Among many epidemic models, one epidemic disease may transmit with the existence of other pathogens or other strains from the same pathogen. In this paper, we consider the case where all of the strains obey the suscep...Among many epidemic models, one epidemic disease may transmit with the existence of other pathogens or other strains from the same pathogen. In this paper, we consider the case where all of the strains obey the susceptible-infected- susceptible mechanism and compete with each other at the expense of common susceptible individuals. By using the heterogenous mean-field approach, we discuss the epidemic threshold for one of two strains. We confirm the existence of epidemic threshold in both finite and infinite populations subject to underlying epidemic transmission. Simulations in the Barabasi-Albert （BA） scale-free networks are in good agreement with the analytical results.展开更多
The control of highly contagious disease spreading in campuses is a critical challenge.In residential universities,students attend classes according to a curriculum schedule,and mainly pack into classrooms,dining hall...The control of highly contagious disease spreading in campuses is a critical challenge.In residential universities,students attend classes according to a curriculum schedule,and mainly pack into classrooms,dining halls and dorms.They move from one place to another.To simulate such environments,we propose an agent-based susceptible–infected–recovered model with time-varying heterogeneous contact networks.In close environments,maintaining physical distancing is the most widely recommended and encouraged non-pharmaceutical intervention.It can be easily realized by using larger classrooms,adopting staggered dining hours,decreasing the number of students per dorm and so on.Their real-world influence remains uncertain.With numerical simulations,we obtain epidemic thresholds.The effect of such countermeasures on reducing the number of disease cases is also quantitatively evaluated.展开更多
Models for diseases spreading are not just limited to SIS or SIR. For instance, for the spreading of AIDS/HIV, the susceptible individuals can be classified into different cases according to their immunity, and simila...Models for diseases spreading are not just limited to SIS or SIR. For instance, for the spreading of AIDS/HIV, the susceptible individuals can be classified into different cases according to their immunity, and similarly, the infected individuals can be sorted into different classes according to their infectivity. Moreover, some diseases may develop through several stages. Many authors have shown that the individuals＇ relation can be viewed as a complex network. So in this paper, in order to better explain the dynamical behavior of epidemics, we consider different epidemic models on complex networks, and obtain the epidemic threshold for each ease. Finally, we present numerical simulations for each case to verify our results.展开更多
In this paper, a dynamic epidemic control model on the uncorrelated complex networks is proposed. By means of theoretical analysis, we found that the new model has a similar epidemic threshold as that of the susceptib...In this paper, a dynamic epidemic control model on the uncorrelated complex networks is proposed. By means of theoretical analysis, we found that the new model has a similar epidemic threshold as that of the susceptible-infectedrecovered （SIR） model on the above networks, but it can reduce the prevalence of the infected individuals remarkably. This result may help us understand epidemic spreading phenomena on real networks and design appropriate strategies to control infections.展开更多
In this paper, we study the dynamical behaviour of an epidemic on complex networks with population mobility. In our model, the number of people on each node is unrestricted as the nodes of the network are considered a...In this paper, we study the dynamical behaviour of an epidemic on complex networks with population mobility. In our model, the number of people on each node is unrestricted as the nodes of the network are considered as cities, communities, and so on. Because people can travel between different cities, we study the effect of a population＇s mobility on the epidemic spreading. In view of the population＇s mobility, we suppose that the susceptible individual can be infected by an infected individual in the same city or other connected cities. Simulations are presented to verify our analysis.展开更多
In this paper, a new susceptible-infected-susceptible （SIS） model on complex networks with imperfect vaccination is proposed. Two types of epidemic spreading patterns （the recovered individuals have or have not imm...In this paper, a new susceptible-infected-susceptible （SIS） model on complex networks with imperfect vaccination is proposed. Two types of epidemic spreading patterns （the recovered individuals have or have not immunity） on scale-free networks are discussed. Both theoretical and numerical analyses are presented. The epidemic thresholds related to the vaccination rate, the vaccination-invalid rate and the vaccination success rate on scale-free networks are demonstrated, showing different results from the reported observations. This reveals that whether or not the epidemic can spread over a network under vaccination control is determined not only by the network structure but also by the medicine＇s effective duration. Moreover, for a given infective rate, the proportion of individuals to vaccinate can be calculated theoretically for the case that the recovered nodes have immunity. Finally, simulated results are presented to show how to control the disease prevalence.展开更多
