This year we are organizing an interdisciplinary summer school from 23-27 September 2024 in Heidelberg to equip early-career modeling scientists with the main concepts and methods of researching and implementing models for climate-sensitive infectious diseases. The topics include:
- Climate and disease data preparation
- Statistical models
- Machine Learning
- Process-based modeling
as well as their application to the converging global challenges: climate change and the spread of infectious diseases.
Target Audience:
MSc. and PhD candidates as well as postdoctoral scientists and young researchers with interest in mathematical/statistical modeling of infectious diseases.
Prerequisites:
- Familiarity with Python and R.
- A background in science.
- Familiarity with ordinary differential equations.
- Knowledge in compartmental models and machine learning is a plus.
