Spatial Epidemiological Analysis of Drug-Resistant Tuberculosis in Indonesia: A Digital Surveillance Approach Using Tableau
DOI:
https://doi.org/10.30953/thmt.v11.654Keywords:
drug-resistant tuberculosis, Indonesia, Tableau Software, unfavorable treatment outcomesAbstract
Background: Drug-resistant tuberculosis (DR-TB) is a significant public health threat in Indonesia, one of the five countries with the highest disease burden globally.
Methods: The authors identify and analyze the geographical clustering patterns of DR-TB and unfavorable treatment outcomes in Indonesia, using a spatial epidemiological approach and digital data visualization techniques. This retrospective study used secondary data from DR-TB patients in the Tuberculosis Information System (SITB) between 2020 and 2024. Treatment outcome data (cured, treatment completed, died, failed, and lost to follow-up) were visualized using Tableau Software to map disease distribution, identify hotspots, and analyze spatiotemporal trends.
Results: The results revealed a heterogeneous geographical distribution of DR-TB, with significant clustering in densely populated urban areas, particularly on Java Island (West Java, East Java, Central Java, and DKI Jakarta) and in North Sumatra. The national rate of unfavorable treatment outcomes was alarmingly high at 54.36%. A notable drop in reported cases in 2023, likely an artifact of pandemic-related surveillance disruptions, was followed by a sharp increase in mortality in 2024. Microspatial analysis within West Java Province further revealed district-level variations in the dominant types of unfavorable outcomes.
Conclusions: The DR-TB epidemic in Indonesia is spatially driven, characterized by significant clustering and systemic treatment failures. The findings reported here confirm that the DR-TB epidemic in Indonesia is driven by sociodemographic and health system factors manifested in an uneven spatial pattern. Spatial epidemiology, supported by digital technology, can be an effective tool for identifying priority areas, optimizing resource allocation, and designing more focused and impact.
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Copyright (c) 2026 Farida Murtiani, M.Stat, Mondastri Korib Sudaryo, PhD, Evi Martha DrPH, Diah Handayani, SpP, PhD
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