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All Journal Media Publikasi Promosi Kesehatan Indonesia (MPPKI) Journal of Public Health and Pharmacy
M. Ischaq Nabil Asshiddiqi
School of Nursing, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong
Medicine & Pharmacology Public Health

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Unveiling Tuberculosis Dynamics in Indonesia for Effective Control and Prevention: A Panel Regression and Clustering Approach Novi Reandy Sasmita; Mutiara Syifa; Mhd Khairul; Latifa Rahayu; Zurnila Marli Kesuma; Selvi Mardalena; Rumaisa Kruba; Virasakdi Chongsuvivatwong; M. Ischaq Nabil Asshiddiqi
Journal of Public Health and Pharmacy Vol. 6 No. 2 (2026)
Publisher : Pusat Pengembangan Teknologi Informasi dan Jurnal Universitas Muhammadiyah Palu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56338/jphp.v6i2.7265

Abstract

Introduction: Tuberculosis (TB) remains a critical global health challenge, with Indonesia ranking second in global TB burden. This study examines factors influencing TB incidence across Indonesian provinces and applies clustering to guide targeted interventions aligned with TB eradication goals by 2030. Specifically, these findings inform Indonesia’s End TB 2030 roadmap by identifying provincial heterogeneity that necessitates differentiated resource allocation and strengthened health governance frameworks. Methods: This ecological time-series study design analyzed data from 34 Indonesian provinces (2020–2022), including TB cases, healthcare services, HIV cases, smoking prevalence, food management places, and public facilities. Descriptive statistics summarized variable distribution, while panel data regression identified key factors using multicollinearity checks, model selection, and assumption testing. Fuzzy Possibilistic C-Means (FPCM) clustering grouped provinces based on similarity characteristics. Results: TB cases rose from 10,351 in 2020 to 21,303 in 2022. This study underscores the multifaceted factors influencing TB incidence in Indonesia. Significant factors included healthcare services (?1 = -8.37), HIV cases (?2 = 13.76), smoking prevalence (?3 = 905.32), food management places (?4 = 1.62), and public facilities (?5 = 1.11). This study proves that TB is not only influenced by health factors but also by non-health factors. Fuzzy clustering using the FPCM identified three clusters based on their possibilistic membership degrees: Cluster 3, with high HIV prevalence and public facilities, requiring urgent action; Cluster 2, needing improved healthcare and smoking reduction; and Cluster 1, with moderate challenges. Conclusions: Health and environmental factors significantly influence TB incidence. Addressing cluster-specific needs, such as enhancing healthcare, reducing HIV and smoking prevalence, and improving public health standards, is essential for TB control. Future studies should expand variables and periods to deepen insights.
Relative Risk and Distribution Assessment of Tuberculosis Cases: A Time-Series Ecological Study in Aceh, Indonesia Novi Reandy Sasmita; Mhd Khairul; Mumtaz Kemal Fikri; Latifa Rahayu; Zurnila Marli Kesuma; Selvi Mardalena; Rumaisa Kruba; Virasakdi Chongsuvivatwong; M. Ischaq Nabil Asshiddiqi
Media Publikasi Promosi Kesehatan Indonesia (MPPKI) Vol. 8 No. 6 (2025)
Publisher : Fakultas Kesehatan Masyarakat, Universitas Muhammadiyah Palu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56338/mppki.v8i6.7264

Abstract

Introduction: Tuberculosis (TB) remains a critical public health issue, particularly in high-incidence regions like Aceh Province, Indonesia. This study aimed to estimate the Relative Risk (RR) and analyze significant differences in the temporal distribution of TB cases across Aceh Province. Methods: A time-series ecological study was conducted using TB case and population data from 23 districts/cities in Aceh Province between 2016 and 2022. Data were analyzed using R software, applying descriptive and inferential statistics. The Standardized Morbidity Ratio (SMR) method estimates RR and is categorized into five risk levels. The Kolmogorov-Smirnov test assessed data normality, guiding the selection of statistical tests. The Friedman and Wilcoxon Signed-Rank tests examined differences in TB case distribution trends. Results: Significant spatial and temporal variations in TB risk were identified. Districts such as Banda Aceh (RR = 2.29–2.13) and Lhokseumawe (RR = 1.89–2.21) consistently demonstrated high RR from 2016 to 2022, reflecting persistent TB transmission. A general upward trend in TB cases was observed across districts, with significant spatial variation (p < 0.001), highlighting a worsening TB burden. Conclusions: The study emphasizes the urgent need for targeted public health interventions tailored to TB's unique spatial and temporal dynamics in Aceh Province, Indonesia. Applying SMR and robust statistical analyses provides valuable insights to inform localized TB control policies and strengthen management strategies in high-burden areas.
A Stochastic Projection for Tuberculosis Elimination in Indonesia by 2030 Novi Reandy Sasmita; Maya Ramadani; Muhammad Ikhwan; Munawwarah Munawwarah; Latifah Rahayu; Selvi Mardalena; M. Ischaq Nabil Asshiddiqi; Suyanto Suyanto; Nanda Safira
Media Publikasi Promosi Kesehatan Indonesia (MPPKI) Vol. 8 No. 11 (2025)
Publisher : Fakultas Kesehatan Masyarakat, Universitas Muhammadiyah Palu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56338/mppki.v8i11.8548

Abstract

Introduction: Indonesia, with the world's second-highest tuberculosis (TB) burden, has targeted TB elimination (65 cases per 100,000) by 2030. This study aimed to evaluate the feasibility of achieving this goal by projecting TB incidence trends using a stochastic epidemic model that accounts for the uncertainties inherent in TB transmission dynamics in latent TB infections. Methods: The initial values for state variables and parameters were derived from a comprehensive literature review and calibrated against publicly available epidemiological data from the Indonesian Ministry of Health reports from 2018-2022. A Susceptible, Vaccinated, Three Exposed, Three Infectious, Recovered (SVE3I3R) model was developed, incorporating Gaussian noise into the exposed compartments to simulate real-world unpredictability in latent infection dynamics. The model was solved numerically using the fourth-order Runge-Kutta (RK4) method in R software. Key outcomes measured were the projected incidence of drug-susceptible TB (DS-TB), multidrug-resistant TB (MDR-TB), and extensively drug-resistant TB (XDR-TB). Results: Model projections suggest that the overall TB incidence rate will fall from 387 cases per 100,000 people in 2023 to a projected 320 cases per 100,000 by 2030. However, this remains far above the national target. While DS-TB cases decreased to 730,283, MDR-TB and XDR-TB cases were projected to surge dramatically to 120,939 cases and 104,651 individuals, respectively. The estimation signals a critical shift in the epidemic's profile. Conclusions: Indonesia is not on track to achieve its 2030 TB elimination target under current interventions. The alarming rise of drug-resistant TB necessitates an urgent, aggressive, and multifaceted policy response. This study underscores the critical value of incorporating stochasticity into epidemiological models for more realistic forecasting and public health planning in high-burden settings.
Co-Authors Latifa Rahayu Latifah Rahayu Maya Ramadani Mhd Khairul Muhammad Ikhwan Mumtaz Kemal Fikri Munawwarah Munawwarah Mutiara Syifa Nanda Safira Novi Reandy Sasmita Rumaisa Kruba Selvi Mardalena Suyanto Suyanto Virasakdi Chongsuvivatwong Zurnila Marli Kesuma