The Impact Of Awareness And Resources On The Disease Spreading Dynamics

In the development of human society,infectious diseases have been not only endangering people's health,but also bringing a great medical burden to the society.How should we accurately simulate the spreading process of infectious diseases in the population,and then design effective preventive measures and containment strategies?This has become an important research direction of disease spreading dynamics.In recent years,the rapid development of complex networks has further promoted the research on the disease spreading dynamics.The disease spreading mechanism in double-layer networks has received extensive attention.In a double-layer network,one is the virtual layer of awareness spreading,and the other is the physical layer of disease spreading.The set of nodes in the two layers of the network is the same,but the way the nodes are connected may be different,because each person plays a different role in different types of social relationships,including family,colleagues,friends,and so on.Due to the rapid development of communication technology,when a infectious disease appears in the population,the awareness associated with the disease quickly spreads through the virtual layer.Therefore,when disease and the related awareness spread simultaneously at different network layers,further study on the coupling dynamics of disease spreading and awareness spreading is needed.In this thesis,it's better to use we establish two new spreading models to study the interaction between double-layer network diseases and related awareness with limited resources.During a disease control,the scientific investment of medical resources and the individual's own consciousness play a very important role.How should we control the medical resources owned by an individual in order to better depress disease outbreaks?This will be an interesting and worth exploring question.Based on this basis,we proposed a corresponding double-layer network SIS-UAU disease-awaresness spreading dynamic model.Unaware and susceptible individuals,since lacking attention to their own risk of disease,provide all the individual medical resources to their infected neighbors.Aware and susceptible individuals set apart?proportion of medical resources for a defense against disease risk,and provide the remaining resources for infected neighbors.Using the micro-Markov chain method,we established the disease spreading state equation and obtained the disease spreading threshold.Interestingly,we found the optimal value interval of?corresponding to the effect of disease depression,and the size of the interval varied with the change of network heterogeneity.At the same time,we found as?increasing,the final infection density showed mixed and first-order phase transitions;for different initial infection densities,we also found that the emergence of hysteresis loops at the final infection density,verifying the existence of first-order phase transitions.The research conclusion has certain guiding significance for the control of epidemics.In the meanwhile,we found most networks in reality were evolving over time.So we proposed a novel double-layer network SIR-UAU disease-awaresness spreading dynamic model:the disease spreading layer is an activity-driven time varying network,while the awareness spreading layer is a static network.In this model,the differences in individual infection and recovery ability were considered.We made an assumption that at each time step,the susceptible individual contacts the infected neighbors and is infected with the probability ?_i=?x_i,while the infected individual recovers with the probability?_i=?y_i.In the subsequent researh,we first analytically obtained the disease spreading threshold of the model using the improved micro-Markov chain method.Secondly,through Monte Carlo simulations,we found that enhancing heterogeneity of individual activity in the physical layer would promote disease spreading,while enhancing heterogeneity of the virtual layer structure would depress disease spreading.We also found that differences in individual infectivity had little effect on disease spreading,but differences in individual recovery ability significantly affected disease spreading thresholds.Finally,we found that the correlation between individual infection ability and recovery ability had little effect on disease spreading.Our research provides a new idea for further exploring the epidemic spreading dynamics in time-varying multiplex networks.