We describe visual analytics solutions aiming to support public health professionals, and thus, preventive measures. Prevention aims at advocating behaviour and policy changes likely to improve human health. Public health strives to limit the outbreak of acute diseases as well as the reduction of chronic diseases and injuries. For this purpose, data are collected to identify trends in human health, to derive hypotheses, e.g. related to risk factors, and to get insights in the data and the underlying phenomena. Most public health data have a temporal character. Moreover, the spatial character, e.g. spatial clustering of diseases, needs to be considered for decision‐making. Visual analytics techniques involve (subspace) clustering, interaction techniques to identify relevant subpopulations, e.g. being particularly vulnerable to diseases, imputation of missing values, visual queries as well as visualization and interaction techniques for spatio‐temporal data. We describe requirements, tasks and visual analytics techniques that are widely used in public health before going into detail with respect to applications. These include outbreak surveillance and epidemiology research, e.g. cancer epidemiology. We classify the solutions based on the visual analytics techniques employed. We also discuss gaps in the current state of the art and resulting research opportunities in a research agenda to advance visual analytics support in public health.

中文翻译：

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公共卫生可视化分析调查

我们描述了旨在支持公共卫生专业人员的可视化分析解决方案，从而提供预防措施。预防旨在倡导可能改善人类健康的行为和政策变化。公共卫生致力于限制急性疾病的爆发以及减少慢性疾病和伤害。为此，收集数据以识别人类健康趋势，推导出假设，例如与风险因素相关的假设，并深入了解数据和潜在现象。大多数公共卫生数据都具有时间特征。此外，在决策时需要考虑空间特征，例如疾病的空间聚类。视觉分析技术涉及（子空间）聚类、识别相关亚群的交互技术，例如特别容易感染疾病，缺失值的插补、视觉查询以及时空数据的可视化和交互技术。在详细介绍应用程序之前，我们描述了广泛用于公共卫生的需求、任务和可视化分析技术。这些包括暴发监测和流行病学研究，例如癌症流行病学。我们根据所采用的可视化分析技术对解决方案进行分类。我们还讨论了当前最先进技术的差距以及研究议程中由此产生的研究机会，以推进公共卫生领域的可视化分析支持。在详细介绍应用程序之前，广泛用于公共卫生的任务和可视化分析技术。这些包括暴发监测和流行病学研究，例如癌症流行病学。我们根据所采用的可视化分析技术对解决方案进行分类。我们还讨论了当前最先进技术的差距以及研究议程中由此产生的研究机会，以推进公共卫生领域的可视化分析支持。在详细介绍应用程序之前，广泛用于公共卫生的任务和可视化分析技术。这些包括暴发监测和流行病学研究，例如癌症流行病学。我们根据所采用的可视化分析技术对解决方案进行分类。我们还讨论了当前最先进技术的差距以及研究议程中由此产生的研究机会，以推进公共卫生领域的可视化分析支持。