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    • Chapter 1: Why spatio-temporal epidemiology?
    • Chapter 2: Modelling health risks
    • Chapter 3: The importance of uncertainty
    • Chapter 4: Embracing uncertainty: the Bayesian approach
    • Chapter 5: The Bayesian approach in practice
    • 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) When populations and hazards collide: modelling exposures
      and health
    • BUC2 (UNAM) Thinking Globally: The Role of Big Data
    • Detecting Pattens in Space and Time (CMM)
    • BUC4 (Bath) New Frontiers: Advanced Modelling in Space and Time
    • Big Data in Environmental Research
    • Statistics and Data Science in Research: unlocking the power of your data
    • Bayesian Hierarchical Models
    • BUCX (UNAM) Quantifying the Health Impacts of Air Pollution
    • Environmental Health Impact Assessment using R (IOM)
  • Computing resources
    • WinBUGS
    • INLA
    • EnviroStat
  • Book's webpage @ CRC

Spatio-Temporal Methods in Environmental Epidemiology

Quantifying the Health Impacts of Air Pollution

course outline

The following are the online resources for the course entitled 'Environmental Health Impact Assessment using R', which is
a workshop delivered at the Institute of Occupational Medicine, Edinburgh on 23rd November 2017 which aims at providing
anintroduction to environment and health impact assessment, with emphasis on practical implementation using R. The workshop
is intended for practitioners of public health, environmental health and those with interests in health-related matters and will
consist of presentations with embedded interactive practical sessions. Participants who have access to a laptop computer are
encouraged to it to the workshop. The course will be given by Prof. Gavin Shaddick (University of Exeter) and Matthew Thomas
(University of Bath).

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

Slides

Part 1

Part 2


Lab Sessions

Part 1

Part 2


Data

Data


Required R Packages

foreign

shapefiles

CARBayes

rgdal


Other Resources

Timetable

How to install R and RStudio

  • ©Gavin Shaddick and James V. Zidek 2015