The Impact Of Individual And Collective Behavior On Disease Transmission And Prevention

Prevention and control of diseases are critical issues concerning public health,social stability,and national security.Several challenges,such as the scarcity of medical resources,population mobility,and vaccine hesitancy,have hindered efforts to control the Covid19.To delve into these challenges,we approached the discussion from both individual and collective perspectives.Drawing on theories such as the mean field theory,pairing approximation model,microscopic Markov chains,agentbased model and questionnaire analysis,we investigated healthcare resource assessment mechanisms,the impact of disease mutations under dynamic interactions,assessment survey on vaccine hesitancy,social value orientation,and the influence of reinforcement learning,and collective decisionmaking on vaccination dilemmas.These studies provide meaningful conclusions regarding individual and collective behaviors in disease transmission and prevention control.The specific research content can be categorized into the following six parts.1、In our study on the healthcare resource assessment mechanism based on evolutionary game theory,we proposed a ”SusceptibleExposedAsymptomaticSymptomaticHospitalizedRecoveredDeath” model with timevarying effects on hospitalization recovery rates and mortality rates.Both rates are influenced by the available healthcare resources and the number of individuals seeking medical attention.We initially conducted an assessment of healthcare resources in China,the United States,Brazil,Japan,Germany,and Italy.Our findings indicated that in the early stages of the pandemic,China and Japan had sufficient healthcare resources,whereas the United States,Brazil,Germany,and Italy faced challenges in adequately responding to the outbreak due to insufficient healthcare resources.Subsequently,utilizing the nextgeneration matrix method,we calculated the basic reproduction number of the model.Based on actual data,we estimated the basic reproduction number for Japan.Our results revealed that in the early stages,the situation in Japan was manageable.2、In our investigation concerning the impact of disease mutations within dynamic interactions,we explore a susceptibleinfectedsusceptible dynamic incorporating a mutation process where pathogen B emerges from the mutation of pathogen A.Employing meanfield theory,this chapter establishes the epidemiological thresholds for the SIS model involving mutation processes.Extensive numerical simulations are conducted to verify the consistency between the theoretically derived thresholds and those obtained through simulation.Our findings unveil distinct phases resulting from varying mutation and infection rates.These phases encompass a diseasefree state(S),a state exclusively featuring pathogen A(I1),a state exclusively featuring pathogen B(I2),and a coexistence state of pathogens A and B(I1I2).3、In our survey examining vaccine hesitancy,we conducted an indepth analysis utilizing previous data derived from questionnaires focused on vaccine hesitancy.The study aimed to gauge the public’s inclination toward receiving the Covid19 vaccine by scrutinizing data collected from 19 countries.Our findings revealed that government recommendations significantly influenced the willingness of individuals to get vaccinated.China exhibited the highest proportion of individuals displaying unwavering willingness to receive vaccination,largely influenced by government recommendations.In contrast,the United States portrayed a lower level of trust in governmentendorsed vaccines.By devising a vaccine hesitancy indicator,we quantified the levels of vaccine hesitancy in four countries.Notably,after vaccine safety certification and subsequent government recommendation,vaccine hesitancy ranked in descending order as follows: China,Germany,the United States,and Brazil.Moreover,when individuals relied on selfinformation to form their vaccination decisions,the degree of vaccine hesitancy followed a similar descending order,with China,Brazil,the United States,and Germany showcasing varying levels of hesitancy.4、Our study delves into the influence of social value orientations on vaccination behavior,aiming to elucidate how an individual’s social value orientation impacts their decisionmaking regarding vaccination.We model the evolution of vaccination behavior through a twostage process involving the vaccination phase and the epidemic stage.During the vaccination phase,individuals adapt their strategies by assessing their fitnesses relative to those of their peers.Within this phase,a parameter α is introduced,controlling an individual’s inclination towards two types of costs: one stemming from vaccination dynamics and epidemic stage,and another being a virtual payoff associated with the satisfaction of being amongst likeminded individuals.The epidemic phase is characterized within a susceptibleinfectedrecovery(SIR)model.Through extensive simulations and pairwise approximation techniques,our study reveals the presence of a firstorder phase transition and a secondorder phase transition concerning the vaccination rate and epidemic size.We find that resolving the vaccination dilemma is feasible when relative costs and individual preferences are localized within specific values.Simultaneously,we observe a bistable phenomenon in vaccination levels,instigated by the behavior of hub nodes in heterogeneous networks.5、Our study focused on employing reinforcement learning techniques to address the vaccination dilemma,exploring how such methodologies impact individuals’ decisionmaking within the vaccination dilemma using the BushMosteller(BM)model as an update rule.Initial,each individual is assigned an expected probability of vaccination.Within the twostage model encompassing the vaccination and epidemic processes,individuals involved in the vaccination stage adjust their vaccination probabilities by comparing their payoffs against fixed losses or average payoffs within their neighborhood.Our investigation suggests that heightened sensitivity tends to promote higher vaccination coverage.Through extensive numerical simulations,our findings indicate that the vaccination dilemma can be partially mitigated.Furthermore,when considering different parameters,the distribution of the expected vaccination probability under two distinct rules exhibits either a normal or skewed distribution.Notably,the rightskewed distribution demonstrates greater promise in overcoming the vaccination dilemma.6、In our study of collective decisionmaking on the vaccination dilemma,we introduced two types of information and two types of thresholds relevant to decisionmaking and extended the susceptibleinfectedsusceptiblevaccinated model to study the spread of disease on household networks.In this model,vaccination depends not only on the environment(number of infected neighbours)but also on the infected members of the household.Individuals update their vaccination strategy by evaluating the environmental risk(individualbased vaccination decisions).In addition,when an infected member of the household exceeds a specific threshold,his susceptible family members are unconditionally vaccinated(collective householdbased vaccination decision).Through extensive numerical simulations and microscopic Markov theory explorations,the results show that this familybased collective vaccination decision cannot stop the epidemic compared to the individualbased vaccination decision.Householdbased collective decisionmaking can only protect immunised family members.Unlike familybased collective decisionmaking,individualbased vaccination decisionmaking can successfully stop disease transmission by separating susceptible individuals from infected individuals.