MALARIA RISK ASSESSMENT USING GEOGRAPHIC INFORMATION SYSTEM (GIS): A CASE OF ADAMA DISTRICT, Ethiopia Kibrom Hailu Tafere (MSc.) ESRI,EAST AFRICA Education GIS CON., SEP, 2016 9/30/2016 3:36:41 PM 1
A short Professional chronicle of “ Kibrom Hailu ” Selected publication Kibrom Hailu T., Tilahun E, and Daniel A,. GIS based Malaria Risk Assessment A case Study of Adama District, Ethiopia , 2012. LAP LAMBERT Academic Publishing. ISBN: 978-3-659-21160- 7 .Deutschland / Germany. Kibrom Hailu T., Nesru M. Evaluation of Solid Waste Dumping Site using GIS & MCE A case study of Addis Ababa, Ethiopia, 2016. LAP LAMBERT Academic Publishing. ISBN: 978-3-659- 91076-0 . Deutschland / Germany. Conference Experience South East Asia Survey Congress June 18 - 20, 2013, Manila, Phillipiness "Spatially- Enabled Society I, Technical Session-I, participated as technical speaker. Federation of International Geodesy (FIG) Surveyor, Training on Reference Frame in Practice, Commission-5: Positioning and Measurement, June 21-22, 2013, Manila, Phillipiness. Reasarch Practice Solid Waste Dumping Site Selection using Multi Criteria Evaluation (MCE) and GIS techniques for Adama Municipality, Ethiopia, 2010. Safe removal of Solid Waste using Re-engineered design of inclination of chimney for Adama Science and Technology University, Ethiopia, 2012. Assessment of flood risk using Geographic Information System (GIS): a case study of kebele 09 in adama city Assessment of sedimentation risk of lake koka using Geographic Information System (GIS) Soil Erosion prediction, prioritization and managment employing SWAT and RUSLE model using Geospatial techniques in Awash watershed Modeling fish biomass for availability and optimal fishing rate in lake Awassa using Remote 9/30/2016 3:36:41 PM 2 Sensing and Geographic Information System (GIS)
Presentation out line • Introduction • Methods • Results and Discussions • Conclusions and Recommendations 9/30/2016 3:36:41 PM 3
Definitions and Options Risk - the Consequence of a specified hazardous event. Hazard - a situation with a potential for harm. Elements at Risk - Human population living in a geographical area where locally acquired malaria cases occur. Vulnerability - is the exposure of a given element. Malarias – the area affected by malaria 9/30/2016 4
Definitions Cont’d Risk assessment - Overall process of risk analysis GIS - set of tools for collecting, storing, retrieving, transforming, and displaying spatial data from the real world for a particular set of purposes. Rescaling Option: 1 to 5 by 1, 1 implies very low level and 5 vice versa. 5 4 3 2 1 9/30/2016 3:36:41 PM 6
Introduction Malaria is the fifth leading cause of death in the world. 40% of the world's population living at risk of malaria. Malaria kills an African child every 30 seconds. Also a primary cause of poverty . More than USD12 billion loss of GDP every year. 9/30/2016 3:36:41 PM 7
Introduction Cont’d Areas below 2000 m a.m.s.l are considered as vulnerable for malaria. In Ethiopia, 68% of the total population lives in areas at risk of malaria. In Adama, 93% of the district are hazardous for malaria . The lack of geo-referenced spatial information to assess malaria hazard and risk level for administration units in the district. * a.m.s.l = above mean sea level 9/30/2016 8 3:36:41 PM
Introduction Cont’d Accordingly, Malaria prevalence is studied by considering three parameters. Hazard, vulnerability and element at risk as per Shook Risk Model (1997) the three parameters are integrated in GIS environment. *GIS – Geographical Information System. 9/30/2016 9 3:36:41 PM
Introduction Cont’d Research Questions: 1. What are the malaria hazard and risk level of Adama district in general ? 2. What are the malaria hazard and risk level each kebele and land use ? 9/30/2016 3:36:41 PM 10
Introduction Cont’d Objectives: To assess malaria risk in Adama District using GIS . To develop spatial model for designing the malaria hazard and risk level assessment. To prepare malaria hazard and risk map of Adama District. To produce tabulated data areas of malaria risk and hazard maps with land use and kebele layers respectively. 9/30/2016 3:36:41 PM 11
Study area General Description • Study area: Adama District • Location (511737.875, 910052.511)min (546432.813, 964326.375)max • Altitude: 1500 to 2300m a.m.s.l • Area is 77779ha. • Mean annual rainfall of 740mm . • Temperature ranges 10 o c to 32 o c. 12 9/30/2016 3:36:41 PM
