Please wait a minute...
文章检索
复杂系统与复杂性科学  2021, Vol. 18 Issue (4): 1-8    DOI: 10.13306/j.1672-3813.2021.04.001
  本期目录 | 过刊浏览 | 高级检索 |
基于“病毒变异”和“环境传人”因素的COVID-19疫情传播动力学研究
李稚, 宋敏
天津工业大学经济与管理学院,天津 300387
Transmission Dynamics of Coronavirus Disease 2019 Based on “Virus Variants” and “Environment-to-human”
LI Zhi, SONG Min
School of Economics and Management, Tiangong university, Tianjin 300387, China
全文: PDF(2262 KB)  
输出: BibTeX | EndNote (RIS)      
摘要 针对目前新型冠状病毒(COVID-19)在中国出现“环境传人”现象,且多国发现新冠病毒变异传染性增强情况。考虑新型冠状病毒“环境传人”传播途径和病毒变异两因素,建立传染病动力学SEIQR模型,进行疫情发展趋势仿真模拟。结果表明,“环境传人”和病毒变异对新冠疫情的传播范围和传播速度产生正向影响,其中,病毒变异对其影响更加显著,而“环境传人”因素会促使疫情爆发时间点大幅提前。对于传染率较高的变异病毒,提高干预措施的强度对抑制变异COVID-19病毒传播的控制效果更为显著。
服务
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章
李稚
宋敏
关键词 COVID-19“环境传人”病毒变异SEIQR模型    
Abstract:Recently, “environment-to-human” transmission has become a new pattern in the spread of COVID-19, and novel coronavirus variants with increased infectivity have appeared in many countries. With considering the “environment-to-human” transmission and virus mutations of the novel coronavirus, the SEIQR model of infectious disease dynamics was established to simulate the development trend of the epidemic. The results showed that, the increased infectivity of virus variants and “environment-to-human” transmission positively affects the spread and speed of COVID-19 epidemic, in which the virus variants had a more significant impact, and the “environment-to-human” transmission will promote the outbreak time of the epidemic to be greatly advanced. For the virus variants with higher infectivity, elevating the intensity of interventions has a more remarkable effect on controlling the spread of COVID-19 variants.
Key wordsCOVID-19 (corona virus disease 2019)    virus variation    “environment-to-human” transmission    SEIQR (susceptible-exposed-infected- quarantine-removed)
收稿日期: 2021-01-28      出版日期: 2021-11-30
ZTFLH:  R563.1  
  R181.8  
基金资助:国家自然科学基金青年项目(72002153);全国统计科学研究项目(2019LY41);国家自然科学基金面上项目(41971249)
通讯作者: 宋敏(1997-),女,山西晋城人,硕士研究生,主要研究方向为复杂系统与复杂网络中传播动力学及相关传播模型。   
作者简介: 李稚(1980-),女,天津人,博士,副教授,主要研究方向为复杂系统优化与预测技术,人工智能与决策分析。
引用本文:   
李稚, 宋敏. 基于“病毒变异”和“环境传人”因素的COVID-19疫情传播动力学研究[J]. 复杂系统与复杂性科学, 2021, 18(4): 1-8.
LI Zhi, SONG Min. Transmission Dynamics of Coronavirus Disease 2019 Based on “Virus Variants” and “Environment-to-human”. Complex Systems and Complexity Science, 2021, 18(4): 1-8.
链接本文:  
http://fzkx.qdu.edu.cn/CN/10.13306/j.1672-3813.2021.04.001      或      http://fzkx.qdu.edu.cn/CN/Y2021/V18/I4/1
[1]World Health Organization. Press conferences on COVID-19 [EB/OL]. [2020-12-22]. https://www.who.int/emergencies/diseases/novel-coronavirus-2019.
[2]中国政府网. 国务院联防联控机制权威发布[EB/OL]. [2021-01-13]. http://www.gov.cn/xinwen/gwylflkjz145/mobile.htm.
[3]Pater A A, Bosmeny M S, Barkau C L, et al. Emergence and evolution of a prevalent new SARS-CoV-2 variant in the united states[DB/OL]. (2021-01-19)[2021-01-28]. http://www.biorxiv.org.cotent/10.1101/2021.01.11.
