Vaccine hesitancy and erosion of herd immunity: harnessing big data to forecast disease re-emergence

项目摘要 世界卫生组织(WHO)估计，5岁以下儿童死亡人数为150万人 由于疫苗可预防的疾病(VPD)，主要是在获得疫苗的发展中国家 事实证明，消除疾病所需的覆盖面是一项挑战。令人惊讶的是，即使在富裕的国家，如 在美国，尽管疫苗覆盖率达到历史最高水平，但群体免疫被证明是难以捉摸的。这在很大程度上是 由于疫苗犹豫不决的现象，或推迟或拒绝接种疫苗的愿望，这构成了障碍 到覆盖全球根除麻疹和脊髓灰质炎等VPD疾病努力的最后一英里。实现 “终局”将需要及早发现疫苗的迟疑性，以及清楚地了解其影响。 这一行为对VPD的(重新)出现和传播具有重要意义。迫切需要的是一种整合的手段 机制传播模型中的不同数据源，以便量化人群免疫力和 在不同的行动方案中进行区别对待。拟议的工作旨在利用一种独特的 医疗索赔的高分辨率数据集，以在地理上定位疫苗接种的延迟，以确定其社会- 经济驱动因素，并剖析了这种行为与麻疹和百日咳的流行病学后果 案例研究。最终，我们的目标是为两者的空间和时间动态开发一个预测模型 接种行为和受影响传染病的发病率。这样的模式将是我们有能力 预测疾病复发，制定公共卫生政策，积极改变疫苗接种格局。

Project Summary The World Health Organization (WHO) estimates that 1.5 million deaths among children under 5 years are due to vaccine-preventable diseases (VPDs), predominantly in the developing world where achieving vaccine coverage necessary for elimination has proved a challenge. Surprisingly, even in wealthy countries such as the United States, herd immunity has proved elusive despite historically high vaccine coverage. This is in large part due to the phenomenon of vaccine hesitancy, or the desire to delay or refuse vaccination, which poses a barrier to covering the last mile in global disease eradication efforts for VPDs such as measles and polio. Achieving the “endgame” will require early detection of vaccine hesitancy, as well as a clear understanding of the impact of this behavior on the (re)emergence and spread of VPDs. What is urgently needed is a means of integrating disparate data sources within a mechanistic transmission model in order to quantify population immunity and discriminate among alternative courses of action. The proposed work aims to harness the potential of a unique high-resolution data set of medical claims to geographically localize vaccination hesitancy, to identify its socio- economic drivers, and dissect the epidemiological consequences of this behavior with measles and pertussis as case studies. Ultimately, our goal is to develop a predictive model for the spatial and temporal dynamics of both vaccination behavior and the incidence of affected infectious diseases. Such a model will be key in our ability to forecast disease re-emergence and design public health policy to positively change the vaccination landscape.