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Remote Sensing tools to study the Epidemiology and Space/Time dynamics of diseases.
|Project type:||Long Term Research|
|Time frame:||2007 - 2010|
|Geographic keyword: Republic of South Africa | Africa | Italy | Europe|
|General keyword: Disease modeling | Remote sensing | Decision support | STIS|
|Specific keyword: Foot and mouth disease | Bluetongue | Spatial epidemiology|
A variety of remote sensing tools has been developed for use in epidemiological studies. Their individual outputs have been helpful to improve our understanding of specific aspects of spatial epidemiology of diseases. Unfortunately, little effort has been made to fine-tune these tools, exploit their complementarity, integrate their outputs in state of the art spatial information systems and test their robustness in a data-driven decision support environment. Within the framework of the Epi-STIS project, a Belgian pool of expertise will be established with the objective to (i) develop a set of innovative integrated generic tools to improve the capability to analyse and understand the space-time dynamics of diseases
and (ii) develop an innovative Space Time Information System framework that can include the outcome of those integrated tools to improve the management of important veterinary diseases.
Finally, a broader multidisciplinary 'Epi-STIS' group will be created which will remain operational beyond the lifetime of the project.
Through two main general scientific objectives Epi-STIS aims at:
- Exploring how a wide range of low, medium, high and very high resolution remote sensing tools and GIS can be integrated and contribute to a better understanding of the space/time dynamics of those veterinary important diseases;
- Exploring how integrated spatial analysis outputs can contribute to improved information and decision support for disease management.
This multi-scale and multi-sensor approach has until now not been adopted. To address the scientific objectives, the proposed cross-cutting project (Epi-STIS) will use historical and contemporary data on two economically important but epidemiologically complementary case studies of a vector borne disease (bluetongue) and a contagious non-vector borne (foot and mouth disease) disease, thus improving the management/control of major diseases hampering livestock production both in Africa and Europe.
- Using the vector-borne disease case study, Epi-STIS aims to (i) evaluate the usefulness of integrating various types of remotely sensed data to model invasion dynamics of vector borne pathogens and (ii) identify features that may constitute barriers to the spread of such pathogens.
- Using the contagious viral disease case study at different human/livestock/wildlife interfaces, Epi-STIS aims to (i) evaluate the usefulness of integrating various types of remotely sensed data to model the spread of non-vector borne contagious viral pathogens, (ii) Identify factors contributing to the permeability of man-made barriers (e.g. game fence) to prevent the spread such contagious pathogens and (iii) identify the drivers of change affecting the spread of a contagious pathogens at different types of interface.
Both case studies are strongly data-driven and rely on a set of common approaches. Although the case studies are disease-specific, the innovative approaches that are developed and implemented will be generic and can be readily applied to other diseases (notably those related to human health) with similar epidemiological settings.
Legend to the figures:
Figure 1: Expert inputs in EPISTIS (L/MRRS = Low and medium resolution remote sensing, HRRS = High resolution remote sensing, VHRRS = Very high resolution remote sensing, STIS = Space Time Information Systems)
Figure 2: Project area – Italy
Figure 3: Project area – South Africa