This paper investigates epidemic dynamics over dynamic networks via the approach of semi-tensor product of matrices. First, a formal susceptible-infected-susceptible epidemic dynamic model over dynamic networks （SISE...This paper investigates epidemic dynamics over dynamic networks via the approach of semi-tensor product of matrices. First, a formal susceptible-infected-susceptible epidemic dynamic model over dynamic networks （SISED-DN） is given. Second, based on a class of determinate co-evolutionary rule, the matrix expressions are established for the dynamics of individual states and network topologies, respectively. Then, all possible final spreading equilibria are obtained for any given initial epidemic state and network topology by the matrix expression. Third, a sufficient and necessary condition of the existence of state feedback vaccination control is presented to make every individual susceptible. The study of illustrative examples shows the effectiveness of our new results.展开更多
The worldwide spread of COVID-19 has caused a grave threat to human life, health, and socio-economic development. It is of great significance to study the transmission mechanism of COVID-19 and evaluate the effect of ...The worldwide spread of COVID-19 has caused a grave threat to human life, health, and socio-economic development. It is of great significance to study the transmission mechanism of COVID-19 and evaluate the effect of epidemic prevention policies. This paper employs a spatial dynamic panel data(SDPD) model to analyze the temporal and spatial spread of COVID-19, incorporating the time-varying features of epidemic transmission and the impact of geographic interconnections.Empirical studies on the COVID-19 outbreak in Shanghai during early 2022 show that the intra-regional transmission of COVID-19 dominated the cross-regional one. Additionally, strict policies are found to effectively reduce the transmission risk of COVID-19 and curb the spillover effect of the epidemic in Shanghai on other regions. Based on these results, we provide three policy suggestions. Furthermore,this research methodology can be extended to investigate other infectious diseases, thereby providing a scientific framework and theoretical basis for evaluating the spread risk of pandemics and formulating appropriate strategies.展开更多
The outbreak of corona virus disease 2019 has profoundly affected people’s way of life.It is increasingly necessary to investigate epidemics over social networks.This paper studies susceptible-infected-removed(SIR)ep...The outbreak of corona virus disease 2019 has profoundly affected people’s way of life.It is increasingly necessary to investigate epidemics over social networks.This paper studies susceptible-infected-removed(SIR)epidemics via the semi-tensor product.First,a formal susceptible-infected-removed epidemic dynamic model over probabilistic dynamic networks(SIRED-PDN)is given.Based on an evolutionary rule,the algebraic form for the dynamics of individual states and network topologies is given,respectively.Second,the SIRED-PDN can be described by a probabilistic mix-valued logical network.After providing an algorithm,all possible final spreading equilibria can be obtained for any given initial epidemic state and network topology by seeking attractors of the network.And the shortest time for all possible initial epidemic state and network topology profiles to evolve to the final spreading equilibria can be obtained by seeking the transient time of the network.Finally,an illustrative example is given to show the effectiveness of our model.展开更多
基金This work was supported by the National Natural Science Foundation of China （Nos. 61374065, 61503225）, the Research Fund for the Taishan Scholar Project of Shandong Province, and the Natural Science Foundation of Shandong Province （No. ZR2015FQ003）.
文摘This paper investigates epidemic dynamics over dynamic networks via the approach of semi-tensor product of matrices. First, a formal susceptible-infected-susceptible epidemic dynamic model over dynamic networks （SISED-DN） is given. Second, based on a class of determinate co-evolutionary rule, the matrix expressions are established for the dynamics of individual states and network topologies, respectively. Then, all possible final spreading equilibria are obtained for any given initial epidemic state and network topology by the matrix expression. Third, a sufficient and necessary condition of the existence of state feedback vaccination control is presented to make every individual susceptible. The study of illustrative examples shows the effectiveness of our new results.
基金Supported by National Key R&D Program of China (2021ZD0111204)National Natural Science Foundation of China (72073126, 72091212, 71973116, 71988101)Young Elite Scientists Sponsorship Program by CAST(YESS20200072)。
文摘The worldwide spread of COVID-19 has caused a grave threat to human life, health, and socio-economic development. It is of great significance to study the transmission mechanism of COVID-19 and evaluate the effect of epidemic prevention policies. This paper employs a spatial dynamic panel data(SDPD) model to analyze the temporal and spatial spread of COVID-19, incorporating the time-varying features of epidemic transmission and the impact of geographic interconnections.Empirical studies on the COVID-19 outbreak in Shanghai during early 2022 show that the intra-regional transmission of COVID-19 dominated the cross-regional one. Additionally, strict policies are found to effectively reduce the transmission risk of COVID-19 and curb the spillover effect of the epidemic in Shanghai on other regions. Based on these results, we provide three policy suggestions. Furthermore,this research methodology can be extended to investigate other infectious diseases, thereby providing a scientific framework and theoretical basis for evaluating the spread risk of pandemics and formulating appropriate strategies.
基金supported by the National Natural Science Foundation of China(Nos.61973175,62203328)the Tianjin Natural Science Foundation(Nos.20JCYBJC01060,21JCQNJC00840)the General Terminal IC Interdisciplinary Science Center of Nankai University.
文摘The outbreak of corona virus disease 2019 has profoundly affected people’s way of life.It is increasingly necessary to investigate epidemics over social networks.This paper studies susceptible-infected-removed(SIR)epidemics via the semi-tensor product.First,a formal susceptible-infected-removed epidemic dynamic model over probabilistic dynamic networks(SIRED-PDN)is given.Based on an evolutionary rule,the algebraic form for the dynamics of individual states and network topologies is given,respectively.Second,the SIRED-PDN can be described by a probabilistic mix-valued logical network.After providing an algorithm,all possible final spreading equilibria can be obtained for any given initial epidemic state and network topology by seeking attractors of the network.And the shortest time for all possible initial epidemic state and network topology profiles to evolve to the final spreading equilibria can be obtained by seeking the transient time of the network.Finally,an illustrative example is given to show the effectiveness of our model.
