Targeting Surra interventions in Mindanao using Remote Sensing, Geographic Information System and Global Positioning System Jennifer A. Alforque Agriculturist II Department of Agriculture Regional Field Unit No. XI Davao City
Surra is a vector-borne disease (vector is a blood-sucking fly “tabanus) of livestock and is a major animal health problem in Mindanao.This disease causes low productivity, abortion, infertility and ultimately, death in livestock animals that are affected by it.
Currently, MUSCA has established that it is prevalent in many parts of Mindanao based on the large amount that has been collected through surveys and active surveillance.The data on the disease distribution is still inadequate because it lacks information on the status of risk based on the environmental and climatic factors associated with the disease.
The use of remotely sensed data, Geographic Information System and Global Positioning System can help improve the quality of information provided to the decision makers particularly in the prioritization of areas for monitoring and control of Surra.
MUSCA POST RADDL - RFU XIII P 39,600 RADDL - RFU X P 40,800 RADDL – ARMM P 33,000 RADDL - RFU IX P 40,800 Mindanao RADDL – RFU XII P 33,000 RADDL-RFU XI P 43,200 Allocation for drugs and supplies per region: (2006) Total: P230,400
The stronger rainfall and the lower elevation, the higher the risk.
The breeding potential and survival of vectors that facilitates the transmission of Surra increases during the wet season and settles in the lowland areas.
Flowchart of GIS analysis and modeling for identifying potential high and low Surra risk areas ADMINISTRATIVE BOUNDARIES CLIMATE DEMOGRAPHY TOPOGRAPHY RAINFALL POPULATION DENSITY DEM MUNICIPAL BOUNDARIES reclass interpolate RAINFALL PATTERNS ELEVATION intersect POTENTIAL SURRA HIGH-RISK AREAS IDENTIFIED Decision-makers
Rainfall Patterns 1 = low rainfall distribution [low risk] 10 = high rainfall distribution [high risk)
Satellite images of MODIS - Land Surface Temperature (LST), Elevation, Enhanced Vegetation Index, Land Cover to monitor the environmental and climatic conditions that will be suitable for Surra occurrence.
Refinement of model by integrating the vector distribution model.
Acknowledgements Dr. David Bourn Dr. Jose Molina Dr. Neil Bantayan Prof. Jun Tiburan Co-participants Resource persons
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