Slides, code and data repository for the course Statistical Methods in Infectious Disease Epidemiology at the Epidemiology, Biostatistics and Prevention Institute of the University of Zurich, Spring 2021. The course is given by Michael Höhle and Maria Dunbar.

The ongoing COVID-19 pandemic reminds us that infectious diseases remain a continuous threat to human health. Understanding and controlling infectious diseases is thus a key element of public health and the role of statistics in this task is to bring stochastic models and observational data into sync when trying to characterize the biological and social processes governing disease spread. This course gives an overview on how such statistical modelling methods for infectious disease dynamics look and how they can be applied in practice. Contents of the course are as follows:

• Introduction to epidemic modelling
  • Compartmental models Deterministic and stochastic SIR-type models
  • Simulation and inference for SIR-type models
• Estimation in compartment models
• Reproduction numbers and their estimation
  • Incubation period, serial interval, generation time and their estimation
• Latencies and Delays
  • Back-calculation method
  • Nowcasting
• Vaccination: effectiveness, efficacy and safety
• Temporal and spatio-temporal detection of clusters
• COVID-19 Outbreak Investigations

The Lectures folder contains the PDFs of the lecture slides and corresponding R code of the slides.

Lecture videos, up2date information and exercise hand-ins is administered through the non-public UZH OLAT page.

The content of the slides etc is available under a Creative Commons 3.0 Attribute-ShareAlike. The code is available under a GNU GPL v3.0 license.