| dc.description.abstract | Abstract
The coronavirus disease 2019 (COVID-19) pandemic has presented significant challenges to global public health systems, potentially impeding the progress in Tuberculosis (TB) elimination efforts. Indonesia, a country burdened with high Tuberculosis prevalence, faces additional obstacles due to the current COVID-19 situation. Hence, the impact COVID-19 pandemic on the spread of Tuberculosis becomes a noticeable issue in Indonesia. This study aims to investigate the spatial patterns of Tuberculosis before and during the COVID-19 pandemic in Yogyakarta City and to explore the relationships between selected environmental and socioeconomic factors and Tuberculosis incidence. To analyze the TB spatial pattern in the study area, the geocoding method was used to convert the text-based Tuberculosis cases, from 2018 to 2021 into geo-coordinates. This spatial dataset was then used to understand the characteristic of TB spatial patterns using cluster analysis. Also, this study uses selected critical environmental and socioeconomic factors to correlate the spatial distribution of Tuberculosis hotspots. This study considers seven factors that are known as important factors relating to the spread of Tuberculosis. They are environmental factors, including land cover, building density, land surface temperature (LST), vegetation density, and socioeconomic factors, including health facility accessibility, population density, and tax income. For the collection of the environmental factors, remote sensing techniques were employed, such as land cover classification, LST estimation, and vegetation density mapping. The results show that (1) the clustering of Tuberculosis is a common phenomenon during the study period, whether before or during the pandemic; (2) the hotspots in the city generally persisted in the center and western areas, and these areas during the pandemic showed a greater clustering significance; and (3) during the pandemic, environmental and socioeconomic has a different correlation to the Tuberculosis incidence: tax income and land surface temperature have the greater negative correlations (-0.55 and -0.36), and among all factors, only NDVI has a positive correlation (0.16). The results of this study explore the areas where the possibility of Tuberculosis transmission is higher and have a better understanding of how the COVID-19 pandemic affects the Tuberculosis spatial patterns in Yogyakarta City, which can assist the local government to have better public health policies in the Tuberculosis transmission prevention practice in the future.
Keywords: Tuberculosis, GIS, COVID-19, Geocoding, Clustering Analysis | en_US |