The explosive availability of open source health data offers new opportunities to analyze and monitor trends in disease. It also opens new pathways to assess how effectively health systems can address these trends. Epidemiologists, health professionals and policy makers increasingly utilize new analytical techniques and software to process and analyze the growing volumes of high resolution health data.
This course trains health professionals with the essential skills to map and analyze routinely collected health data. In this training you will learn what data and methods are used to detect areas of high disease risk and to compare these with geographic patterns of health service delivery.
"The course is highly applicable and provides hands on practice."
"The course absolutely met all my expectations. I enjoyed every day of it."
"The instructors were extremely knowledgeable and helpful in trouble shooting"
"I appreciate the amount of topics covered. I feel I now know enough to find my way and learn more"
"The case studies force you to explore and find solutions which increased the learning."
- A degree in public health or international health: BSc, MSc or equivalent academic training
A basic knowledge of epidemiology and principles of social research
- At least 3 years of professional experience, preferably working at a national level in low and middle income countries
- Proven proficiency in spoken and written English
The application package is due two months before the start of the course.
Please upload your application online. The following documents should be uploaded:
- A one-page letter of motivation
- Copies of your diplomas and grade reports
- An up-to-date curriculum vitae
This course can be taken on its own or as part of the Master in International Health (MIH) programme.
Early Bird registration
Early Bird registration and payment applies when payment is made before 31 March 2019.
Please note that you will receive a response on your application within 4 weeks.
FAQ Online Application System
Do you have a question about our Online Application System? Then you can find the answer in our FAQ Online Application System:
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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.
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.
Specific topics further 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
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.
- 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
In both weeks guest speakers are invited to present applications of the use of GIS in disease control programmes and research projects.
The course will use the following open source and freely available software packages:
- GeoDA (optional)
- DHIS2 (vs 4.x)
- R statistical programming (optional)
Why study at KIT?
Up-to-date approach to complex public health issues
Exchange between disciplines
Development of personal and professional competencies
Participants from diverse backgrounds and countries
Teaching by highly qualified specialists
Positively reviewed by tropEd
KIT: international centre of excellence in international health and development
Accredited by NVAO