Application of Geographic Information System into Spatial Model of Tuberculocis Cases at Depansar in the Year Of 2007
ABSTRACT
Ni Nyoman Kristina, Hari Kusnanto, Anis Fuad
Background: At Province of Bali, the contagious diseases which should be alerted are the new emerging diseases and re-emerging diseases. To cover this problem, the government has developed ten national priority programs and one of them is GERDUNAS (Gerakan Terpadu Nasional) Tuberculosis. Refer to this problem, the researcher would describe several aspects which influenced the prevalence of tuberculosis (TB), such as density, poverty, urban status, and the distance to healthcare facilities. This model suggested spatial model to determine the susceptible area of TB at Denpansar.
Objectives: This study was aimed to find out the benefits of spatial model in determining level of susceptible area to TB, to find out the relationship between density and TB cases, and also to find out the association of TB clustering in the poor area, urban clusters at Denpansar, and distance to the healthcare facilities with the benefit of spatial model in improving management of TB control at the high endemic area.
Method: This study was an observational research with cross sectional approach. Data analysis used software of Geoda and SatScan for the GIS process.
Results: There was correlation between TB cases and poverty (z = = 3,502, p = 0.0004). Meanwhile density (z = -1,529, p = 0.126) and urban status (z = -1.113, p = 0.909) were not related to TB cases. The chi-square analysis also showed that there was no correlation between TB cases and distance to the healthcare facilities (x2 = 0.21, p = 0.65). Analysis of spatial dependency with Moran’s test showed the value of 0.670 (p = 0.412).
Conclusion: TB cases correlated to poverty significantly, and have no correlation with density, urban status, and distance to the healthcare facilities. Spatial distribution pattern of TB did not follow any specific pattern. Clustering of TB tended to exist in poverty area and spread following the direction of road.
Keywords: Geographic Information System, Spatial Model, Smear (+) TB