Fraunhofer Institute for Digital Medicine MEVIS, Bremen / Lübeck, Germany.
Leibniz Institute for Preventive Research and Epidemiology BIPS, Bremen, Germany.
Stud Health Technol Inform. 2022 Aug 17;296:17-24. doi: 10.3233/SHTI220799.
In Germany, the current COVID-19 cases are managed and reported by the local health authorities. The workload of their employees during the pandemic is high, especially in periods of high infection numbers. In this work a decision support toolkit for local health authorities is introduced. A demonstrator web application was developed with the R Shiny framework and is publicly accessible online. It contains five separate tools based on statistical models for specific use cases and corresponding questions of COVID-19 cases and their contacts. The underlying statistical methods have been implemented in a new open-source R package. The toolkit has the potential to support local health authorities' employees in their daily work. A simulated-based validation of the statistical models and a usability evaluation of the demonstrator application in a user study will be carried out in the future.
在德国，当前的 COVID-19 病例由当地卫生部门负责管理和报告。在大流行期间，他们的员工工作量很大，尤其是在感染人数较高的时期。在这项工作中，引入了一个用于地方卫生当局的决策支持工具包。使用 R Shiny 框架开发了一个演示 Web 应用程序，并在线公开提供。它包含五个基于统计模型的独立工具，用于特定用例以及 COVID-19 病例及其接触者的相应问题。基础的统计方法已在一个新的开源 R 包中实现。该工具包有可能支持地方卫生当局员工的日常工作。未来将基于模拟对统计模型进行验证，并在用户研究中对演示应用程序的可用性进行评估。
