water sources, infrastructure, space and the dynamics of ...

Water sources, infrastructure, space and the dynamics of environmental diseases in Saboba District: Using GISTable 11: Criteria for Interpreting Correlation. Source: Cohen (1988)Correlation Negative PositiveSmall −0.3 to −0.1 0.1 to 0.3Medium −0.5 to −0.3 0.3 to 0.5Large −1.0 to −0.5 0.5 to 1.0Method usedDistances to major towns, roads and watercourses were extracted usingArcGIS tool – Spatial Analyst – Distance – Straight line. The resultswere saved into DBF 4 format – MS Excel and then to SPSS where thesignificance was tested using correlation (2-tailed) with the three leading(environmental) diseases (Malaria, Typhoid and RTI) in the district. Forthe purpose of this study, 0.05 levels are considered significant. It isworth noting that percentage of reported diseases to population in eacharea is used in this study, and not the raw figure. Figure 8 to 13 show thevarious map outcomes, while Table 12 shows its corresponding values.Space and environmental diseases: GIS analysisWith the aid of GIS (ArcGIS), this section analyses the relation betweenenvironmental diseases and the above mentioned spatial variables.Distances of settlements to the main town (district capital) in Saboba districtFigure 8 shows that majority of the settlements in Saboba district islocated beyond 10 km (10,000 metres) from the major town (Saboba)where the only hospital in the district is located. Poor road networks andfloods further impede movement of people to the district capital.Distances from each settlement to the major town were extracted usingGIS (results are affected by distances to major towns in neighbouringdistricts). The results are shown in column 12 of Table 12Distances of settlements to roads in Saboba districtThe research also tried to find out whether there are any relationshipbetween closeness to road and the three environmental diseases,especially RTI, through smoke and dust from moving vehicles. Thereported cases of these diseases of each settlement and its correspondentdistances to the nearest vertices of a road are shown in the map in Figure9, and its values in column 8,9,10 and 13 in Table 12. The outcome isimputed into SPSS to find correlation between the two variables, and theresults shown and analysed later in this section.Distances of settlements to rivers in Saboba districtFigure 10 depicts distances of each settlement with respect to the nearestriver course (excluding streams, lakes and dams). A number of thesettlements are located within 6 km (6000 metres) from the rivers. Theassumption/analogy is that the more closer a settlement is to a river, thehigher the rates of water-related diseases – example, malaria.Distances of settlements to watercourses in the Saboba districtFigure 11 shows distances of each settlement with respect to the nearestwatercourse (stream, lake, dam etc). The reported disease values of eachsettlement and its correspondent distance to watercourses are shown incolumn 8,9,10 and 14 in Table 12. Majority of the settlements are locatedwithin 3 km (3000 metres) to the nearest watercourse. However, veryfew of these water bodies provide water for the communities due to theirseasonality of flow. The analogy is that the more closer a settlement is towatercourses, the higher its risks of water-related diseases. Thisassumption was tested by correlating distances of settlements to31