The following is an example of a structure for a course in spatio-temporal epidemiology. This follows the structure of

a thirteen week graduate level course that was given at the University of British Columbia in 2013 in which there were

two 1.5 hour lectures per week. The participants in that course were statistics graduate students and students of public

health who had a strong statistical background.

Reference is given to the material in the chapters in the book together with suggested times that might be dedicated to

that material.

a thirteen week graduate level course that was given at the University of British Columbia in 2013 in which there were

two 1.5 hour lectures per week. The participants in that course were statistics graduate students and students of public

health who had a strong statistical background.

Reference is given to the material in the chapters in the book together with suggested times that might be dedicated to

that material.

Chapter |
Sections |
Suggested Timing |

Chapter 1: Why spatio-temporal epidemiology? |
All |
0.5 week plus background reading |

Chapter 2: Modelling health risks |
All, excluding 2.6 & 2.7 |
1 Week |

Chapter 3: The importance of uncertainty |
3.1–3.4 inclusive |
0.5 Week |

Chapter 4: Embracing uncertainty: the Bayesian approach |
4.1–4.6 inclusive |
2 Weeks |

Chapter 5: The Bayesian approach in practice |
All |
2 Weeks |

Chapter 6: Strategies for modelling |
6.1–6.7 inclusive |
1 Week |

Chapter 7: Is `real' data always quite so real? |
7.1–7.3 inclusive |
1 Week |

Chapter 8: Spatial patterns in disease |
All excluding 8.2 |
1.5 Weeks |

Chapter 9: From points to fields: Modelling environmental hazards over space |
9.1–9.14 inclusive |
1.5 Weeks |

Chapter 10: Why time also matters |
10.1–10.4 inclusive & 10.7 |
1 Week |

Chapter 11: The interplay between space and time in exposure assessment |
11.1, 11.2, 11.3.1, 11.4 |
1 Week |