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首页> 外文期刊>Chaos, Solitons and Fractals: Applications in Science and Engineering: An Interdisciplinary Journal of Nonlinear Science >Risk assessment for infectious disease and its impact on voluntary vaccination behavior in social networks
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Risk assessment for infectious disease and its impact on voluntary vaccination behavior in social networks

机译:社交网络中传染病的风险评估及其对自愿接种行为的影响

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Achievement of the herd immunity is essential for preventing the periodic spreading of an infectious disease such as the flu. If vaccination is voluntary, as vaccination coverage approaches the critical level required for herd immunity, there is less incentive for individuals to be vaccinated; this results in an increase in the number of so-called "free-riders" who craftily avoid infection via the herd immunity and avoid paying any cost. We use a framework originating in evolutionary game theory to investigate this type of social dilemma with respect to epidemiology and the decision of whether to be vaccinated. For each individual in a population, the decision on vaccination is associated with how one assesses the risk of infection. In this study, we propose a new risk-assessment model in a vaccination game when an individual updates her strategy, she compares her own payoff to a net payoff obtained by averaging a collective payoff over individuals who adopt the same strategy as that of a randomly selected neighbor. In previous studies of vaccination games, when an individual updates her strategy, she typically compares her payoff to the payoff of a randomly selected neighbor, indicating that the risk for changing her strategy is largely based on the behavior of one other individual, i.e., this is an individual-based risk assessment. However, in our proposed model, risk assessment by any individual is based on the collective success of a strategy and not on the behavior of any one other individual. For strategy adaptation, each individual always takes a survey of the degree of success of a certain strategy that one of her neighbors has adopted, i.e., this is a strategy-based risk assessment. Using computer simulations, we determine how these two different riskassessment methods affect the spread of an infectious disease over a social network. The proposed model is found to benefit the population, depending on the structure of the social network and cost of vaccination. Our results suggest that individuals (or governments) should understand the structure of their social networks at the regional level, and accordingly, they should adopt an appropriate risk-assessment methodology as per the demands of the situation.
机译:牛群免疫力的获得对于防止诸如流感等传染病的周期性传播至关重要。如果自愿接种疫苗,因为疫苗接种覆盖率已接近牛群免疫所需的关键水平,则个人接种疫苗的动机就会减少;这导致所谓的“搭便车”的人数增加,他们通过畜群免疫巧妙地避免感染并避免支付任何费用。我们使用起源于进化博弈论的框架来研究这种社会困境,涉及流行病学和是否要接种疫苗的决定。对于人群中的每个人,疫苗接种的决定都取决于人们如何评估感染风险。在这项研究中,我们提出了一种疫苗接种游戏中的新风险评估模型,当一个人更新其策略时,她将自己的收益与净收益进行比较,该净收益是通过对采用与随机策略相同策略的个体的集体收益进行平均而获得的选择的邻居。在先前的疫苗接种游戏研究中,当一个人更新其策略时,她通常将其收益与随机选择的邻居的收益进行比较,这表明更改其策略的风险很大程度上取决于另一个人的行为,即是基于个人的风险评估。但是,在我们提出的模型中,任何人的风险评估都是基于一项策略的集体成功,而不是任何其他人的行为。为了进行策略调整,每个人始终会对其邻居之一采用的某种策略的成功程度进行调查,即这是基于策略的风险评估。使用计算机模拟,我们确定这两种不同的风险评估方法如何影响社交网络上传染病的传播。根据社会网络的结构和疫苗接种成本,发现了所提议的模型可以使人口受益。我们的结果表明,个人(或政府)应了解其在区域一级的社交网络的结构,因此,他们应根据情况的需要采用适当的风险评估方法。

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