Investigation How The Human Behaviors Affect The Spread Of The Epidemic

Human behavior patterns and psychological patterns have a great impact on the spread of the epidemic. According to the real human behavior, construct the epidemic spreading model, put forward the methods to curb the epidemic spread is the focus question of the network research. Based on the complex network theory and game theory, in this paper, we theoritical analysis the dynamic characteristics of the epidemic spreading. The effects of human behavior patterns on the epidemic spreading are explored.Based on the change of network topology and the individual’ avoidance psychology, we study the how the human movement behavior and psychological behavior influence on the epidemic spreading from the third chapter to the sixth chapter. Firstly, epidemic spreading in the bipartite networks by considering the risk awareness is studied. Consider the fact that some special diseases will only spread among in the different types of individuals, we study this kind of disease using the the bipartite networks. Taking into account the individual risk awareness, the epidemic thresholds is theoretical calculated based on the mean field method. The results show that with the increase of the awareness of individual risks, people are easily to escape from the disease. The next, the virus variation model by considering the degree-dependent spreading rate is investigated. Considering the difference of different individuals’ physical quality and antibody, we investigate the epidemic spreading model with the virus mutation. By using the mean-field theory, the epidemic threshold in the BA network and the ER network can be theoretical drawn. Then, we explore the epidemic process on activity-driven modular networks. We propose two novel models of epidemic spreading by considering the activity-driven and the network modular. Firstly, we consider the susceptible-infected-susceptible (SIS) contagion model and derive analytically the epidemic threshold. The results indicate that the epidemic threshold only involves with the individual’s activity and the number of connections. Then, the infected-driven vaccination model is presented. Simulation results illustrate that the final density of vaccination will increase with the increase of the response strength of vaccination. The infected-driven vaccination is a good way to control the epidemic spreading. Finally, we research how the heterogeneous infection rate effect on the epidemic spreading in activity-driven network.we research the impact of the heterogeneous infection rate on the epidemic spread in the activity-driven networks. By using the mean field approximation, the epidemic threshold is theoretical-ly obtained. Several immunization strategies that could curb the epidemic spread are presented. Based on the theoretical analysis and simulation results, we obtain that the epidemic would be prevented effectively if the infection rate strongly correlates with the individuals activity. However, if infection rate has a little correlation with the individuals activity, most of individuals may be infected. In addition, the epidemic can be suppressed soon if the individuals with high activity are immunized preferentially.Based on the game theory and individual immune behavior, we study the how the human psychological behavior influence on the epidemic spreading from the seventh chapter to the ninth chapter. Firstly, we shed important light on how the initial level of visibility and limited resource might affect the evolution of the players’strategies under different network structure. We perform the prisoner’s dilemma game in the lattice network and the scale-free network, the simulation results indicate that the average density of death in lattice network decreases with the increases of the initial proportion of visibility. However, the contrary phenomenon is observed in the scale-free network. Further results reflect that the individuals’ payoff in lattice network is significantly larger than the one in the scale-free network. In the lattice network, the visibility individuals could earn much more than the invisibility one. However, the difference is not apparent in the scale-free network. We also find that a high Successful-Defection-Payoff (SDB) and a rich natural environment have relatively larger deleterious cooperation effects. A high SDB is beneficial to raising the level of visibility in the heterogeneous network, however, that has adverse visibility consequences in homogeneous network. Our result reveals that players are more likely to cooperate voluntarily under homogeneous network structure. Then, we explore how the memory and conformism effect the individuals’vaccination. Considering that memory and conformity could affect the agent’s decision, we propose a novel model to describe the vaccination dilemma by entangling the spreading dynamics with an evolutionary framework. Our results indicate that if the individuals make decision mostly depending on their own payoffs and do not believe too much in the celebrity, the final infected number will be significantly reduced. Comparing with the individuals in the BA network, people in the ER network escape from contagion much more easily and could get bigger payoffs. For the countries, strengthening the medical security system and reducing the cost of immunity can curb the spread of viruses effectively. From an individual’s viewpoint, people just remember their own last season’s payoffs can urge them to vaccinate. Finally, we explore an evolutionary vaccination game in the modified activity driven network by considering the closeness. We set a closeness parameter p which is used to describe the way of connection between two individuals. The simulation results show that the closeness p may have an active role in weakening both the spreading of epidemic and the vaccination. Besides, when vaccination is not allowed, the final recovered density increases with the value of the ratio of the infection rate to the recovery rate. However, when vaccination is allowed the final density of recovered individual first increases and then decreases with the value of the ratio of the infection rate to the recovery rate. Two variables are designed to identify the relation between the individuals’activities and their states. The results draw that both recovered and vaccinated frequency increase with the increase of the individuals’ activities. Meanwhile, the immune fee has less impact on the individuals’ vaccination than the closeness. While the ratio of the infection rate to the recovery rate is in a certain range, with the increase of the value of the ratio of the infection rate to the recovery rate, the recovered frequency of the whole crowds reduces.