CIHR_training_course

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Introduction to time series modeling for syndromic surveillance

View the Project on GitHub isabelfulcher/CIHR_training_course

Time series modeling methods for syndromic surveillance

This course consisted of five 90-minute lecutres followed by 90-minute lab sessions. The goal is to introduce attendees to concepts in time series modeling, with a particular focus on syndromic surveillance using routine health systems data. The contents available here include lecture slides and materials for the lab sessions.

Course instructors

This course is co-taught by Bethany Hedt-Gauthier (Harvard Medical School), Michael Law (University of British Columbia), and Isabel Fulcher (Harvard Medical School). Donald Fejfar and Nichole Kulikowski are the teaching assistants.

Course preparation

Download R and RStudio: If you plan to participate in the lab sessions, please download both R and RStudio (free statistical software) prior to the first session on March 2. Instructions for both Windows and Mac users are available online here (please ignore the third step about SDSFoundations Package). You can also watch this video for step by step download instructions.

Additional resources

Supplemental course materials for “Building capacity for COVID-19 Surveillance: A Statistics Course for Health Officials in Seven Low- and Middle-Income Countries”

Session 1 (March 2): Indicator choices and data visualization

Session 2 (March 9): Fitting time series models, Part 1

Session 3 (March 16): Fitting time series models, Part 2

Session 4 (March 23): Getting and cleaning the data

Session 5 (March 30): Data visualization, Part 2