Geographic Information Systems (GIS) for Public Health and Epidemiology
Amsterdam, Netherlands
Course
DURATION
2 weeks
LANGUAGES
English
PACE
Full time
APPLICATION DEADLINE
14 Feb 2027
EARLIEST START DATE
14 Apr 2027
TUITION FEES
EUR 1,995 / per course *
STUDY FORMAT
On-Campus
* early bird fee € 1.596 and | tropEd fee € 1.796. Early bird fee applies if payment is received before 14 January 2027
Key Summary
About: This KIT Institute course teaches use of Geographic Information Systems (GIS) for public health and epidemiology, focusing on analyzing open source health data, mapping disease patterns in time and place, assessing access to health services. Using Free and Open Source Software, the course combines lectures, case studies, guest presentations, and is accredited by tropEd for the Master in International Health.
Career Outcomes: Graduates can pursue roles as public health analyst, epidemiologist, GIS specialist, health planner, monitoring and evaluation officer, or work in disease control programmes, research institutions, NGOs, health ministries, applying spatial analysis, geo-visualization, health mapping and programme evaluation skills.
The explosive availability of open source health data offers new opportunities to analyse and monitor trends in disease. It also opens new pathways to assess how effectively health systems can address these trends. Epidemiologists, health professionals and policymakers increasingly utilise new analytical techniques and software to process and analyse the growing volumes of high resolution health data.
Geographic Information Systems (GIS) provide tools for planning and monitoring of health interventions and disease control activities to improve health care delivery and utilisation. In this course you will learn how to use GIS to identify patterns of disease in time and place and to assess public access to health care services. Emphasis will also be given to geo-visualise health management information for advocacy purposes and to monitor and evaluate programme performance. Case studies and lectures will address a wide range of infectious diseases, including neglected tropical diseases, water-borne diseases and sexually transmitted infections.
This course aims to provide health professionals with a solid understanding and hands-on practice allowing them to use GIS in their daily work. The increasing use of open source software solutions in professional settings provides a free, yet perfectly viable alternative to commercial software. This course uses Free and Open Source Software solutions to allow course participants to bring their skills into practice without depending on commercial packages.
In both weeks guest speakers are invited to present applications of the use of GIS in disease control programmes and research projects.
Accreditation
This course is also accredited for the Master in International Health programme organised by tropEd, a network of European institutions for higher education in international health.
First week
The first week will focus on learning basic GIS theory and functions. Emphasis will be given to develop basic software operating skills and understanding of analytical approaches to analyze spatial data.
Topics include
- Basic GIS theory and principles including spatial data formats
- Introduction to QGIS 3.x software package
- Spatial data management
- Using online data repositories and data extraction from cloud databases (e.g. DHIS2)
- Data visualization and cartographic concepts
- Using geographic coordinate reference systems
- Introduction to essential geoprocessing functions
Second week
The second week of the course will provide the opportunity to apply and extend the GIS skills that have been learned in the first week into a public health context. The course will address specific problems in the field of planning and evaluating disease control programmes and space-time analyses of health data.
Topics include:
- Spatial analysis of geographic patterns of disease: point pattern analysis and geographic cluster analysis
- Geographic access analysis: quantifying health service coverage
- Spatial Multi Criteria Risk Analysis using the MATCH approach
- Digital (spatial) data-collection using ODK software system
The course will use the following open source and freely available software packages:
- QGIS 3.x open source GIS package.
- GeoDA (optional)
- DHIS2 (vs 4.x)
- R statistical programming (optional)