Predicting Tuberculosis Vulnerability Based on Environmental Factors Using Multi-Criteria Analysis in Bukittinggi
Tuberculosis is still an infectious disease problem and the main cause of death in Indonesia, where there was an increase in cases from 301 per 100,000 population (2020) to 354,000 per 100,000 population (2021), with the death rate increasing by 55%. This research aims to determine the TB vulnerability cluster influenced by the main risk factors, namely TB prevalence, cure rate, immunization, population density, and population arrivals in Bukittinggi, using the Weight Product (WP) analysis method, and then describe them by mapping tuberculosis vulnerability. The findings indicate that four sub-districts exhibit the highest levels of tuberculosis vulnerability: Tarok Dipo (0.0379), Campago Guguk Bulek (0.0399), Campago Ipuh (0.0399), and Aur Tajungkang Tangah Sawah (0.0389). A multi-sectoral TB control committee comprising public works, environmental, and health agencies should be formed to organize and carry out focused actions. Establish a strong TB surveillance system that includes contact tracing, active case finding, and routine monitoring of important indicators. Create and implement specialized intervention packages for high-vulnerability subdistricts, including social support programs, housing rehabilitation, and air quality control.
Authors
- Nurhasan Syah (ORCID: https://orcid.org/0000-0003-0264-5884)
- Linda Handayuni (ORCID: https://orcid.org/0000-0002-5859-5110)
- Iswandi Umar (ORCID: https://orcid.org/0000-0003-2230-3806)
- Indang Dewata (ORCID: https://orcid.org/0000-0001-9725-1372)
- Evi Hasnita (ORCID: https://orcid.org/0009-0004-7698-0153)
- Eka Budi Satria
Institutions
- State University of Padang (ID)
- Universitas Bung Hatta (ID)
- Universitas Islam Negeri Sjech M. Djamil Djambek Bukittinggi (ID)
- Universitas Dharmas Indonesia (ID)
Publication Details
- Journal
- Media Kesehatan Masyarakat Indonesia
- Published
- 2024-12-31
- DOI
- https://doi.org/10.30597/mkmi.v20i4.36887
- Citations
- 2
- Primary Topic
- Data Mining and Machine Learning Applications
- Type
- article
- Field-Weighted Citation Impact
- 1.56
Funders
- Universitas Negeri Padang