Investigating Spatial Patterns of Pulmonary Tuberculosis and Main Related Factors in Bandar Lampung, Indonesia Using Geographically Weighted Poisson Regression

Abstract

Tuberculosis (TB) is a highly infectious disease, representing one of the major causes of death worldwide. Sustainable Development Goal 3.3 implies a serious decrease in the incidence of TB cases. Hence, this study applied a spatial analysis approach to investigate patterns of pulmonary TB cases and its drivers in Bandar Lampung (Indonesia). Our study examined seven variables: the growth rate of pulmonary TB, population, distance to the city center, industrial area, green open space, built area, and slum area using geographically weighted Poisson regression (GWPR). The GWPR model demonstrated excellent results with an R2 and adjusted R2 of 0.96 and 0.94, respectively. In this case, the growth rate of pulmonary TB and population were statistically significant variables. Spatial pattern analysis of sub-districts revealed that those of Panjang and Kedaton were driven by high pulmonary TB growth rate and population, whereas that of Sukabumi was driven by the accumulation of high levels of industrial area, built area, and slums. For these reasons, we suggest that local policymakers implement a variety of infectious disease prevention and control strategies based on the spatial variation of pulmonary TB rate and its influencing factors in each sub-district.

Keywords

• infectious disease
• epidemiology
• health
• geographic information system
• spatial science
• geostatistics