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

Stud Health Technol Inform. 2022 Aug 17:296:17-24. doi: 10.3233/SHTI220799.

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.

Keywords: COVID-19; Decision Support Techniques; Public Health; Quarantine; Statistical Models.

MeSH terms

  • COVID-19*
  • Esters
  • Humans
  • Models, Statistical
  • Pandemics
  • Software

Substances

  • Esters