The Centre for Applied Spatial Epidemiology (CASE) supports health professionals to make data-informed decisions. CASE provides unique geographic analysis of health data and new opportunities for health professionals to understand and learn from local variations in disease. That means that Governments and NGOs can prioritise health care interventions where they are needed most.
Small data for big decisions
KIT Royal Tropical Institute established CASE to improve health interventions by aligning epidemiological approaches with evidence-based best practices. We work together with governments, institutes and NGOs in low-to-middle-income countries, while encouraging health managers to use available data and spatial analysis techniques to improve decision making and more effectively deliver health care to all.
CASE combines technical expertise in the fields of spatial statistics, geo-data management and impact evaluations with a broad content knowledge of various infectious and neglected tropical diseases—including Tuberculosis (TB), HIV, and Malaria, among others—to support disease control programs.
Over the last decade, we have been a leader in spatial epidemiology research as well as the development of Geographic Information System (GIS) tools and services for disease control.
Visualising the local nature of disease
Epidemiology traditionally focuses on the local conditions of a fixed geographical area where people experience disease. However, innovations in GIS and geoinformation technologies now allow us to measure and quantify the increasingly mobile and dynamic environment in which people are exposed to health risks and disease.
Above all, we aim to provide the tools to visualise the local nature, progression and spread of disease.
Good Spatial Epidemiology
The MATCH Approach
A cornerstone of the Centre for Applied Spatial Epidemiology is the MATCH Approach. This innovative geo-spatial analysis framework evaluates the effectiveness of interventions in the context of the local disease risk, burden and health efforts. This information is especially valuable in informing local interventions.
The power of the MATCH approach is twofold. First, it employs and analyses multiple — and often underused — sources of geographically, temporally and demographically disaggregated data on epidemiological risk factors. And finally, it links data to policy objectives, combines and simplifies complex data into a more intuitive format and builds capacity for data management and analysis. This enables decision makers to use their program data to make better informed decisions supported by local evidence.
MATCH is currently being applied to support TB programs around the world to identify persistent gaps in program functioning which lead to over four million people with TB not being diagnosed or reported globally. MATCH consequently provides a valuable tool to identify geographic areas where TB case detection, diagnosis and reporting can be strengthened.
Training & Education
Using innovative geo-spatial tools opens new perspectives on how we consider the effect of geographic contexts on health, and especially disease.
Continuous knowledge transfer as well as capacity building amongst data managers, analysts and M&E experts is required to ensure that these innovations are accessible and become embedded in routine analyses and presentation,
Simultaneously, outputs of the application of analytical tools need to be critically appraised and interpreted within local context to provide value for planning. As part of our projects and programme support, we also train local counterparts and work closely with stakeholders. As a result, we build capacity and create ownership of the process and outcomes which will inform health planning, beyond the support provided by KIT.
KIT also houses an education centre with Masters’ programmes and advanced courses for health professionals — all aimed at strengthening health systems around the world. The courses are offered in cooperation with the Vrije Universiteit Amsterdam.
Data disclosure & processing
Much of the effort required to generate maps and apply spatial analysis to routinely collected programme data relies on the availability and accessibility of health data. Recently, many health programmes have adopted electronic data systems, such as the DHIS2, to collect, store an manage project data. This data is generally accessible via customizable interfaces which allow users to perform basic analysis for monitoring purposes.
To leverage these applications and fully disclose the data contained within these resources, CASE developed a GIS plugin which makes data stored and managed using DHIS2 fully interoperable with Quantum GIS, therefore enabling the integration of data across various geographic units and scales.
Comparison of two Gram stain point-of-care systems for urogenital gonorrhoea among high-risk patients
Objectives: To compare point-of-care (POC) systems in two different periods: (1) before 2010 when all high-risk patients were offered POC management for urogenital gonorrhoea by Gram stain examination; and (2) after 2010 when only those with symptoms were offered Gram stain examination.