the early phases right after the invasion of the virus.</p>\",\"PeriodicalId\":13587,\"journal\":{\"name\":\"Infectious Diseases of Poverty\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":4.8000,\"publicationDate\":\"2022-11-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9701379/pdf/\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Infectious Diseases of Poverty\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1186/s40249-022-01039-y\",\"RegionNum\":1,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"INFECTIOUS DISEASES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Infectious Diseases of Poverty","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1186/s40249-022-01039-y","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"INFECTIOUS DISEASES","Score":null,"Total":0}
引用次数: 6

摘要

背景:人们越来越担心传染性更强的奥密克戎BA.2变异株和最新的BA.4、BA.5变异株,这使新冠肺炎疫情的缓解过程更加困难。我们的研究旨在通过传递新入侵理论中的动态模型来寻找最优控制策略。方法:基于2022年1月31日至5月31日在中国四个城市(南京、上海、深圳和苏州)的公开数据来源。基于生物入侵的概念,我们将理论曲线划分为五个阶段。然后,通过检测研究区域的聚类,进行空间自相关分析。然后,我们选择了一个基于系统动力学方法的新冠肺炎数学模型来模拟多种干预措施场景。最后,我们使用了公开的移民数据来计算溢出风险。结果:上海和深圳的疫情经历了整个入侵阶段,而南京和苏州的疫情均在建立阶段结束。结果表明,除深圳外,所有城市的Rt值与公共卫生和社会措施指数均呈负相关。干预措施在所有研究城市的不同入侵阶段都已生效。直到5月31日,上海的大部分溢出风险仍保持在溢出风险阈值(18.81-303.84)以上,实际溢出次数(0.94-74.98)也随着时间的推移而增加。深圳报告的奥密克戎病例在疫情爆发阶段仅高于溢出风险阈值(17.92),与实际的部分溢出一致。在南京和苏州,实际报告的病例数没有超过溢出警报值。结论:生物入侵对理解新冠肺炎传播和爆发的驱动因素和机制有实质性贡献。在评估了每个入侵阶段城市的溢出风险后,我们发现在四个城市实施的动态零新冠策略成功遏制了奥密克戎变异株的疾病流行高峰,这与病毒入侵后早期执行公共卫生和社会措施的方式高度相关。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Optimal control strategies of SARS-CoV-2 Omicron supported by invasive and dynamic models.

Optimal control strategies of SARS-CoV-2 Omicron supported by invasive and dynamic models.

Optimal control strategies of SARS-CoV-2 Omicron supported by invasive and dynamic models.

Optimal control strategies of SARS-CoV-2 Omicron supported by invasive and dynamic models.

Background: There is a raising concern of a higher infectious Omicron BA.2 variant and the latest BA.4, BA.5 variant, made it more difficult in the mitigation process against COVID-19 pandemic. Our study aimed to find optimal control strategies by transmission of dynamic model from novel invasion theory.

Methods: Based on the public data sources from January 31 to May 31, 2022, in four cities (Nanjing, Shanghai, Shenzhen and Suzhou) of China. We segmented the theoretical curves into five phases based on the concept of biological invasion. Then, a spatial autocorrelation analysis was carried out by detecting the clustering of the studied areas. After that, we choose a mathematical model of COVID-19 based on system dynamics methodology to simulate numerous intervention measures scenarios. Finally, we have used publicly available migration data to calculate spillover risk.

Results: Epidemics in Shanghai and Shenzhen has gone through the entire invasion phases, whereas Nanjing and Suzhou were all ended in the establishment phase. The results indicated that Rt value and public health and social measures (PHSM)-index of the epidemics were a negative correlation in all cities, except Shenzhen. The intervention has come into effect in different phases of invasion in all studied cities. Until the May 31, most of the spillover risk in Shanghai remained above the spillover risk threshold (18.81-303.84) and the actual number of the spillovers (0.94-74.98) was also increasing along with the time. Shenzhen reported Omicron cases that was only above the spillover risk threshold (17.92) at the phase of outbreak, consistent with an actual partial spillover. In Nanjing and Suzhou, the actual number of reported cases did not exceed the spillover alert value.

Conclusions: Biological invasion is positioned to contribute substantively to understanding the drivers and mechanisms of the COVID-19 spread and outbreaks. After evaluating the spillover risk of cities at each invasion phase, we found the dynamic zero-COVID strategy implemented in four cities successfully curb the disease epidemic peak of the Omicron variant, which was highly correlated to the way to perform public health and social measures in the early phases right after the invasion of the virus.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Infectious Diseases of Poverty
Infectious Diseases of Poverty Medicine-Public Health, Environmental and Occupational Health
CiteScore
16.70
自引率
1.20%
发文量
368
审稿时长
13 weeks
期刊介绍: Infectious Diseases of Poverty is a peer-reviewed, open access journal that focuses on essential public health questions related to infectious diseases of poverty. It covers a wide range of topics and methods, including the biology of pathogens and vectors, diagnosis and detection, treatment and case management, epidemiology and modeling, zoonotic hosts and animal reservoirs, control strategies and implementation, new technologies, and their application. The journal also explores the impact of transdisciplinary or multisectoral approaches on health systems, ecohealth, environmental management, and innovative technologies. It aims to provide a platform for the exchange of research and ideas that can contribute to the improvement of public health in resource-limited settings. In summary, Infectious Diseases of Poverty aims to address the urgent challenges posed by infectious diseases in impoverished populations. By publishing high-quality research in various areas, the journal seeks to advance our understanding of these diseases and contribute to the development of effective strategies for prevention, diagnosis, and treatment.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信