Johannes Bracher – personal website
I am a postdoctoral researcher working with Melanie Schienle at the Chair of Statistics and Econometrics at Karlsruhe Insitute of Technology and Tilmann Gneiting in the Computational Statistics Group at Heidelberg Institute for Theoretical Studies. I am moreover a fellow of the YIG Preparation Programme at KIT and a PI in the Helmholtz Information and Data Science School for Health. You can also find me on Google Scholar and Twitter.
My email address is [my first name].[my last name]@kit.edu.
- Epidemic forecasting
- Forecast evaluation
- Count time series modelling
- since May 2020: Postdoctoral researcher, KIT Karlsruhe and HITS Heidelberg, Germany
- 2020: PhD Epidemiology and Biostatistics, University of Zurich, Switzerland. Thesis title: Statistical modelling and forecsting of infectious disease surveillance counts. Supervisor: Leonhard Held.
- 2016: MSc Statistics, LMU Munich, Germany
- 2013: BA Sociology, LMU Munich, Germany
- 2012: BSc Statistics, LMU Munich, Germany
My postdoctoral work is part of the Helmholtz Information & Data Science Pilot Project SIMCARD. Currently I spend most of my time on the following projects:
See my Google Scholar profile for an up-to-date bibliography.
- Cramer EY, Ray EL, Lopez VM, Bracher J et al (2022). Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the US. Proceedings of the National Academy of Sciences 119(15):e2113561119.
- Bracher J, Wolffram D, Deuschel J, Görgen K, Ketterer J et al (2021). A pre-registered short-term forecasting study of COVID-19 in Germany and Poland during the second wave. Nature Communications, 12:5173. Preprint available here.
- Bracher J, Ray EL, Gneiting T and Reich NG (2020) Evaluating epidemic forecasts in an interval format. PLOS Computational Biology 17(2): e1008618. Preprint available here.
- Bracher, J and Held, L (2020) A marginal moment matching approach for fitting endemic-epidemic models to underreported disease surveillance counts. Biometrics 77(4):1202–1214. Preprint available here.
- Bracher J and Held L (2019). Endemic-epidemic models with discrete-time serial interval distributions for infectious disease prediction. International Journal of Forecasting, in press. Preprint available here.
- Bracher J (2019). On the multibin logarithmic score used in the FluSight competitions. Proceedings of the National Academy of Sciences, 116(42):20809–20810. Preprint of an extended version available here.
- Held L, Meyer S and Bracher J (2017). Probabilistic forecasting in infectious disease epidemiology: the 13th Armitage lecture, Statistics in Medicine 36(22):3443-3460. Preprint available here.
- Bracher J (2022). A thinning-based representation of the compound-Poisson INGARCH model, with an interpretation as a stochastic epidemic process.
- Ray EL, Brooks LC, Bien J, Biggerstaff M, Bosse NI, Bracher J et al (2022). Comparing trained and untrained probabilistic ensemble forecasts of COVID-19 cases and deaths in the United States.
- Bracher J, Wolffram D, Deuschel J, Görgen K, Ketterer J et al (2021). National and subnational short-term forecasting of COVID-19 in Germany and Poland, early 2021.
- Bosse NI, Abbott S, Bracher J, Hain H, Quilty BJ et al (2021). Comparing human and model-based forecasts of COVID-19 in Germany and Poland.
- Bracher J and Littek JM (2021). An empirical assessment of influenza intensity thresholds obtained from the moving epidemic and WHO methods.
Some slides from recent talks: