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Chinese Physics B 2024年第3期33卷 690-699页

作者：谢笑笑霍良安董雅芳程英英 Business School University of Shanghai for Science and TechnologyShanghai 200093China School of Intelligent Emergency Management University of Shanghai for Science and TechnologyShanghai 200093China School of Management Henan University of Science and TechnologyLuoyang 471023China

While the interaction between information and disease in static networks has been extensively investigated,many studies have ignored the characteristics of network *** this study,we construct a new two-layer coupling model to explore the interactions between information and *** upper layer describes the diffusion of disease-related information,and the lower layer represents the disease *** then use power-law distributions to examine the influence of asymmetric activity levels on dynamic propagation,revealing a mapping relationship characterizing the interconnected propagation of information and diseases among partial nodes within the ***,we derive the disease outbreak threshold by using the microscopic Markov-chain approach(MMCA).Finally,we perform extensive Monte Carlo(MC)numerical simulations to verify the accuracy of our theoretical *** findings indicate that the activity levels of individuals in the disease transmission layer have a more significant influence on disease transmission compared with the individual activity levels in the information diffusion ***,reducing the damping factor can delay disease outbreaks and suppress disease transmission,while improving individual quarantine measures can contribute positively to disease *** study provides valuable insights into policymakers for developing outbreak prevention and control strategies.

关键词： information diffusion disease transmission asymmetric activity levels quarantine strength

Studying the co-evolution of information diffusion,vaccination behavior and disease transmission in multilayer networks with local and global effects

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Chinese Physics B 2024年第3期33卷 677-689页

作者：霍良安武兵杰 Business School University of Shanghai for Science and TechnologyShanghai 200093China School of Intelligent Emergency Management University of Shanghai for Science and TechnologyShanghai 200093China

Today,with the rapid development of the internet,a large amount of information often accompanies the rapid transmission of disease outbreaks,and increasing numbers of scholars are studying the relationship between information and the disease transmission process using complex *** fact,the disease transmission process is very *** this information,there will often be individual behavioral measures and other factors to *** of the previous research has aimed to establish a two-layer network model to consider the impact of information on the transmission process of disease,rarely divided into information and behavior,*** carry out a more in-depth analysis of the disease transmission process and the intrinsic influencing mechanism,this paper divides information and behavior into two layers and proposes the establishment of a complex network to study the dynamic co-evolution of information diffusion,vaccination behavior,and disease *** is achieved by considering four influential relationships between adjacent layers in multilayer *** the information layer,the diffusion process of negative information is described,and the feedback effects of local and global vaccination are *** the behavioral layer,an individual's vaccination behavior is described,and the probability of an individual receiving a vaccination is influenced by two factors:the influence of negative information,and the influence of local and global disease *** the disease layer,individual susceptibility is considered to be influenced by vaccination *** state transition equations are derived using the micro Markov chain approach(MMCA),and disease prevalence thresholds are *** is demonstrated through simulation experiments that the negative information diffusion is less influenced by local vaccination behavior,and is mainly influenced by global vaccination behavior;vaccination behavior is mainly influenced by local d

关键词： information diffusion vaccination behavior disease transmission multilayer networks local and global effect

Prediction of disease transmission Risk in Universities Based on SEIR and Multi-hidden Layer Back-propagation Neural Network Model

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IJLAI Transactions on Science and Engineering

IJLAI Transactions on Science and Engineering 2024年第1期2卷 24-31页

作者： Jiangjiang Li Lijuan Feng School of Electronic and Electrical Engineering Zhengzhou University of Science and TechnologyZhengzhou 450064 China

Against the background of regular epidemic prevention and control,in order to ensure the return of teachers to work,students to return to school and safe operation of schools,the risk of disease transmission is analyzed in key areas such as university canoons,auditoriums,teaching buildings and *** risk model of epidemic transmission in key regions of universities is established based on the improved SEIR model,considering the four groups of people,namely susceptible,latent,infected and displaced,and their mutual transformation *** feature post-processing,the selected feature parameters are processed with monotone non-decreasing and smoothing,and used as noise-free samples of stacked sparse denoising automatic coding network to train the ***,the feature vectors after dimensionality reduction of the stacked sparse denoising automatic coding network are used as the input of the multi-hidden layer back-propagation neural network,and these features are used as tags to carry out fitting training for the *** results show that the implementation of control measures can reduce the number of contacts between infected people and susceptible people,reduce the transmission rate of single contact,and reduce the peak number of infected people and latent people by 61%and 72%respectively,effectively controlling the disease spread in key regions of *** method is able to accurately predict the number of infections.