[4]Volz E, Mishra S, Chand M, et al. Assessing transmissibility of SARS-CoV-2 lineage B.1.1.7 in England[J]. Nature, 2021,593(1):266-269.
[5]环球网. 多地出现本土病例,警惕新冠病毒“环境传人”[EB/OL]. [2020-12-21]. https://3w.huanqiu.com/a/de583b/41BbiCxtKZ0.
Global Times. Multiole local cases occured, alerting to the “enviroment-to-human” transmission of novel coronavirus[EB/OL]. [2020-12-21]. https://3w.huanqiu.com/a/de583b/41BbiCxtKZ0.
[6]Liu P, Yang M, Zhao X, et al. Cold-chain transportation in the frozen food industry may have caused a recurrence of COVID-19 cases in destination: successful isolation of SARS-CoV-2 virus from the imported frozen cod package surface [J]. Biosafety and Health, 2020, 2(4): 199-201.
[7]人民日报的微博视频. 天津防疫发布会[EB/OL]. [2020-11-24]. https://weibo.com/tv/show/1042211:457486633081244 4?from=old_pc_videoshow.
People′s Daily Weibo Video. Press conference of the epidemic prevention of Tianjin [EB/OL]. [2020-11-24]. https://weibo.com/tv/show/1042211:457486633081244 4?from=old_pc_videoshow.
[8]Pang X, Ren L, Wu S, et al. Cold-chain food contamination as the possible origin of COVID-19 resurgence in Beijing [J]. National Science Review, 2020, 7(12): 1861-1864.
[9]Weissman G E, Crane-Droesch A, Chivers C, et al. Locally informed simulation to predict hospital capacity needs during the COVID-19 pandemic [J]. Annals of Internal Medicine, 2020, 173(1): 21-28.
[10] Zhou X, Wu Z, Yu R, et al. Modelling-based evaluation of the effect of quarantine control by the Chinese government in the coronavirus disease 2019 outbreak [J]. Science China Life Sciences, 2020, 63(8): 1257-1260.
[11] 王思远, 谭瀚霖, 李东杰. 基于改进传染病动力学易感-暴露-感染-恢复(SEIR)模型预测新型冠状病毒肺炎疫情[J]. 第二军医大学学报, 2020, 41(6): 637-641.
Wang Siyuan, Tan Hanlin, Li Dongjie. Coronavirus disease 2019 epidemic trend prediction based on improved infectious disease dynamics susceptible-exposed-infected-recovered (SEIR) model[J]. Academic Journal of Second Military Medical University, 2020, 41(6): 637-641.
[12] 严阅, 陈瑜, 刘可伋, 等. 基于一类时滞动力学系统对新型冠状病毒肺炎疫情的建模和预测[J]. 中国科学:数学, 2020, 50(3): 385-392.
Yan Yue, Chen Yu, Liu Keji, et al. Modeling and prediction for the trend of outbreak of NCP based on a time-delay dynamic system[J]. Scientia Sinica Mathematica, 2020, 50(3): 385-392.
[13] Chen Y, Cheng J, Jiang Y, et al. A time delay dynamical model for outbreak of 2019-nCoV and the parameter identification [J]. Journal of Inverse and Ill-posed Problems, 2020, 28(2): 243-250.
[14] Yang Z, Zeng Z, Wang K, et al. Modified SEIR and AI prediction of the epidemics trend of COVID-19 in China under public health interventions [J]. Journal of Thoracic Disease, 2020, 12(3): 165-174.
[15] Zu J, Li M L, Li Z F, et al. Transmission patterns of COVID-19 in the mainland of China and the efficacy of different control strategies: a data-and model-driven study [J]. Infectious Diseases of Poverty, 2020, 9(83): 1-14.
[16] Prem K, Liu Y, Russell T W, et al. The effect of control strategies to reduce social mixing on outcomes of the COVID-19 epidemic in Wuhan, China: a modelling study [J]. Lancet Public Health, 2020, 5(5): 261-270.
