Vaccination Effectiveness On Disease Spreading

Recent outbreaks of novel infectious diseases(e.g.COVID-19,H2N3)have high-lighted the threat of pathogen transmission,vaccination offers a necessary tool to re-lieve the sickness.However,vaccine efficacy is one of the barriers to eradicating the epidemic.In this paper,the impact of vaccine effectiveness on disease transmission is studied by using ordinary differential equation and mean field theory.Then,the dy-namic characteristics of disease transmission evolution under vaccine effectiveness are studied in metapopulation network by using Markov theory.This paper can be divided into the following two parts.1?In the study of the impact of vaccine effectiveness on disease transmission based on complex network,this paper explores the relationship between vaccine ef-fectiveness and age structure.The relationship distribution between vaccine effective-ness and age usually follows Gaussian distribution,such as H3N2,influenza A and influenza B.Based on this fact,this paper adds the age structure to the traditional two-stage SIR/V model,uses the three-stage model: decision-making stage,epidemic stage and birth-death stage to study the human behavioral choice of vaccination,and analyzes the internal causes of the change of vaccination rate.In the homogeneous network,the three-stage model with age structure produces higher vaccination level and less epi-demic scale,because the vaccinated individuals can form slower and more clusters than the vaccine is completely effective,which can effectively prevent the spread of disease? In heterogeneous networks,due to the influence of hub nodes,the three-stage model with age structure produces a larger epidemic scale and lower vaccination level at a relative cost of C ? 0.8.In addition,giving priority to vaccination to the elderly is conducive to curbing the epidemic in the face of population aging.2?In the theoretical analysis of vaccine effectiveness based on metapopulation network,this paper introduces the effectiveness of vaccine into Movement-Interaction-Return(MIR)model for the first time,and studies the evolutionary dynamics of this system.Through a large number of simulations and numerical solutions of Markov theory,it is found that the mobility will reduce the transmission threshold,which is the result of population migration spreading the disease to the whole metapopulation network,but the change of transmission threshold is very small.In metapopulation,the cycle between susceptibility,disease and succession is maintained in a dynamic balance.Secondly,when appropriate parameters are taken,with the change of disease transmission rate and population migration rate,when the disease transmission rate ex-ceeds the migration threshold,the disease will break out.The transmission threshold is calculated by Markov theory.The transmission threshold is related to the structure of the network,migration rate,parameter ? in the probability of infection of vaccinated individuals,recovery rate of diseased individuals,vaccination rate and failure rate.Fi-nally,the dynamic characteristics of changing the evolution of each state of vaccine effectiveness are studied.It is found that improving the effectiveness of vaccine is helpful to improve the proportion of vaccination and inhibit the spread of disease.