Modeling the Coupled Dynamics of Influenza Transmission and Vaccination Behavior

 描述（由申请人提供）：是否接种季节性流感疫苗的决定在很大程度上取决于对感染风险和接种疫苗的贝内的态度和信念。流感病毒感染的风险可能随季节而变化，并取决于个人的疫苗接种状况和社会网络的疫苗接种覆盖率。此外，与感染风险有关的态度和信念可以在社会上传播， 网络因此，除了个人的态度，信仰和经验与疫苗接种和治疗的in puzzuenza，互动的个人和特点的社会网络 可以在影响流感暴发的性质和严重程度以及促进疫苗接种的有效性和成本方面发挥重要作用。我们之前的探索性研究证实了接种疫苗的行为之间存在强烈的动态相互作用，在流行病学和社会网络结构中。我们收集了与决定寻求接种流感疫苗相关的行为因素的全国代表性横断面调查数据。然后，我们使用这些数据为创新的基于代理人的模型（ABM）的开发提供信息，该模型允许过去在流行病季节的经验影响在当前季节接种疫苗的决定，从而在人群水平上预测流行病的过程。与过去和标准的方法相比，我们的模型包括人类决策的两个重要属性：（a）来自过去经验的记忆和适应性，以及（B）通过谣言/信息传播的同行竞争。然而，我们的ABM假设了一个人口统计学上同质的人群，只考虑了理想化的社会网络结构，只考虑了一组减少的态度和信念，这些态度和信念会影响我们的调查所建议的接种疫苗的行为。在拟议的研究中，我们有兴趣通过允许我们的人口在接种疫苗的人口统计特征、接种疫苗的倾向以及接种疫苗的建议和机会方面有所不同，来加强和完善我们的ABM。我们将进行一项为期四年的纵向小组研究，以构建一个经验行为模型的决定，以获得季节性疫苗接种在马鲁恩扎，将包括额外的态度因素的问题，并考虑更广泛的行为机制。我们将构建一个改进的社会联系网络结构，代表美国（US）内的大城市/小城市。我们会考虑不同的 覆盖代表不同混合类型的社会联系网络结构。这种方法将使我们能够以比任何现有的随机网络模型更细的粒度和更高的真实性来建模社会互动和疾病传播。我们将校准我们的模型，以再现美国按社会人口阶层划分的疫苗接种率和感染率的一般年度趋势。然后，我们将使用我们的模型来评估行为和态度因素如何影响基于替代疫苗接种促进策略和基于激励的策略的政策的有效性，以及当通用疫苗变得可用和抗病毒药物的可用性意识增加时的预期变化。

 DESCRIPTION (provided by applicant): Decisions on whether or not to get vaccinated for seasonal influenza are largely motivated by attitudes and beliefs of the risks of infection and benefits of being vaccinated. The risk of influenza infection can change from season to season and depends on one's own vaccination status and the vaccination coverage among one's social net- work. Furthermore, attitudes and beliefs related to risk of infection can spread over a social network. Thus, in addition to personal attitudes, beliefs and experiences with vaccination and treatments for influenza, interactions of individuals on and characteristics of the social network can play important roles in shaping the nature and severity of influenza outbreaks and the effectiveness and cost of promoting vaccination. Our previous exploratory research has confirmed a strong dynamical interplay between behavior to get vaccinated, influenza epidemiology and social network structures. We collected nationally-representative cross- sectional survey data on behavioral factors associated with the decision to seek influenza vaccination. We then used these data to inform the development of an innovative agent-based model (ABM) that allowed experiences from past influenza seasons affect decisions to get vaccinated in the current season, and thus influence the course of an epidemic at the population level. In contrast to past and standard approaches, our models include two important properties of human decision-making: (a) memory and adaptability from past experiences and (b) peer-influences via rumor/information spreading. However, our ABM assumed a demographically homogenous population, considered just idealized social network structures and only considered a reduced set of attitudes and beliefs that affect the behavior to get vaccinated as suggested by our survey. In the proposed research we are interested in enhancing and refining our ABM by allowing our population to vary in terms of the demographic characteristics that influence vaccination, predisposition towards vaccination, and exposure to advice and opportunities for vaccination. We will conduct a four-year longitudinal panel study to construct an empirical behavioral model of decisions to get vaccinated for seasonal influenza that will include questions on additional attitudinal factors and considers a wider set of behavioral mechanisms. We will construct an improved social contact network structure that is representative of a large town/small city within the United States (US). We will consider different overlaying social contact network structures representative of different types of mixing. This approach will allow us to model social interactions and disease spread at a finer granularity and a higher level of realism than any existing random network model. We will calibrate our model in order to reproduce general yearly US trends of vaccination rates and infections by socio-demographic strata. We will then use our model to evaluate how behavioral and attitudinal factors influence the effectiveness of policies based on alternative vaccination promotion strategies and incentive-based strategies, and the expected changes when universal vaccines become available and awareness of the availability of antivirals increases.