Guinea Worm ( Dracunculiasis ) Eradication in Ghana: Hotspots for Intervention - PowerPoint PPT Presentation

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Guinea Worm ( Dracunculiasis ) Eradication in Ghana: Hotspots for Intervention

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  1. Guinea Worm (Dracunculiasis) Eradication in Ghana: Hotspots for Intervention UP206A Final Project Joseph Asunka March 2011 Source: The Cater Center

  2. Purpose • To explore the distribution of cases of dracunculiasis and healthcare facilities in Northern Ghana and identify hotspots for intervention. Overall goal is to assist the guinea worm eradication program in Ghana.

  3. Dracunculiasis, one of the Neglected Tropical Diseases according to the CDC, has been a major public health issue in Ghana; specifically the Northern Region of Ghana. • The primary mode of prevention is behavior change, mostly through public health education. Are there any deficits in the distribution of public health facilities in the endemic region? • Scale of analysis is Area Council: National Regions  Districts  Area Councils

  4. Data Sources • Center for Remote Sensing and Geo- Information Services, Univ. of Ghana • Ghana Health Service • The Cater Center • ESRI : World Physical Map

  5. Where is Ghana? Ghana is on the West Coast of Africa

  6. By 2004, Guinea Worm disease (dracunculiasis) remains endemic in Ghana and Sudan.

  7. And in Ghana, most of the cases reported in 2008 were concentrated in the Northern Region.

  8. And in the Northern Region, the TolonKumbunguDistrict leads in the number of cases.

  9. Between 2004 and 2008, nearly all districts recorded a reduction in the number of cases, some as much 50 percent and more.

  10. Focusing on the eight districts with more than 400 cases in 2004, the percent reduction in cases by 2008 is generally associated with the number of healthcare facilities.

  11. In Ghana, healthcare facilities tend to be concentrated in urban areas. The Southern part of the country also has more facilities than the Northern part.

  12. In order to identify the hot spots, I computed an index based on the following features of the districts: • Number of cases reported in 2008 • Number of existing facilities • Distance to the facilities • (Euclidian distance) and • Population

  13. First I converted the features (Number of cases, Number of facilities, and Population size) of each district into rasters using the simple model on the left.

  14. I then reclassified the rasters as follows, using the model on the left: hotspots (areas ranked as high priority) are areas with higher number of cases, higher population, longer distances to facilities, and lower number of facilities.

  15. When I weight all items equally (i.e. # of cases, # of facilities, population size, and distance to health facilities) the following areas are identified as hotspots.

  16. Then I weighted the number of cases more heavily; twice as much as the other components; doing so, North West Gonja is no longer a hotspot. But the need areas in the Tolon district expands, reflecting the relatively large number of cases recorded in this district in 2008. Tolon recorded the highest number of cases (905) in 2008, which is about 30% of all cases in the entire region.

  17. METADATA

  18. Skills • Modeling • Measurement/Distance • Hotspot analysis • Creating indices • Original data incorporation • Geoprocessing • Inset map • Graduated symbols • Attribute sub-set selection • Boundary sub-set selection