Article(id=1281627220380729952, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1281627156769903305, articleNumber=null, orderNo=null, doi=10.16265/j.cnki.issn1003-3033.2026.01.0664, pmid=null, cstr=null, oa=null, hot=null, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1756483200000, receivedDateStr=2025-08-30, revisedDate=1761926400000, revisedDateStr=2025-11-01, acceptedDate=null, acceptedDateStr=null, onlineDate=1783493340820, onlineDateStr=2026-07-08, pubDate=1769529600000, pubDateStr=2026-01-28, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1783493340820, onlineIssueDateStr=2026-07-08, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1783493340820, creator=13701087609, updateTime=1783493340820, updator=13701087609, issue=Issue{id=1281627156769903305, tenantId=1146029695717560320, journalId=1146031787341344770, year='2026', volume='36', issue='1', pageStart='1', pageEnd='280', issueExtLink='null', onlineDate='null', pubDate='1769529600000', pubDateStr='2026-01-28', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1783493325654, creator='13701087609', updateTime=1783588714348, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1282027246013624992, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1281627156769903305, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1282027246013624993, tenantId=1146029695717560320, journalId=1146031787341344770, issueId=1281627156769903305, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=257, endPage=266, ext={EN=ArticleExt(id=1281627221722907233, articleId=1281627220380729952, tenantId=1146029695717560320, journalId=1146031787341344770, language=EN, title=Coupled transmission model of spatial infectious diseases and negative emotions based on multilayer networks, columnId=1149735805633081985, journalTitle=China Safety Science Journal, columnName=Occupational Health, runingTitle=null, highlight=null, articleAbstract=

To reveal the co-evolutionary relationship between disease transmission intensity and emotional diffusion rate, based on a two-layer complex network structure, this study integrated the classical Susceptible-Exposed-Infected-Recovered (SEIR) epidemic model with a five-state emotional dynamics framework (Se-Ee-Ie-Ge-Re) to construct a coupled dynamics model (SEIR-SeEeIeGeRe). Theoretical derivation and simulation validation were conducted using the microscopic Markov chain approach and Monte Carlo simulation. The findings reveal that although reducing the disease infection probability can mitigate the scale of emotional propagation, its inhibitory effect on the peak of emotional propagation remains limited. In contrast, shortening the disease incubation period and improving the recovery rate significantly regulate the spread of negative emotions, exhibiting a two-stage propagation pattern characterized by emotional metabolic hysteresis and the density threshold effect of emotional guides. Furthermore, enhancing individuals' compliance with epidemic preventive measures can effectively delay the spread and reduce the scale of negative emotions through three pathways: blocking transmission chains, reinforcing social norms, and correcting cognitive biases.

, authors=Tiantian WANG1, Haiyun MA1, Zhirong WANG1, Tiezhong LIU**, 2, Xiaohan YAN3, authorsList=Tiantian WANG, Haiyun MA, Zhirong WANG, Tiezhong LIU, Xiaohan YAN, authorCompany=null, correspAuthors=Tiezhong LIU, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1281627222259778148, articleId=1281627220380729952, tenantId=1146029695717560320, journalId=1146031787341344770, language=CN, title=基于多层网络的传染病与负面情绪耦合传播模型, columnId=1281608104106242978, journalTitle=中国安全科学学报, columnName=职业健康, runingTitle=null, highlight=null, articleAbstract=

为揭示疾病传播强度与情绪扩散速率的协同演化关系,基于双层复杂网络结构,将经典易感-潜伏-感染-免疫(SEIR)模型与情绪传播的5状态动力学框架(Se-Ee-Ie-Ge-Re)相融合,构建耦合动力学模型(SEIR-SeEeIeGeRe),并采用微观马尔可夫链(MMC)与蒙特卡罗(MC)法仿真进行理论推演与仿真验证。研究结果表明:降低传染病感染概率虽可降低情绪传播规模,但对情绪传播高峰的抑制作用有限;而缩短传染病潜伏期与提高治愈率,可显著调控负面情绪传播,呈现情绪代谢迟滞效应与情绪引导者密度阈值效应的双阶段传播特征。此外,提高个体防疫配合度可通过阻断传播链、强化社会规范与矫正认知偏差3条路径实现,有效延缓负面情绪扩散并缩小其规模。

, authors=王甜甜讲师1, 马海韵教授1, 王志荣教授1, 刘铁忠教授**, 2, 闫晓涵讲师3, authorsList=王甜甜讲师, 马海韵教授, 王志荣教授, 刘铁忠教授, 闫晓涵讲师, authorCompany=null, correspAuthors=刘铁忠教授, authorNote=

王甜甜(1994—),女,山东德州人,博士,讲师,主要从事风险分析与应急管理等方面的研究。E-mail:

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** 刘铁忠(1974—),男,黑龙江海伦人,博士,教授,主要从事风险分析与危机管理方面的研究。E-mail:
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王甜甜(1994—),女,山东德州人,博士,讲师,主要从事风险分析与应急管理等方面的研究。E-mail:

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王甜甜(1994—),女,山东德州人,博士,讲师,主要从事风险分析与应急管理等方面的研究。E-mail:

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基于多层网络的传染病与负面情绪耦合传播模型
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王甜甜讲师 1 , 马海韵教授 1 , 王志荣教授 1 , 刘铁忠教授 **, 2 , 闫晓涵讲师 3
中国安全科学学报 | 职业健康 2026,36(1): 257-266
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中国安全科学学报 |职业健康 2026 , 36 (1) : 257 -266
基于多层网络的传染病与负面情绪耦合传播模型
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王甜甜(1994—),女,山东德州人,博士,讲师,主要从事风险分析与应急管理等方面的研究。E-mail:

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王甜甜讲师1 , 马海韵教授1, 王志荣教授1, 刘铁忠教授**, 2 , 闫晓涵讲师3
作者信息
  • 1南京工业大学 应急管理学院,江苏 南京 211816
  • 2北京理工大学 管理学院,北京 100081
  • 3河北经贸大学 金融学院,河北 石家庄 050061
通讯作者:
** 刘铁忠(1974—),男,黑龙江海伦人,博士,教授,主要从事风险分析与危机管理方面的研究。E-mail:
作者简介:

王甜甜(1994—),女,山东德州人,博士,讲师,主要从事风险分析与应急管理等方面的研究。E-mail:

Coupled transmission model of spatial infectious diseases and negative emotions based on multilayer networks
Tiantian WANG1 , Haiyun MA1, Zhirong WANG1, Tiezhong LIU**, 2 , Xiaohan YAN3
Affiliations
  • 1School of Emergency Management, Nanjing Tech University, Nanjing Jiangsu 211816, China
  • 2School of Management, Beijing University of Technology, Beijing 100081, China
  • 3School of Finance, Hebei University of Economics and Business, Shijiazhuang Hebei 050061, China
出版时间: 2026-01-28 doi: 10.16265/j.cnki.issn1003-3033.2026.01.0664
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为揭示疾病传播强度与情绪扩散速率的协同演化关系,基于双层复杂网络结构,将经典易感-潜伏-感染-免疫(SEIR)模型与情绪传播的5状态动力学框架(Se-Ee-Ie-Ge-Re)相融合,构建耦合动力学模型(SEIR-SeEeIeGeRe),并采用微观马尔可夫链(MMC)与蒙特卡罗(MC)法仿真进行理论推演与仿真验证。研究结果表明:降低传染病感染概率虽可降低情绪传播规模,但对情绪传播高峰的抑制作用有限;而缩短传染病潜伏期与提高治愈率,可显著调控负面情绪传播,呈现情绪代谢迟滞效应与情绪引导者密度阈值效应的双阶段传播特征。此外,提高个体防疫配合度可通过阻断传播链、强化社会规范与矫正认知偏差3条路径实现,有效延缓负面情绪扩散并缩小其规模。

多层网络  /  负面情绪  /  传染病  /  耦合传播模型  /  微观马尔可夫链(MMC)

To reveal the co-evolutionary relationship between disease transmission intensity and emotional diffusion rate, based on a two-layer complex network structure, this study integrated the classical Susceptible-Exposed-Infected-Recovered (SEIR) epidemic model with a five-state emotional dynamics framework (Se-Ee-Ie-Ge-Re) to construct a coupled dynamics model (SEIR-SeEeIeGeRe). Theoretical derivation and simulation validation were conducted using the microscopic Markov chain approach and Monte Carlo simulation. The findings reveal that although reducing the disease infection probability can mitigate the scale of emotional propagation, its inhibitory effect on the peak of emotional propagation remains limited. In contrast, shortening the disease incubation period and improving the recovery rate significantly regulate the spread of negative emotions, exhibiting a two-stage propagation pattern characterized by emotional metabolic hysteresis and the density threshold effect of emotional guides. Furthermore, enhancing individuals' compliance with epidemic preventive measures can effectively delay the spread and reduce the scale of negative emotions through three pathways: blocking transmission chains, reinforcing social norms, and correcting cognitive biases.

multilayer networks  /  negative emotion  /  infectious disease  /  coupling spreading model  /  Micro-Markov chain (MMC)
王甜甜讲师, 马海韵教授, 王志荣教授, 刘铁忠教授, 闫晓涵讲师. 基于多层网络的传染病与负面情绪耦合传播模型. 中国安全科学学报, 2026 , 36 (1) : 257 -266 . DOI: 10.16265/j.cnki.issn1003-3033.2026.01.0664
Tiantian WANG, Haiyun MA, Zhirong WANG, Tiezhong LIU, Xiaohan YAN. Coupled transmission model of spatial infectious diseases and negative emotions based on multilayer networks[J]. China Safety Science Journal, 2026 , 36 (1) : 257 -266 . DOI: 10.16265/j.cnki.issn1003-3033.2026.01.0664
  • 国家社科基金资助(21BGL299)
  • 江苏省哲学社会科学联合会项目(23SSL133)
  • 江苏高校哲学社会科学研究一般项目(2025SJYB0169)
  • 教育部人文社会科学青年基金项目(25YCZH260)
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doi: 10.16265/j.cnki.issn1003-3033.2026.01.0664
  • 接收时间:2025-08-30
  • 首发时间:2026-07-08
  • 出版时间:2026-01-28
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  • 收稿日期:2025-08-30
  • 修回日期:2025-11-01
基金
国家社科基金资助(21BGL299)
江苏省哲学社会科学联合会项目(23SSL133)
江苏高校哲学社会科学研究一般项目(2025SJYB0169)
教育部人文社会科学青年基金项目(25YCZH260)
作者信息
    1南京工业大学 应急管理学院,江苏 南京 211816
    2北京理工大学 管理学院,北京 100081
    3河北经贸大学 金融学院,河北 石家庄 050061

通讯作者:

** 刘铁忠(1974—),男,黑龙江海伦人,博士,教授,主要从事风险分析与危机管理方面的研究。E-mail:
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https://castjournals.cast.org.cn/joweb/zgaqkxxb/CN/10.16265/j.cnki.issn1003-3033.2026.01.0664
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2种不同金属材料的力学参数

Family
属数
Number of
genus
种数
Number of
species
占总种数比例
Percentage of
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Genus
种数
Number of
species
占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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