KSRI@KIT
EJIS

"Utilizing Concept Drift for Measuring the Effectiveness of Policy Interventions: The Case of the COVID-19 Pandemic" by Lucas Baier, Niklas Kühl, Jakob Schoeffer, and Gerhard Satzger was accepted for publication at the EJIS

  • Datum: 01.12.2020
  • "Utilizing Concept Drift for Measuring the Effectiveness of Policy Interventions: The Case of the COVID-19 Pandemic" by Lucas Baier, Niklas Kühl, Jakob Schoeffer, and Gerhard Satzger was accepted for publication at the European Journal of Information Systems
    In the article, the authors use machine learning and apply so-called drift detection methods in a novel way to measure the effectiveness of policy interventions — instantiated on the example of the COVID-19 pandemic. On the basis of their detected drifts in the daily infection numbers, they analyze how characteristics of each (EU) country or (US) state, e.g., decisiveness, climate or population density, influence the time lag until policy measures show their effectiveness. As a result, especially the timing of school closures reveals a significant effect on the development of the pandemic. 

    The preprint is available here.