Centre for Epidemic Response and Innovation (CERI), School for Data Science and Computational Thinking, Stellenbosch University, Stellenbosch 7600, South Africa.
Department of Computer Science, Faculty of Science, Stellenbosch University, Stellenbosch 7600, South Africa.
Genes (Basel). 2024 Jul 3;15(7):876. doi: 10.3390/genes15070876.
During the coronavirus disease 2019 (COVID-19) pandemic, the number and types of dashboards produced increased to convey complex information using digestible visualizations. The pandemic saw a notable increase in genomic surveillance data, which genomic epidemiology dashboards presented in an easily interpretable manner. These dashboards have the potential to increase the transparency between the scientists producing pathogen genomic data and policymakers, public health stakeholders, and the public. This scoping review discusses the data presented, functional and visual features, and the computational architecture of six publicly available SARS-CoV-2 genomic epidemiology dashboards. We found three main types of genomic epidemiology dashboards: phylogenetic, genomic surveillance, and mutational. We found that data were sourced from different databases, such as GISAID, GenBank, and specific country databases, and these dashboards were produced for specific geographic locations. The key performance indicators and visualization used were specific to the type of genomic epidemiology dashboard. The computational architecture of the dashboards was created according to the needs of the end user. The genomic surveillance of pathogens is set to become a more common tool used to track ongoing and future outbreaks, and genomic epidemiology dashboards are powerful and adaptable resources that can be used in the public health response.
在 2019 年冠状病毒病(COVID-19)大流行期间,为了使用易消化的可视化方式传达复杂信息,制作的仪表板数量和类型有所增加。大流行期间,基因组监测数据显著增加,基因组流行病学仪表板以易于解释的方式呈现这些数据。这些仪表板有可能增加产生病原体基因组数据的科学家与政策制定者、公共卫生利益相关者和公众之间的透明度。本范围综述讨论了六个可用的 SARS-CoV-2 基因组流行病学仪表板所呈现的数据、功能和视觉特征以及计算架构。我们发现了三种主要类型的基因组流行病学仪表板:系统发育、基因组监测和突变。我们发现数据来自不同的数据库,例如 GISAID、GenBank 和特定国家的数据库,并且这些仪表板是针对特定地理位置制作的。关键绩效指标和使用的可视化效果特定于基因组流行病学仪表板的类型。仪表板的计算架构是根据最终用户的需求创建的。病原体的基因组监测将成为一种更常用的工具,用于跟踪当前和未来的爆发,而基因组流行病学仪表板是一种强大且适应性强的资源,可用于公共卫生应对。