Estimating childhood infectious disease outbreak risk in the context of heterogeneous vaccine coverage

在不同疫苗覆盖率的背景下估计儿童传染病爆发风险

• 批准号: 9769616
• 负责人: Malia Jones
• 金额: $ 10.01万
• 依托单位: UNIVERSITY OF WISCONSIN-MADISON
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-09-01 至 2023-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9769616
• 关键词: Address; Advocacy; Affect; Area; Attitude; Automobile Driving; Behavior; Belief; Biological Models; Child; Childhood; Clinical; Communicable Diseases; Communities; Complex; County; Decision Making; Development; Diffuse; Diffusion; Diffusion of Innovation; Disease; Disease Outbreaks; Elements; Epidemic; Epidemiology; Future; Geography; Goals; Group Processes; Health; Health Policy; Health behavior; Herd Immunity; Infectious Disease Epidemiology; Intervention; Intervention Trial; Interview; K-Series Research Career Programs; Lead; Measles; Mentors; Methods; Modeling; Names; Online Systems; Outcome; Outcome Study; Parents; Pathway Analysis; Pattern; Pertussis; Policies; Policy Developments; Population; Positioning Attribute; Preventive; Process; Public Health; Quarantine; Research; Risk; Risk Estimate; Risk Management; Schools; Science; Social Network; Structure; Subgroup; Surveys; Testing; Training; United States; Universities; Vaccines; base; career; career development; clinical practice; contagion; disorder prevention; early childhood; faculty mentor; high risk; individual variation; infectious disease model; innovation; member; novel; prevent; relative effectiveness; senior faculty; social; stem; success; theories; tool; trend; uptake

Abstract Voluntary refusal of recommended childhood vaccines is becoming more common. Moreover, spatial clustering of unvac- cinated children likely introduces epidemic outbreak risk that extends far beyond what population averages suggest. How- ever, the degree to which clustering of vaccine refusal affects risk of infectious disease outbreak is largely unknown. Dy- namic processes leading to clustering of vaccine refusal are also understudied, limiting our ability to target interventions explicitly at the high-risk phenomenon of vaccine refusal clustering. Many outbreak risk management strategies are based in policy (e.g., school-entry vaccine mandates). Such policies should consider the realities of clustered vaccine refusals. This K01 Career Development Award proposal consists of advanced training and research aims on this topic. The candi- date's career objective is to become a leader in infectious disease prevention by conducting research at the intersection of infectious disease, social epidemiology, geospatial science, and complex systems modeling. The training aims focus on three areas: 1) agent-based modeling of infectious disease, 2) health policy, and 3) professional development. An interdis- ciplinary team of four senior faculty mentors at UW-Madison and Emory University will oversee the candidate's training, and includes experts in clinical pediatric infectious disease, vaccine advocacy, vaccine refusal clustering, health policy, and agent-based modeling of health behaviors. The project has two research aims. Aim 1 is to quantify the excess risk of measles and pertussis outbreak stemming from clusters of unvaccinated children. Agent-based models will be used to sim- ulate populations and test dynamic within-group processes and potential policy effects on those processes. Aim 2 is to characterize the attributes of vaccine-hesitant ideas that promote uptake of hesitancy and refusals in terms of diffusion of innovation theory. A mixed methods approach will include structured interviews, a web-based survey of vaccine-hesitant parents (target n=600), and development of an agent-based model to aid in targeting future intervention efforts. Associa- tions between diffusion of innovation constructs in vaccine hesitancy and vaccine outcomes will be estimated. Study out- comes include: a) an estimate of outbreak risk stemming from clustering in vaccine refusal; b) a decision making tool to guide policy development; and c) characterization of vaccine hesitancy using a diffusion of innovation framework. These results will fill critical empirical and theoretical gaps in vaccine hesitancy by informing how to most effectively prevent the formation of (and how to respond to) clusters of parents who refuse vaccines. To maximize success and subsequent dissemination and public health impact of the proposed research, collaborators for the proposed K01 include experts in social networks, diffusion of innovation, agent-based modeling, and community-based early childhood intervention trials. With this network of collaborators, results of the mentored K01 research will be used to substantiate future R01 interven- tion trials using a preventive health framework to modify the dynamic group processes leading to vaccine refusal clusters and infectious disease outbreak.

摘要 自愿拒绝推荐的儿童疫苗越来越普遍。此外，unvac的空间聚类- 接种疫苗的儿童可能带来的流行病爆发风险远远超过人口平均水平。怎么-- 然而，拒绝接种疫苗的聚集性对传染病爆发风险的影响程度在很大程度上是未知的。Dy- 导致疫苗拒绝聚集的动力学过程也未得到充分研究，限制了我们有针对性的干预能力 明确了拒绝接种疫苗聚集性的高危现象。许多疫情风险管理策略都是基于 在策略中（例如，学校接种疫苗）。这些政策应考虑到拒绝接种群体性疫苗的现实。 这个K 01职业发展奖提案包括关于这个主题的高级培训和研究目标。坎迪- 日期的职业目标是通过在交叉点进行研究，成为传染病预防的领导者 传染病、社会流行病学、地理空间科学和复杂系统建模。培训目标集中在 三个领域：1）基于代理的传染病建模，2）卫生政策，3）专业发展。一个中间人- 由威斯康星大学麦迪逊分校和埃默里大学的四名高级教师导师组成的学院团队将监督候选人的培训， 包括临床儿科传染病，疫苗宣传，疫苗拒绝集群，卫生政策， 和基于主体的健康行为建模。该项目有两个研究目标。目标1是量化超额风险， 麻疹和百日咳爆发源于未接种疫苗的儿童群体。基于代理的模型将用于模拟- 计算人口，测试动态组内过程和潜在的政策对这些过程的影响。目标二是 描述疫苗犹豫想法的属性，这些想法促进了犹豫和拒绝的吸收， 创新理论混合方法包括结构化访谈，基于网络的疫苗犹豫者调查， 父母（目标n=600），并制定一个基于代理人的模式，以帮助有针对性的未来干预工作。相关， 将估计疫苗犹豫和疫苗结果中创新结构的传播之间的关系。学习- 包括：a）对疫苗拒绝聚集引起的爆发风险的估计; B）决策工具， 指导政策制定; c）利用创新推广框架，说明疫苗犹豫的特点。这些 研究结果将通过告知如何最有效地预防， 拒绝接种疫苗的父母群体的形成（以及如何应对）。为了最大限度地取得成功， 传播和公共卫生的影响，拟议的K 01的合作者包括专家， 社交网络、创新传播、基于代理的建模和基于社区的幼儿干预试验。 有了这个合作者网络，K 01研究的指导结果将用于证实未来的R 01干预。 使用预防性健康框架修改导致疫苗拒绝集群的动态群体过程的试验 和传染病爆发。