Understanding the relationship between herd immunity and geographic scale to improve estimates of localized infectious disease outbreak risk

摘要 在美国，疫苗可预防疾病的爆发规模和频率正在增加。例如, 虽然它在2000年被正式宣布消灭，但在世界上已经有同样多的麻疹病例 2019年前5个月(940)超过了自1994年以来的任何一个完整的日历年度。考虑到疫苗迟疑不决的趋势， 麻疹和其他疫苗可预防疾病的未来暴发几乎肯定会发生。群体免疫力 描述一种现象，在这种现象中，对感染没有免疫力的个人被间接保护，使其免受 这种感染是由人群中接种疫苗的个人造成的。它是一个重要的概念，用于设计和 监测疫苗接种活动，了解传染病传播动态。尽管它的 重要的是，群体免疫的许多方面仍未得到充分或未被研究，从而限制了其有用性 在应用流行病学或公共卫生环境中。这份K01奖提案关注的是群体免疫力及其 在地方地理尺度上与传染病暴发风险的关系。我的职业目标是成为一名 在疫苗接种和疫苗可预防疾病的空间流行病学方面的领先学者，专门从事 将人类行为、政策和疾病传播系统联系起来以了解 疾病暴发风险的演变性质。培训活动的重点是扩大我目前在健康方面的专业知识 地理和空间数据分析，具有传染病流行病学方法方面的专门培训，代理- 基于建模和社交网络分析。拟议的研究计划支持跨学科的 一种综合了地理学、流行病学、数据科学和 计算模型和公共卫生实践，以检查疫苗接种之间的复杂关系 覆盖率、群体免疫力、地理范围、空间和社会联系模式以及疾病传播 动力学。我的研究目标是：1)评估使用基于网络的社区来定义牛群的方法 检测算法，2)确定疫苗接种覆盖率和疫苗接种率之间关系的地理范围 群体免疫效应是可以检测到的，3)通过以下方式改进对当地疾病爆发风险的估计 将潜在的疾病传播链与疫苗接种覆盖率数据相结合。我的指导和建议 团队在培训和研究主题方面拥有专业知识，并具有领导经验 跨学科研究团队。研究的结果将是一种创新的方法来定义 人口中与流行病学相关的牛群，关于检测牛群能力的新信息 不同地理范围的分析的免疫效果，以及对当地传染病的改进估计 暴发风险。本K01奖项中提出的研究、培训和指导计划将支持 制定一项未来的R级建议，以检查疫苗局部暴发的风险如何可预防 随着人类行为的改变(例如，拒绝接种疫苗)和疾病的发生，疾病会在空间和时间上演变 疫苗相关政策(例如，禁止疫苗接种豁免)。

ABSTRACT The size and frequency of outbreaks of vaccine-preventable diseases in the US are increasing. For example, although it was officially declared eliminated in 2000, there already have been as many measles cases in the US in the first five months of 2019 (940) than any full calendar year since 1994. Given trends in vaccine hesitancy, future outbreaks of measles and other vaccine-preventable diseases are all but certain to occur. Herd immunity describes the phenomenon wherein individuals without immunity from an infection are indirectly protected from that infection by immunized individuals within the population. It is an important concept for designing and monitoring vaccination campaigns and understanding infectious disease transmission dynamics. Despite its importance, a number of aspects of herd immunity remain under- or unexamined, thereby limiting its usefulness in applied epidemiological or public health settings. This K01 Award proposal focuses on herd immunity and its relationship with infectious disease outbreak risk at local geographic scales. My career goal is to become a leading scholar in the spatial epidemiology of vaccination and vaccine-preventable diseases, specializing in research that links together human behavior, policy, and disease transmission systems to understand the evolving nature of disease outbreak risk. The training activities focus on expanding my current expertise in health geography and spatial data analysis with specialized training in infectious disease epidemiology methods, agent- based modeling, and social network analysis. The proposed research program supports an interdisciplinary approach that integrates concepts and techniques from geography, epidemiology, data science and computational modeling, and public health practice to examine the complex relationships among vaccination coverage, herd immunity, geographic scale, spatial and social connectivity patterns, and disease transmission dynamics. My research aims are: 1) Evaluate approaches to define herds using network-based community detection algorithms, 2) Identify geographic scales at which the relationship between vaccination coverage and the herd immunity effect is detectable, and 3) Develop improved estimates of local disease outbreak risk by integrating potential chains of disease transmission with vaccination coverage data. My mentoring and advisory team have specialized expertise across the training and research topics, as well as experience leading interdisciplinary research teams. The outcomes of the research will be an innovative approach to define epidemiologically-relevant herds in the population, new information regarding the ability to detect the herd immunity effect across various geographic scales of analysis, and improved estimates of local infectious disease outbreak risk. The research, training, and mentoring plans proposed in this K01 award will support the development of a future R-level proposal to examine how the risk of local outbreaks of vaccine-preventable diseases evolves over space and time as changes occur in both human behaviors (e.g., vaccine refusal) and vaccine-related policy (e.g., banning exemptions from vaccination).