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Short Course Materials for Forecasting for Decision-Making: An Epidemiological & Ecological Perspective

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Overview

This repository will contain all materials for the Short Course on Forecasting for Decision-Making: An Epidemiological & Ecological Perspective. The course is in-person and will be hosted at the Fields Institute in Toronto, ON and takes place from July 24th - 28th. The course materials include lectures, exercises and forecast modelling materials for three case studies: Infectious Disease Control, Fisheries Management, Water Quality Monitoring. All course materials will be made available online after July 28th. For a description of the course's overall objectives, please see here.

Schedule

Time Slots Monday Tuesday Wednesday Thursday Friday
9:00
-
10:00
Lecture 1 Topic(s):
(1) Introductions & Schedule Overview;

(2) Introduction to Forecasting

Lead(s):
(1) KB, CRF & Instructors;
(2) Mike Dietze
Topic:
Bayesian Analysis - Part 2

Instructor: Mike Dietze
Topic:
Model Assessment

Instructor: Mike Irvine
Topic:
Delivering Forecasting Models to Decision Makers

Instructor: Colin Daniel and Alex Filazzola
Topic:
OCAP Training Part 1


Instructor: OCAP
10:00
-
10:20
Coffee Break
10:20
-
11:20
Lecture 2 Topic:
Introduction to the Modelling Landscape

Instructor: Irena Papst
Topic:
Reproducibility & Transparency

Instructor: Mike Irvine
Topic:
Combining Fish Population Forecasting with Fisheries Management:
an Introduction to Management Strategy Evaluation (MSE)

Instructor: Brooke Davis
Topic:
Experiences Building Collaborations and Bridging Communication

Instructor: Brooke Davis + Other Instructors
(1) Group Work:
Finalize Presentation

(2) Overview of NEON Ecological Forecasting Challenge

Lead: (2) Quinn Thomas
11:20
-
11:30
Break
11:30
-
12:30
Extra Practice
or
Lecture 3:
Topic:
Bayesian Analysis - Part 1

Instructor: Mike Dietze
Exercise 2:
Paired Coding

Lead: Mike Dietze
Exercise 3:
MSE Exercise


Lead: Brooke Davis
Topic:
Decision Analysis in Health

Instructor: Beate Sander
Group Work:
Finalize Presentation

Closing Remarks
12:30
-
1:30
Lunch
1:30
-
3:00
Extra Practice
or
Lecture 3:
Exercise 1:
Introduction to Bayesian Analysis

Lead(s): Mike Dietze + Mike Irvine
Topic(s):
(1) Code Review Example;
(2) Propagating, Analyzing, &
Reducing Uncertainty

Instructor: Mike Dietze + Irena Papst
Group work Exercise 4:
Writing Lay Summaries Exercise

Lead: Korryn Bodner and Carina Rauen Firkowski
Group Project Presentations
Part 1
3:00
-
3:20
Coffee Break
3:20
-
5:30
Group Work Case Study Introductions (30 mins)

Case Study Overviews (in small groups)

Lead(s): All Instructors
Group work Group work Group work Group Project Presentations
Part 2

End at 3:50pm
6:00
-
8:00
Group Dinner

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