Session timetable
Day 1: Delays and estimating the effective reproduction number
Monday June 23
Session 0: Introduction and course overview
Monday June 23: 09.00-09.30
- Introduction: 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 23: 09.30-10.30
- Introduction: statistical concepts used in the course (15 mins)
- Introduction: stan concepts used in the course (15 mins)
- Practice: introduction to estimation in stan (30 mins)
Session 2: Delay distributions
Monday June 23: 11.00-11.45
- Introduction: epidemiological delays and how to represent them with probability distributions (10 mins)
- Practice: simulate and estimate epidemiological delays (30 mins)
- Wrap up (5 mins)
Session 3: Biases in delay distributions
Monday June 23: 11.45-12.30 and 14.00-14.45
- Introduction: biases in delay distributions (10 mins)
- Practice:
- simulating biases in delay distributions and estimating delays without adjustment on these data (35 mins)
- 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 23: 14.45-15.30
- Introduction: Using delay distributions to model the data generating process of an epidemic (15 mins)
- Practice: implementing a convolution model and identifying potential problems (30 mins)
Session 5: \(R_t\) estimation and the renewal equation
Monday June 23: 16.00-17.30
- Introduction: the time-varying reproduction number (10 mins)
- Practice:
- using the renewal equation to estimate R (35 mins)
- combining \(R_t\) estimation with delay distribution convolutions (35 mins)
- Wrap up (10 mins)
Day 2: An introduction to nowcasting and forecasting
Tuesday June 24
Tuesday June 24: 09.00-09.15
- Day 1 review (15 mins)
Session 6: Nowcasting concepts
Tuesday June 24: 09.15-10.30
- Introduction: nowcasting as a right-truncation problem (10 mins)
- Practice:
- simulating the delay distribution (25 mins)
- nowcasting using pre-estimated delay distributions (30 mins)
- Wrap up (10 mins)
Session 7: Nowcasting with an unknown reporting delay
Tuesday June 24: 11.00-12.30
- Introduction: joint estimation of delays and nowcasts (10 mins)
- Practice:
- joint estimation of delays and nowcasts (35 mins)
- joint estimation of delays, nowcasts and reproduction numbers (35 mins)
- Wrap up (10 mins)
Session 8: Visualising infectious disease forecasts
Tuesday June 24: 14.00-14.45
- Introduction: forecasting as an epidemiological problem, and its relationship with nowcasting and \(R_t\) estimation (10 mins)
- Practice: extending a model into the future and visualising your forecast (30 minutes)
- Wrap up (5 minutes)
Session 9: Forecast evaluation
Tuesday June 24: 14.45-15.30
- Introduction: quantitatively evaluating forecasts (10 mins)
- Practice: evaluating forecasts with a range of metrics (30 mins)
- Wrap up (5 mins)
Session 10: Forecasting models
Tuesday June 24: 16.00-17.30
- Introduction: a spectrum of forecasting models (10 mins)
- Practice: evaluating forecasts from a range of models (60 mins)
- Wrap up & discussion (20 mins)
Day 3: Forecast ensembles, methods in the real world and course summary
Wednesday June 25
Wednesday June 25: 09.00-09.15
- Day 2 review (15 mins)
Session 11: Forecasting with ensembles
Wednesday June 25: 09.15-10.30
- Introduction: strategies for collating and combining models (10 mins)
- Practice: evaluating methods for ensemble forecasts (55 mins)
- Wrap up (10 mins)
Session 12: Methods in the real world
Wednesday June 25: 11.00-12.00
- Presentations and Q&A on uses of nowcasts & forecasts in the real world (60 mins)
Session 13: End of course summary
Wednesday June 25: 12.00-12.30
- Summary of the course (10 mins)
- Final discussion and closing (20 mins)