Sessions

Session 0: Introduction and course overview

Monday June 24: 9.00-9.30

• Introduction to the course and the instructors (10 mins)
• Motivating the course: From an epidemiological line list to informing decisions in real-time (20 mins)

Session 1: R, Stan, and statistical concept background

Monday June 24: 9.30-10.30

• Introduction to statistical concepts used in the course (15 mins)
• Introduction to stan concepts used in the course (15 mins)
• Practice session: introduction to estimation in stan (30 mins)

Session 2: Delay distributions

Monday June 24: 11.00-11.45

• Introduction to epidemiological delays and how to represent them with probability distributions (10 mins)
• Practice session: simulate and estimate epidemiological delays (30 mins)
• Wrap up (5 mins)

Session 3: Biases in delay distributions

Monday June 24: 11.45-12.30 and 14.00-14.45

• Introduction to biases in delay distributions (10 mins)
• Practice session: Simulating biases in delay distributions and estimating delays without adjustment on these data (35 mins)
• Practice session: estimating delay distributions with adjustments for bias (35 mins)
• Wrap up (10 mins)

Session 4: Using delay distributions to model the data generating process of an epidemic

Monday June 24: 14.45-15.30

• Using delay distributions to model the data generating process of an epidemic (15 mins)
• Practice session: implementing a convolution model and identifying potential problems (30 mins)

Session 5: \(R_t\) estimation and the renewal equation

Monday June 24: 16.00-17.30

• Introduction to the time-varying reproduction number (10 mins)
• Practice session: using the renewal equation to estimate R (35 mins)
• Practice session: combining \(R_t\) estimation with delay distribution convolutions (35 mins)
• Wrap up (10 mins)

Session 6: Nowcasting concepts

Tuesday June 25: 9.00-10.30

• Introduction to nowcasting as a right-truncation problem (10 mins)
• Practice session: Simulating the delay distribution (35 mins)
• Practice session: Nowcasting using pre-estimated delay distributions (35 mins)
• Wrap up (10 mins)

Session 7: Nowcasting with an unknown reporting delay

Tuesday June 25: 11.00-12.30

• Introduction to joint estimation of delays and nowcasts (10 mins)
• Practice session: Joint estimation of delays and nowcasts (35 mins)
• Practice session: Joint estimation of delays, nowcasts and reproduction numbers (35 mins)
• Wrap up (10 mins)

Session 8: Forecasting concepts

Tuesday June 25: 14.00-15.30

• Introduction to forecasting as an epidemiological problem, and its relationship with nowcasting and \(R_t\) estimation (10 mins)
• Practice session: extending a model into the future (35 minutes)
• Practice session: evaluate your forecast (35 mins)
• Wrap up (10 mins)

Session 9: Forecasting models

Tuesday June 25: 16.00-17.30

• An overview of forecasting models (10 mins)
• Practice session: Evaluating forecasts from a range of models (60 mins)
• Wrap up and discussion (20 mins)

Session 10: Examples of available tools

Tuesday June 25: 9.00-10.30

• Introduction to tools for \(R_t\) estimation, nowcasting and forecasting (5 mins)
• Group work: explore a tool and relate it to key concepts in the course (30 mins)
• Discussion (15 mins)
• Individual exploration of all packages (35 mins)
• Wrap up (5 mins)

Session 11: Methods in the real world

Wednesday June 26: 11.00-12.00

• Presentations and Q&A on uses of nowcasts & forecasts in the real world (60 mins)

Session 12: End of course summary

Wednesday June 26: 12.00-12.30

• Summary of the course (10 mins)
• Final discussion and closing (20 mins)