Jannik Deuschel
A5038703966- COVID-19, Geopolitics, Technology, Migration
- Regional Socio-Economic Development Trends
- Impact of AI and Big Data on Business and Society
- COVID-19 epidemiological studies
- COVID-19 Pandemic Impacts
- Data-Driven Disease Surveillance
- Forecasting Techniques and Applications
- SARS-CoV-2 and COVID-19 Research
- Influenza Virus Research Studies
- Explainable Artificial Intelligence (XAI)
- Energy Load and Power Forecasting
- COVID-19 Digital Contact Tracing
- Machine Learning in Healthcare
- Health Systems, Economic Evaluations, Quality of Life
- COVID-19 Clinical Research Studies
Karlsruhe Institute of Technology
2020-2023
Short-term forecasts of infectious disease burden can contribute to situational awareness and aid capacity planning. Based on best practice in other fields recent insights epidemiology, one maximise the predictive performance such if multiple models are combined into an ensemble. Here, we report ensembles predicting COVID-19 cases deaths across Europe between 08 March 2021 07 2022.
Abstract Disease modelling has had considerable policy impact during the ongoing COVID-19 pandemic, and it is increasingly acknowledged that combining multiple models can improve reliability of outputs. Here we report insights from ten weeks collaborative short-term forecasting in Germany Poland (12 October–19 December 2020). The study period covers onset second wave both countries, with tightening non-pharmaceutical interventions (NPIs) subsequently a decay (Poland) or plateau renewed...
During the COVID-19 pandemic there has been a strong interest in forecasts of short-term development epidemiological indicators to inform decision makers. In this study we evaluate probabilistic real-time predictions confirmed cases and deaths from Germany Poland for period January through April 2021.
Abstract We report insights from ten weeks of collaborative COVID-19 forecasting for Germany and Poland (12 October – 19 December 2020). The study period covers the onset second wave in both countries, with tightening non-pharmaceutical interventions (NPIs) subsequently a decay (Poland) or plateau renewed increase (Germany) reported cases. Thirteen independent teams provided probabilistic real-time forecasts cases deaths. These were lead times one to four weeks, evaluation focused on one-...
Abstract Background Short-term forecasts of infectious disease burden can contribute to situational awareness and aid capacity planning. Based on best practice in other fields recent insights epidemiology, one maximise the predictive performance such if multiple models are combined into an ensemble. Here we report ensembles predicting COVID-19 cases deaths across Europe between 08 March 2021 07 2022. Methods We used open-source tools develop a public European Forecast Hub. invited groups...
Abstract Background During the COVID-19 pandemic there has been a strong interest in forecasts of short-term development epidemiological indicators to inform decision makers. In this study we evaluate probabilistic real-time predictions confirmed cases and deaths from Germany Poland for period January through April 2021. Methods We Poland. These were issued by 15 different forecasting models, run independent research teams. Moreover, performance combined ensemble forecasts. Evaluation is...
Interpretable policy learning seeks to estimate intelligible decision policies from observed actions; however, existing models fall short by forcing a tradeoff between accuracy and interpretability. This limits data-driven interpretations of human decision-making process. e.g. audit medical decisions for biases suboptimal practices, we require processes which provide concise descriptions complex behaviors. Fundamentally, approaches are burdened this because they represent the underlying...