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Applied spatial analysis

Graduate Programme in Public Health

The primary focus in this course will be on application of selected methods with the aim to study spatial correlation, evaluate spatial clustering, prepare maps using different interpolation methods, and spatial modelling (such as estimating rates and relative risks). The focus will be on application of the concepts through practical exercises using R and practising these by working with a concrete project and applying the methods using participants’ own data.

The aim of the course is to obtain knowledge on

  • Geographical data and geocoding
  • Modifiable areal unit problem (MAUP), spatial autocorrelation and neighbourhood selection
  • Visualization of spatial data on maps
  • Spatial clustering
  • Spatial interpolation
  • Geostatistics
  • Spatial modelling and spatial regression analysis.

Contents: The participants are introduced to geographical point, grid and areal data, selected spatial analyses and application of these methods within public health and related areas (such as environmental and veterinary research).

Course period: 6 May to 7 June 2019 with lectures 6-10 May 9am-4pm all days. Presentation of course report 7 June 2019. Consultations by appointments

Course and teaching arrangement: A 5-week course. In the first week (6-10 May), there will be lectures, group discussions and exercises (full days 9am-4pm). The following weeks (13 May - 3 June) participants (individually) work with their own project and prepare a course report. Participants will each have a 1-hour consultation with course lecturers regarding their project. In the 5th week (3 June) the report is handed-in. Each participant presents the report at a seminar 7 June.

Course credit: 6 ECTS

Course leader: Prof Annette Kjær Ersbøll, National Institute of Public Health, SDU

Course lecturers: Prof Annette Kjær Ersbøll, National Institute of Public Health, SDU and Post Doc Kristine Bihrmann, National Institute of Public Health, SDU

Prerequisite: The PhD courses Biostatistics I+II or a similar course. Knowledge of a statistical analysis program such as SAS/STATA/R. Participants should bring their own laptop with R installed.

Place: National Institute of Public Health, Studiestræde 6, 1455 København K

Max number of participants: 20 PhD students

Course Fee:
The course is free of charge for PhD students enrolled in the Faculty of Health Sciences at the University of Southern Denmark.
For PhD students enrolled in Universities that have joined the "Open market agreement", there is a course fee of DKK 518,-.
For other participants there is a course fee of DKK 7175,-