Modeling the Prevalence of Tuberculosis in Java, Indonesia: An Ecological Study Using Geographically Weighted Regression

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I Gusti Ngurah Edi Putra
Martya Rahmaniati
Tris Eryando
Tiopan Sipahutar


There is a paucity of studies investigating the spatial pattern and factors associated with the prevalence of tuberculosis (TB) in Java. This study aimed to identify spatial autocorrelation, clusters, and factors associated with TB prevalence in Java using district- or city-level data. This was an ecological study using data from 118 districts or cities across six provinces in Java. Spatial analyses (i.e., Global Moran’s I, Local Indicator Spatial Autocorrelation [LISA], and Geographically Weighted Regression [GWR]) were used. This study found positive spatial autocorrelation of TB prevalence in Java (Global Moran’s I = .45, p = .001). Statistically significant high-high clusters (p < .05) were identified in some districts within the capital city of Jakarta, Banten, and West Java provinces. The GWR model with the Bi-square Kernel weighting function was selected as the best model to predict the prevalence of TB (R2 = 37.50%, AIC = -59.94%). Findings from the GWR model indicate that the average number of years in education, the percentages of households with floor space per capita < 8 m2 and reporting easy access to health care facilities were associated with the prevalence of TB in some districts within West and Central Java provinces. Therefore, considering district differences in factors associated with TB prevalence, locally-focused interventions are worth considering.


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I Gusti Ngurah Edi Putra, Institute of Population Health, University of Liverpool, Liverpool, United Kingdom

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