Spatial Analysis of Tuberculosis in Sleman by Using Geographic Information System (GIS)
ABSTRACT
Wawan Kusugiharjo, Hari Kusnanto
Background : There are some problems in prevention of Tuberculosis cases in Sleman, especially in finding cases coverage of positive LUNG terbium BTA. This is caused by lack of support from the policy makers. This condition affects the organizers of the program and paramedics become unmotivated, so that the goals could not be reached. Nowadays, finding cases coverage has reached number of 50% and this condition probably derived the increasing of Lung TB infection risk in Sleman and it is predicted that a patient with positive Lung TB can infect other 10 persons in a year. From the explanation above, this study combined some variables that could affect Lung TB cases; they were density, poverty, and health service facilities. By using spatial factor analyzes, this study, hopefully, can be used as the consideration in policy making of Lung TB prevention at Sleman.
Objective: The study was aimed to find out the relationship between density, poorness and supporting facilities to health service of LUNG terbium BTA (+) case in District of Sleman.
Methods : A cross sectional survey was held in Sleman, Yogyakarta. The population was area population that involved area segments in all research units (the overall of Sleman areas) and all LUNG terbium BTA (+) cases during 2005 (387 cases). Independent variables were density, poverty, and facilities of health service. Meanwhile, dependent variable was LUNG terbium BTA (+) case.
Data analysis : Spatial analysis of SaTScan was used to find out LUNG terbium BTA (+) clusters, Excel Distcalc was used to measure distance between patient’s residence to the health service facilities, and spatially weighted regression analysis of GeoDa was used to find out the relationship among independent variables and dependent variables.
Results : Analysis of spatially weighted regression (spatial errors model) showed that density was related to LUNG terbium BTA(+) cases (t= -1,992 p = 0,049); LUNG terbium BTA(+) case was not related to poverty (t= -0,667 p = 0,506 ( p>0,05)); and LUNG Terbium BTA (+) was not based on current spatial distribution pattern (p= 0,622 (p>0,05)). From the Space-Time Permutation Model (Likelihood Ratio Test), it was obtained 8 clusters. First cluster happened on January 1, 2005 until January 31, 2005 with coordinate point of (- 7.767990 s, 110.391840 E) and radius of 2,18 km. Meanwhile, the Most Likely Cluster was cluster which happened on March 1,2005 until March 31, 2005 with coordinate point of (- 7.641750 sulfur, 110.382630 E) and radius of 2,11 km
Conclusion : LUNG terbium BTA (+) case did not associate with poverty, but it associated with density. There were significant clustering of LUNG terbium disease BTA(+) cases in Sleman. Cluster of LUNG terbium BTA(+) cases tended to follow high density pattern, not to follow poverty based on administration.
Keywords : LUNG terbium BTA(+) case, density, Poverty, facilities of health services, Geographic Information System.