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EsteR - A Digital Toolkit for COVID-19 Decision Support in Local Health Authorities
Sonja Jäckle1, Rieke Alpers1, Lisa Kühne2
1Fraunhofer Institute for Digital Medicine MEVIS, Bremen / Lübeck, Germany.
Abstract:
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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