Spatial-Temporal Evolution Analysis And Immune Strategy Research Of Disease Transmission On Network

From ancient times to today,infectious diseases have been a major challenge facing human society,threatening human life and causing social and economic losses.The development of global integration promotes exchanges between different parts of the world and the growing complexity of interpersonal relationships has prompted the rapid spread of diseases among people and spread to all parts of the world.To formulate effective control strategies,researchers study the law of disease transmission.On the basis of other scholars’ research,SIR model is used to study the temporal and spatial evolution characteristics of disease transmission in mobile population,and disease transmission considering spatial distance and intimacy weight.In order to control diseases effectively,an optimization method of immune control strategy is proposed.Specific research work includes the following aspects:(1)Considering the mobility of individuals in society,the SIR model of agent agent is established.The simulation technology was used to simulate the spread of infectious diseases in the process of population movement,and the spatial distribution and temporal transmission of infectious diseases were studied.With the movement and contact of individuals,diseases spread in the population.The spatial distribution of infected nodes is clustered and spread around with the change of time.Finally,all individuals are infected.(2)A SIR disease transmission mechanism with distance and intimacy weights is proposed on complex networks to analyze the characteristics of disease transmission.Firstly,we consider the geographical range of individual occupations and residences at the meso-level.According to the spatial distance between network nodes,we assume several different commuting radius to study the characteristics of disease transmission considering spatial distance.The simulation results show that,without any control measures,the smaller the set commuting radius,the slower the disease transmission speed,the later the disease outbreak period,and the smaller the peak value.Secondly,a weighted network is constructed to represent the intimate relationship between nodes.The greater the weight value,the greater the frequency of contact between individuals.The disease transmission characteristics considering the intimacy weight are studied,and compared with the spread of non-weighted networks.Research shows that the closer the relationship between nodes in the same scale weighted network,the faster the disease spread,and the propagation speed in the weighted network is slower than that in the same topological structure weighted network.Because distance and intimacy affect the spread of disease,the characteristics of disease transmission under the synergistic effect of spatial distance and intimacy are studied.It is found that the closer the distance between nodes and the greater the weight of intimacy,the more prevalent the infection is in the network.(3)Node immunization can effectively control the spread of disease,but it is generally based on the characteristics of nodes in the network to select immune nodes.On the basis of target immunization,the immune strategy optimization method is proposed.Using game theory to quantify individual’s economic benefits,disease transmission and game strategy learning evolve together under the condition of voluntary immunization.Four kinds of indicators,i.e.Degree centrality,Betweenness centrality,Clossness centrality and structural hole constraint coefficient,were used to randomly select immune nodes for priority vaccination.The influence of game learning on immunization strategy was analyzed,and the immunization strategy with minimum overall economic loss was selected.It is found that the relatively important nodes in the priority immunization network can effectively promote the learning of vaccination strategies of nodes,so as to achieve the control of disease transmission.