Methods Factor development: By a common rescaling option the causative factors were developed for malaria prevalence. Hazard ( Agro-Ecology distance ) , Zone, Soil, Slope and River Vulnerability ( Wetness-index, Land Use and Lake distance) , Element at risk ( Population ) and Risk were developed and analyzed. Over lay analysis: Taking head of Shook Risk Model the 3 parameters were overlaid. MR = MH x V x Er *MR = Malaria Risk *MH = Malaria Hazard , *V = Vulnerability , *Er = Element at risk 13 9/30/2016 3:36:41 PM
DEM AEZ Soil River Slope Rasterization Schematic representation of Slope AEZ River Soil malaria risk analysis Reclassification Euclidean Distance Slope AEZ Soil River Reclassification Weighted Overlay DEM River Malaria Weighted Overlay Lake Hazard Weighted Overlay Reclassification Map WI WI Malaria Risk Malaria Euclidean LU Map LU Vulnerability Map Lake Lake Element at Risk Population Pop. IDW Density Reclassification 9/30/2016 3:36:41 PM 14
Methods Tabulation area analysis: The generated outputs of Adama District malaria risk assessment were cross tabulated with Kebele & LU for further investigations. Tabulate Tabulate Land Area Area Use Hazard Vs Risk LU Vs LU Malaria Risk Malaria Risk Tabulate Vs Hazard Area Kebele Hazard Vs Kebele Kebele Tabulate Area 9/30/2016 3:36:41 PM 15 *LU = Land Use, *Kebele = small administration unit * Vs = inter comparison
Results and Discussions There are spatial overlay analysis and tabulation area analysis results generated in the research. Spatial overlay analysis Result : 1. Malaria Hazard Assessment 0.1% of the area is rated as low hazardous due to coarse texture soils ( like pheozems ) and steep slope factors . 84.87% of the area is rated as high to very high hazardous due to soils with heavy or clay textured ( Mollic & Vertic Andosols ) and AEZ ( warm-semi arid & warm-sub moist lowlands ) factors. *AEZ = Agro Ecology Zone 9/30/2016 3:36:41 PM 16
Results Cont’d Malaria Hazard Assessment The Consistency Ratio was 0.07 , Which is acceptable as the values <= 0.1 W AEZ =54% W SLOPE =28% Ranks of Hazard level Hazard Area (ha) (%) Low 78.910243 0.10 Moderate 11682.596 15.02 W SOIL =12% W RD =6% High 45084.179 57.96 Very High 20933.315 26.91 9/30/2016 3:36:41 PM 17 Total Area 77779 100
Results Cont’d 2. Malaria Risk Assessment Low malaria risk areas ( 68.97% ) are highly influenced by elements at risk ( due to less population density ) factor level . 30.97% of the area is rated as moderate to very high risk areas. due to the associated hazard & element at risk level. 9/30/2016 3:36:41 PM 18
Results Cont’d Malaria Risk Assessment All factors have equal weight of importance Ranks of Risk Area (ha) Risk (%) Very Low 49.14 0.06 Low 53641.75 68.97 Moderate 22951.41 29.51 High 1136.51 1.46 Very High 0.19 0.00024 9/30/2016 3:36:41 PM 19 Total Area 77779 100
Results Cont’d Tabulation area analysis Result: 1. Hazard Vs Land Use 87% to 91% of the high & very high hazard level areas are covered by cultivated land . Grassland ( 42%) has the lowest value that reduce the hazard level due to the limiting slope factor. Water (0%) has got the lowest value under very high category due to the nature of water bodies. 9/30/2016 3:36:41 PM 20
Results Cont’d Low Moderate High Very High Area Id Land Use (ha) % Area (ha) % Area (ha) % Area (ha) % Shrub 1 Land 0 0 0 0 3332.67 7.38 1462.71 6.99 Grass 2 Land 0 0 0 0 181.15 0.40 252.23 1.21 Cultivated 3 Land 75.85 100 10985.68 94.29 39334.95 87.14 19194.61 91.80 4 Water 0 0 665.73 5.71 2293.38 5.08 0 0 Hazard Vs Land Use 9/30/2016 3:36:41 PM 21
Results Cont’d 2. Hazard Vs Kebele According to ADHO , only three kebeles Bubisa Kusaya, Laku Balchi, and Mukiye Haro are found to be non-malarias. All the rest 38 kebeles to be malarias ones. *ADHO = Adama District Health Office 9/30/2016 3:36:41 PM 22
Results Cont’d due to the distance from river and soil factors influence on malaria hazard The study confirms that only Bubisa Kusaya and laku Balchi are non-malarias all the rest 39 kebeles are malarias. This shows that the study result is in strong agreement with the official data. 9/30/2016 3:36:41 PM 23
Results Cont’d 3. Malaria Risk Vs Land Use 99% of Shrub land & grassland are categorized under low risk level due to less population density in the area. 79% Cultivated land & 78% water bodies are categorized under moderate risk level due to the higher population density . 9/30/2016 3:36:41 PM 24
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