This paper presents a modified susceptible-infected-recovered（SIR） model with the effects of awareness and vaccination to study the epidemic spreading on scale-free networks based on the mean-field theory.In this mo...This paper presents a modified susceptible-infected-recovered（SIR） model with the effects of awareness and vaccination to study the epidemic spreading on scale-free networks based on the mean-field theory.In this model,when susceptible individuals receive awareness from their infected neighbor nodes,they will take vaccination measures.The theoretical analysis and the numerical simulations show that the existence of awareness and vaccination can significantly improve the epidemic threshold and reduce the risk of virus outbreaks.In addition,regardless of the existence of vaccination,the awareness can increase the spreading threshold and slow the spreading speed effectively.For a given awareness and a certain spreading rate,the total number of infections reduces with the increasing vaccination rate.展开更多
We have studied the topology and epidemic spreading behaviors on the networks in which deactivation mechanism and long-rang connection are coexisted.By means of numerical simulation,we find that the clustering coeffic...We have studied the topology and epidemic spreading behaviors on the networks in which deactivation mechanism and long-rang connection are coexisted.By means of numerical simulation,we find that the clustering coefficient C and the Pearson correlation coefficient r decrease with increasing long-range connectionμand the topological state of the network changes into that of BA model at the end(whenμ=1).For the Susceptible-Infect-Susceptible model of epidemics,the epidemic threshold can reach maximum value atμ=0.4 and presents two different variable states aroundμ=0.4.展开更多
This paper analyzes the dynamics of a two-strain symbiotic contact process on graphs using a discrete-time nonlinear dynamical system framework.Our study focuses on the coexistence problem,examining how different netw...This paper analyzes the dynamics of a two-strain symbiotic contact process on graphs using a discrete-time nonlinear dynamical system framework.Our study focuses on the coexistence problem,examining how different network topologies and co-infection dynamics affect the spread and persistence of both strains.We derive infection probabilities for each strain over time and demonstrate that the survival of the epidemic requires the epidemic threshold S>1 for at least one strain.This condition is shown to be necessary for the sustained propagation of the epidemic.Our findings provide insights into the role of symbiosis in multi-strain epidemic models on complex networks.展开更多
基金supported by the National Natural Science Foundation of China (Grant No. 11072136)the Shanghai Leading Academic Discipline Project,China (Grant No. S30104)
文摘Among many epidemic models, one epidemic disease may transmit with the existence of other pathogens or other strains from the same pathogen. In this paper, we consider the case where all of the strains obey the susceptible-infected- susceptible mechanism and compete with each other at the expense of common susceptible individuals. By using the heterogenous mean-field approach, we discuss the epidemic threshold for one of two strains. We confirm the existence of epidemic threshold in both finite and infinite populations subject to underlying epidemic transmission. Simulations in the Barabasi-Albert （BA） scale-free networks are in good agreement with the analytical results.
基金Project supported by the National Natural Science Foundation of China(Grant No.61871234).
文摘The control of highly contagious disease spreading in campuses is a critical challenge.In residential universities,students attend classes according to a curriculum schedule,and mainly pack into classrooms,dining halls and dorms.They move from one place to another.To simulate such environments,we propose an agent-based susceptible–infected–recovered model with time-varying heterogeneous contact networks.In close environments,maintaining physical distancing is the most widely recommended and encouraged non-pharmaceutical intervention.It can be easily realized by using larger classrooms,adopting staggered dining hours,decreasing the number of students per dorm and so on.Their real-world influence remains uncertain.With numerical simulations,we obtain epidemic thresholds.The effect of such countermeasures on reducing the number of disease cases is also quantitatively evaluated.
基金Supported by the Foundation of Anhui Education Bureau under Grant No.KJ2007A003the Natural Science Foundation of Anhui,China under Grant No.070416225+2 种基金a Grant from the Health,Welfare and Food Bureau of the Hong Kong SAR GovernmentNSFC under Grant No.10672146supported by Shanghai Leading Academic Discipline Project,Project Number:S30104
文摘Models for diseases spreading are not just limited to SIS or SIR. For instance, for the spreading of AIDS/HIV, the susceptible individuals can be classified into different cases according to their immunity, and similarly, the infected individuals can be sorted into different classes according to their infectivity. Moreover, some diseases may develop through several stages. Many authors have shown that the individuals＇ relation can be viewed as a complex network. So in this paper, in order to better explain the dynamical behavior of epidemics, we consider different epidemic models on complex networks, and obtain the epidemic threshold for each ease. Finally, we present numerical simulations for each case to verify our results.