[17] Li Q, Guan X H, Wu P, et al. Early transmission dynamics in Wuhan, China, of novel coronavirus-infected pneumonia [J]. The New England Journal of Medicine, 2020, 382(13): 1199-1207.
[18] Chan J F-W, Yuan S F, Kok K-H, et al. A familial cluster of pneumonia associated with the 2019 novel coronavirus indicating person-to-person transmission: a study of a family cluster [J]. The Lancet, 2020, 395(10223): 514-523.
[19] 央视新闻微博. 专家回应无症状感染者传播[EB/OL]. [2021-01-13]. http://weibo.com/cctvxinwen?is_all=1&stat_date=2021011&page=20#feedtop.
CCTV New Weibo. Experts respond to the vival transmission in asymptomatic infected individuals[EB/OL]. [2021-01-13]. http://weibo.com/cctvxinwen?is_all=1&stat_date=2021011&page=20#feedtop.
[20] 大连市统计局,国家统计局大连调查队. 大连统计年鉴2019[M]. 北京: 中国统计出版社,2019.
[21] 曹盛力, 冯沛华, 时朋朋. 修正SEIR传染病动力学模型应用于湖北省2019冠状病毒病(COVID-19)疫情预测和评估[J]. 浙江大学学报(医学版), 2020, 49(2): 178-184.
Cao Shengli, Feng Peihua, Shi Pengpeng. Study on the epidemic development of corona virus disease-19 (COVID-19) in Hubei province by a modified SEIR model[J]. Journal of Zhejiang University (Medical Sciences), 2020, 49(2): 178-184.
[22] 王霞, 唐三一, 陈勇, 等. 新型冠状病毒肺炎疫情下武汉及周边地区何时复工? 数据驱动的网络模型分析[J]. 中国科学:数学, 2020, 50(7): 969-978.
Wang Xia, Tang Sanyi, Chen Yong, et al. When will be the resumption of work in Wuhan and its surrounding areas during COVID-19 epidemic? A data-driven network modeling analysis[J]. Scientia Sinica Mathematica, 2020, 50(7): 969-978.
[23] 武文韬, 李达宁, 李莉, 等. 基于SIR模型分析不同强度防控手段在当前武汉市新型冠状病毒(2019-nCoV)感染的肺炎疫情中的作用[J]. 医学新知, 2020, 30(1): 78-82.
Wu Wentao, Li Daning, Li Li, et al. Analysis of the role of different intensity prevention and control measures in the current epidemic of novel coronavirus (2019-nCoV) infected pneumonia in Wuhan based on SIR model[J]. New Medicine, 2020, 30(1): 78-82.
[24] 耿辉, 徐安定, 王晓艳, 等. 基于SEIR模型分析相关干预措施在新型冠状病毒肺炎疫情中的作用[J]. 暨南大学学报(自然科学与医学版), 2020, 41(2): 175-180.
Geng Hui, Xu Anding, Wang Xiaoyan, et al. Analysis of the role of current prevention and control measures in the epidemic of corona virus disease 2019 based on SEIR model[J]. Journal of Jinan University (Natural Science & Medicine Edition), 2020, 41(2): 175-180.
[25] 葛洪磊, 刘南. 重大传染病疫情演化情境下应急物资配置决策建模分析:以新冠肺炎疫情为例[J]. 管理工程学报, 2020, 34(3): 214-222.
Ge Honglei, Liu Nan. Modeling of emergency materials allocation decision-making problems based on the evolution scenarios of serious infectious disease: a case of COVID-19 [J]. Journal of Industrial Engineering/Engineering Management, 2020, 34(3): 214-222.
[26] 央视网. 新冠病毒出现“环境传人”如何应对?[EB/OL]. [2020-12-21]. https://news.cctv.com/2020/12/21/ARTIJGcRHu6PCbVjowPPAkGH201221.shtml.
CCTV. How to deal with the “environment-to-human” transmission of COVID-19?[EB/OL]. [2020-12-21]. https://news.cctv.com/2020/12/21/ARTIJGcRHu6PCbVjowPPAkGH201221.shtml.
No related articles found!
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed