EsteR - A Digital Toolkit for COVID-19 Decision Support in Local Health Authorities.

Sonja Jäckle, Rieke Alpers, Lisa Kühne,Jakob Schumacher,Benjamin Geisler,Max Westphal

Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie (GMDS)(2022)

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摘要
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.
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关键词
COVID-19,Decision Support Techniques,Public Health,Quarantine,Statistical Models
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