基金Project supported by the National Natural Science Foundation of China (Grant No.60774088)the Program for New Century Excellent Talents of Higher Education of China (Grant No NCET 2005-290)the Special Research Fund for the Doctoral Program of Higher Education of China (Grant No 20050055013)
文摘In this paper, a dynamic epidemic control model on the uncorrelated complex networks is proposed. By means of theoretical analysis, we found that the new model has a similar epidemic threshold as that of the susceptible-infectedrecovered （SIR） model on the above networks, but it can reduce the prevalence of the infected individuals remarkably. This result may help us understand epidemic spreading phenomena on real networks and design appropriate strategies to control infections.
基金supported by National Natural Science Foundation of China (Grant Nos 60744003,10635040,10532060 and 10672146)the Specialized Research Fund for the Doctoral Program of Higher Education of China (Grant No 20060358065)+2 种基金National Science Fund for Fostering Talents in Basic Science (Grant No J0630319)A grant from the Health,Welfare and Food Bureau of the Hong Kong SAR GovernmentShanghai Leading Academic Discipline Project (Project Number:J50101)
文摘In this paper, we study the dynamical behaviour of an epidemic on complex networks with population mobility. In our model, the number of people on each node is unrestricted as the nodes of the network are considered as cities, communities, and so on. Because people can travel between different cities, we study the effect of a population＇s mobility on the epidemic spreading. In view of the population＇s mobility, we suppose that the susceptible individual can be infected by an infected individual in the same city or other connected cities. Simulations are presented to verify our analysis.
基金supported by the National Natural Science Foundation of China (Grant Nos 60674093,10832006)the Hong Kong Research Grants Council under Grant CityU 1117/08E
文摘In this paper, a new susceptible-infected-susceptible （SIS） model on complex networks with imperfect vaccination is proposed. Two types of epidemic spreading patterns （the recovered individuals have or have not immunity） on scale-free networks are discussed. Both theoretical and numerical analyses are presented. The epidemic thresholds related to the vaccination rate, the vaccination-invalid rate and the vaccination success rate on scale-free networks are demonstrated, showing different results from the reported observations. This reveals that whether or not the epidemic can spread over a network under vaccination control is determined not only by the network structure but also by the medicine＇s effective duration. Moreover, for a given infective rate, the proportion of individuals to vaccinate can be calculated theoretically for the case that the recovered nodes have immunity. Finally, simulated results are presented to show how to control the disease prevalence.
基金Project supported by the National Natural Science Foundation of China (Grant No. 60874091)the Six Projects Sponsoring Talent Summits of Jiangsu Province,China (Grant No. SJ209006)+1 种基金the Natural Science Foundation of Jiangsu Province,China (Grant No. BK2010526)the Graduate Student Innovation Research Program of Jiangsu Province,China (Grant No. CXLX11 0414)
文摘This paper presents a modified susceptible-infected-recovered（SIR） model with the effects of awareness and vaccination to study the epidemic spreading on scale-free networks based on the mean-field theory.In this model,when susceptible individuals receive awareness from their infected neighbor nodes,they will take vaccination measures.The theoretical analysis and the numerical simulations show that the existence of awareness and vaccination can significantly improve the epidemic threshold and reduce the risk of virus outbreaks.In addition,regardless of the existence of vaccination,the awareness can increase the spreading threshold and slow the spreading speed effectively.For a given awareness and a certain spreading rate,the total number of infections reduces with the increasing vaccination rate.
文摘We have studied the topology and epidemic spreading behaviors on the networks in which deactivation mechanism and long-rang connection are coexisted.By means of numerical simulation,we find that the clustering coefficient C and the Pearson correlation coefficient r decrease with increasing long-range connectionμand the topological state of the network changes into that of BA model at the end(whenμ=1).For the Susceptible-Infect-Susceptible model of epidemics,the epidemic threshold can reach maximum value atμ=0.4 and presents two different variable states aroundμ=0.4.
基金supported by the Mathematics for Sustainable Development(MATH4SDG)project,which is a research and development project running in the period 2021-2026 at Makerere University-Uganda,University of Dar es Salaam-Tanzania,and the University of Bergen-Norway.
文摘This paper analyzes the dynamics of a two-strain symbiotic contact process on graphs using a discrete-time nonlinear dynamical system framework.Our study focuses on the coexistence problem,examining how different network topologies and co-infection dynamics affect the spread and persistence of both strains.We derive infection probabilities for each strain over time and demonstrate that the survival of the epidemic requires the epidemic threshold S>1 for at least one strain.This condition is shown to be necessary for the sustained propagation of the epidemic.Our findings provide insights into the role of symbiosis in multi-strain epidemic models on complex networks.