关键词： disease transmission SEIR model Prediction Stacked sparse denoising automatic coding network

Impact of asymmetric activity on interactions between information diffusion and disease transmission in multiplex networks

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理论物理通讯:英文版 2023年第7期75卷 1-14页

作者： Xiaoxiao Xie Liang’an Huo Laijun Zhao Ying Qian Business School University of Shanghai for Science and TechnologyShanghai 200093China

disease is a serious threat to human *** the characteristics of disease transmission is helpful for people to effectively control *** real life,it is natural to take various measures when people are aware of *** this paper,a novel coupled model considering asymmetric activity is proposed to describe the interactions between information diffusion and disease transmission in multiplex ***,the critical threshold for disease transmission is derived by using the micro-Markov chain ***,the theoretical results are verified by numerical *** results show that reducing the activity level of individuals in the physical contact layer will have a continuous impact on reducing the disease outbreak threshold and suppressing the *** addition,the activity level of individuals in the virtual network has little impact on the transmission of the ***,when individuals are aware of more disease-related information,the higher their awareness of prevention will be,which can effectively inhibit the transmission of *** research results can provide a useful reference for the control of disease transmission.

关键词： asymmetric activity information diffusion disease transmission activity level multiplex networks

The effect of changing COVID-19 restrictions on the transmission rate in a veterinary clinic

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Infectious disease Modelling 2023年第1期8卷 294-308页

作者： Lee Spence David E.Anderson Ibrahim Halil Aslan Mahir Demir Chika C.Okafor Marcy Souza Suzanne Lenhart Department of Mathematics University of TennesseeKnoxvilleTNUSA Department of Large Animal Clinical Sciences College of Veterinary MedicineUniversity of TennesseeKnoxvilleTNUSA Hopkins Marine Station Stanford Doerr School of SustainabilityUSA Department of Mathematics Giresun UniversityGiresunTurkey Department of Biomedical and Diagnostic Sciences College of Veterinary MedicineUniversity of TennesseeKnoxvilleTNUSA

With the declaration of the COVID-19 pandemic by the World Health Organization on March 11,2020,the University of Tennessee College of Veterinary Medicine(UTCVM),like other institutions,restructured their services to reduce the potential spread of the COVID-19 virus while simultaneously providing critical and essential veterinary services.A mathematical model was developed to predict the change in the level of possible COVID-19 infections due to the increased number of potential contacts within the UTCVM hospital.A system of ordinary differential equations with different compartments for UTCVM individuals and the Knox county population was formulated to show the dynamics of transmission and the number of confirmed *** transmission rates in the model were estimated using COVID-19 case data from the surrounding county and UTCVM *** from this model show the increasing number of COVID-19 cases among UTCVM personnel as the number of daily clients and the number of veterinary staff in the clinic are *** also investigate how changes within the Knox county community impact the UTCVM *** scenarios show the importance of understanding the effects of re-opening scenarios in veterinary teaching hospitals.

关键词： Veterinary teaching hospital COVID-19 Mathematical model disease transmission

Revisiting classical SIR modelling in light of the COVID-19 pandemic

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Infectious disease Modelling 2023年第1期8卷 72-83页

作者： Leonid Kalachev Erin L.Landguth Jon Graham Mathematical Sciences University of MontanaMissoulaUSA Center for Population Health Research School of Public and Community Health SciencesUniversity of MontanaMissoulaUSA

Background:Classical infectious disease models during epidemics have widespread usage,from predicting the probability of new infections to developing vaccination plans for informing policy decisions and public health ***,it is important to correctly classify reported data and understand how this impacts estimation of model *** COVID-19 pandemic has provided an abundant amount of data that allow for thorough testing of disease modelling assumptions,as well as how we think about classical infectious disease modelling ***:We aim to assess the appropriateness of model parameter estimates and preiction results in classical infectious disease compartmental modelling frameworks given available data types(infected,active,quarantined,and recovered cases)for situations where just one data type is available to fit the *** main focus is on how model prediction results are dependent on data being assigned to the right model ***:We first use simulated data to explore parameter reliability and prediction capability with three formulations of the classical Susceptible-Infected-Removed(SIR)modelling *** then explore two applications with reported data to assess which data and models are sufficient for reliable model parameter estimation and prediction accuracy:a classical influenza outbreak in a boarding school in England and COVID-19 data from the fall of 2020 in Missoula County,Montana,***:We demonstrated the magnitude of parameter estimation errors and subsequent prediction errors resulting from data misclassification to model compartments with simulated *** showed that prediction accuracy in each formulation of the classical disease modelling framework was largely determined by correct data classification versus *** a classical example of influenza epidemics in an England boarding school,we argue that the Susceptible-Infected-Quarantined-Recovered(SIQR)model is more appropriat

关键词： Basic disease reproduction number Communicable disease control Coronavirus COVID-19 disease transmission Epidemics Epidemiology Influenza data Mathematical models Montana SIR models

Risk assessment of hepatitis E transmission through tissue allografts

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World Journal of Gastrointestinal Pathophysiology 2022年第2期13卷 50-58页

作者： Rafael Villalba Vicente Mirabet Center for Blood Transfusion Tissues and CellsCórdoba 14004Spain Cell and Tissue Bank Centro de Transfusión de ValenciaValencia 46014Spain

Hepatitis E virus(HEV)is a small non-enveloped single stranded RNA virus whose genotypes 3 and 4 have been associated with zoonotic transmission in industrialized *** infection is considered the main cause of acute hepatitis *** some cases,transfusion of blood components or organ transplantation have been reported as the source of *** have conducted a literature review on the risk of transmission through cell and tissue *** no case was found,measures to control this risk should be taken when donor profile(based upon geographical and behavioural data)recommended *** to be considered in donor screening and tissue processing to assess and to reduce the risk of HEV transmission are approached.

