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    • Chapter 1: Why spatio-temporal epidemiology?
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    • Chapter 4: Embracing uncertainty: the Bayesian approach
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    • Chapter 6: Strategies for modelling
    • Chapter 7: Is `real' data always quite so real?
    • Chapter 8: Spatial patterns in disease
    • Chapter 9: From points to fields: Modelling environmental hazards over space
    • Chapter 10: Why time also matters
    • Chapter 11: The interplay between space and time in exposure assessment
    • Chapter 12: Roadblocks on the way to causality: exposure pathways, aggregation and other sources of bias
    • Chapter 13: Better exposure measurements through better design
    • Chapter 14: New frontiers
  • Courses
    • Statistical methods in epidemiology
    • Spatio-temporal Methods in epidemiology
    • Advanced statistical modelling in space and time
    • BUC1 (CIMAT)
    • BUC2 (UNAM)
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  • Book's webpage @ CRC

Spatio-Temporal Methods in Environmental Epidemiology

New Frontiers: Advanced Modelling in Space and Time

course outline

The following are the online resources for the course entitled 'New frontiers: advanced modelling in space and time',
which is part of a series of workshops, organised and funded as a collaboration between University of Bath, UNAM
and CIMAT. These workshops have been termed the BUC series. More details can be found here.

This course was delivered at the University of Bath, Bath, UK between 2nd-4th June 2016.

This course is designed for graduates/students who have an interest in spatio-temporal methods and how they might be
applied in epidemiological analyses.

The slides, problem sheets, solutions and other relevant resources can be found below.

Slides

Course Slides


Lab Sessions

Design of monitoring network

Spatial modelling with INLA


Data

Design of monitoring network

Spatial modelling with INLA


Required R Packages

INLA

spatstat

mvtnorm

lattice

mgcv

pixmap

numDeriv

fields

  • ©Gavin Shaddick and James V. Zidek 2015