To design effective vaccine policies, policymakers need detailed data about who has been vaccinated, who is holding out, and why. However, existing data in the US are insufficient: reported vaccination rates are often delayed or missing, and surveys of vaccine hesitancy are limited by high-level questions and self-report biases. Here, we show how large-scale search engine logs and machine learning can be leveraged to fill these gaps and provide novel insights about vaccine intentions and behaviors. First, we develop a vaccine intent classifier that can accurately detect when a user is seeking the COVID-19 vaccine on search. Our classifier demonstrates strong agreement with CDC vaccination rates, with correlations above 0.86, and estimates vaccine intent rates to the level of ZIP codes in real time, allowing us to pinpoint more granular trends in vaccine seeking across regions, demographics, and time. To investigate vaccine hesitancy, we use our classifier to identify two groups, vaccine early adopters and vaccine holdouts. We find that holdouts, compared to early adopters matched on covariates, are 69% more likely to click on untrusted news sites. Furthermore, we organize 25,000 vaccine-related URLs into a hierarchical ontology of vaccine concerns, and we find that holdouts are far more concerned about vaccine requirements, vaccine development and approval, and vaccine myths, and even within holdouts, concerns vary significantly across demographic groups. Finally, we explore the temporal dynamics of vaccine concerns and vaccine seeking, and find that key indicators emerge when individuals convert from holding out to preparing to accept the vaccine.

翻译：为设计有效的疫苗政策，政策制定者需要关于已接种、犹豫未接种及其原因的详细数据。然而，美国现有数据存在不足：报告的接种率时常滞后或缺失，关于疫苗犹豫的调查受限于宽泛的问题设置和自报偏倚。本文展示了如何利用大规模搜索引擎日志与机器学习填补这些空白，并提供关于疫苗意图与行为的新见解。首先，我们开发了一个疫苗意图分类器，能准确检测用户何时在搜索中寻找COVID-19疫苗。该分类器与美国疾控中心接种率高度一致，相关系数超过0.86，并能实时估算至邮政编码级别的疫苗意图率，使我们能够精确捕捉不同地区、人口统计特征及时间维度下疫苗寻求的微观趋势。为探究疫苗犹豫现象，我们运用该分类器识别出两类群体：疫苗早期采纳者与疫苗观望者。研究发现，相较于匹配协变量的早期采纳者，观望者点击不可信新闻网站的概率高出69%。此外，我们将25,000个疫苗相关URL组织成层次化的疫苗关切本体，发现观望者更关注疫苗要求、疫苗研发与审批以及疫苗谣言；即使在观望者内部，不同人口群体的关切也显著不同。最后，我们探讨了疫苗关切与疫苗寻求的时变动态，发现当个体从观望转为准备接受疫苗时，关键指标会显现。