关键词： Hepatitis E Tissue allograft Risk assessment disease transmission Donor screening Bioburden reduction

Effect of multiple delays on the dynamics of cannibalistic prey-predator system with disease in both populations

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International Journal of Biomathematics 2017年第4期10卷 77-122页

作者： Santosh Biswas Sudip Samanta Qamar J. A. Khan Joydev Chattopadhyayt Department of Mathematics Jadavpur University188 Raja S. C. Mallik Road Kolkata 700032 India Agricultural and Ecological Research Unit Indian Statistical Institute 203 B. T. Road Kolkata 700108 India Department of Mathematics and Statistics Sultan Qaboos University P. O. Box 36 P. C. 123 Al-Khod Oman

In the present paper, we investigate a prey-predator system with disease in both prey and predator populations and the predator population is cannibalistic in nature. The model is extended by introducing incubation delays in disease transmission terms. Local stability analysis of the system around the biologically feasible equilibria is studied, The bifurcation analysis of the system around the interior equilibrium is also studied, The sufficient conditions for the permanence of the system are derived in the presence of delays. We observe that incubation delays have the ability to destabilize the cannibalistic prey-predator system. Finally, we perform numerical experiments to substantiate our analytical findings.

关键词： Cannibalism disease transmission incubation delay persistence Hopf bifur-cation.

Optimal control analysis of Ebola disease with control strategies of quarantine and vaccination

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Infectious diseases of Poverty 2016年第1期5卷 648-659页

作者： Muhammad Dure Ahmad Muhammad Usman Adnan Khan Mudassar Imran Department of Mathematics Prince Sultan UniversityRiyadhKingdom of Saudi Arabia Department of Mathematics University of DaytonDaytonOHUSA Department of Mathematics Lahore University of Management SciencesLahorePakistan Department of Mathematics and Natural Sciences GULF University for Science and TechnologyMishrefKuwait

Background:The 2014 Ebola epidemic is the largest in history,affecting multiple countries in West *** isolated cases were also observed in other regions of the ***:In this paper,we introduce a deterministic SEIR type model with additional hospitalization,quarantine and vaccination components in order to understand the disease *** control strategies,both in the case of hospitalization(with and without quarantine)and vaccination are used to predict the possible future outcome in terms of resource utilization for disease control and the effectiveness of vaccination on sick ***,with the help of uncertainty and sensitivity analysis we also have identified the most sensitive parameters which effectively contribute to change the disease *** have performed mathematical analysis with numerical simulations and optimal control strategies on Ebola virus ***:We used dynamical system tools with numerical simulations and optimal control strategies on our Ebola virus *** original model,which allowed transmission of Ebola virus via human contact,was extended to include imperfect vaccination and *** the qualitative analysis of all three forms of Ebola model,numerical techniques,using MATLAB as a platform,were formulated and analyzed in *** simulation results support the claims made in the qualitative ***:Our model incorporates an important component of individuals with high risk level with exposure to disease,such as front line health care workers,family members of EVD patients and Individuals involved in burial of deceased EVD patients,rather than the general population in the affected *** analysis suggests that in order for R0(i.e.,the basic reproduction number)to be less than one,which is the basic requirement for the disease elimination,the transmission rate of isolated individuals should be less than one-fourth of that for non-isolated *** analysis also predicts,

关键词： Epidemiology Ebola virus disease Optimal control strategies disease transmission

Spatial transmission of avian influenza (type H5) in birds

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Integrative Zoology 2009年第4期4卷 418-425页

作者： Xinhai LI Xiaoming LIU Lei XU Zhibin ZHANG State Key Laboratory of Integrated Pest Management on Pest Insects and Rodents Institute of ZoologyChinese Academy of SciencesBeijingChina

Highly pathogenic avian influenza(HPAI)H5N1 continues to threaten domestic and wild birds,as well as human ***,the mechanism of spatial transmission of HPAI is still *** analyzed the current distribu-tion of HPAI occurrences based on World Organization for Animal Health reported data from 3049 sites in the world from December 2003 to June 2006,and found that these sites were spaced at distances with a frequency peak of 100–200 *** built a cellular automata model to simulate the spatial transmission process of HPAI as a function of transmission distance,variance of the transmission distance,infection rate,and transmission times(how many times HPAI transmits from one host to another before suppression).We determined that the transmis-sion distance between HPAI occurrences is approximately 100 km on the basis of historical HPAI occurrences from 2003 to 2006 in both wild and domestic *** effectively reduce the long-distance spreading of HPAI,preventing close contact between domestic birds and waterfowl within a radius of 100 km around HPAI occur-rence sites is essential.

关键词： avian influenza birds cellular automata model disease transmission H5N1.