Tracing Tuberculosis: A comprehensive evaluation of surveillance system performance in Kendari District, Southeast Sulawesi

Tuberculosis (TB) remains a major public health challenge in Indonesia, highlighting the need for a robust and responsive surveillance system to guide effective control strategies. This study aimed to evaluate the performance of the TB surveillance system at Puskesmas Wua-Wua by assessing its input, process, output components, and surveillance attributes. A descriptive qualitative design was employed, using total sampling to recruit key and general informants involved in TB program implementation. Data were collected through semi-structured interviews, direct observation, and document review, and analyzed using Miles and Huberman’s interactive model with methodological and source triangulation to enhance data credibility. The findings show that digital transformation through the SITB platform has substantially improved data processing, reporting efficiency, and timeliness, enabling real-time access to surveillance information and supporting evidence-based decision-making. Several surveillance attributes including simplicity, flexibility, completeness, and timeliness performed strongly, and structured validation mechanisms supported data quality. However, the most critical gaps were observed in the input components: limited human resource capacity, dual workloads, insufficient certified training, and inadequate funding for essential operational needs. These constraints hindered optimal data validity, analytical capacity, and long-term system sustainability. Although reporting and cross-sectoral collaboration largely complied with national regulations, the absence of epidemiological analysis at the health center level and logistical shortages indicated areas requiring strengthening. Despite notable digital progress, the TB surveillance system’s effectiveness relies on strengthened workforce capacity, sustainable financing and improved interfacility coordination to ensure a system that is both technologically advanced and operationally resilient.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-12-31
DOI
https://doi.org/10.5281/zenodo.18336397
Primary Topic
Data-Driven Disease Surveillance
Type
article
Field-Weighted Citation Impact
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article

Tracing Tuberculosis: A comprehensive evaluation of surveillance system performance in Kendari District, Southeast Sulawesi

Listy Handayani, Sri Tungga Dewi, Siti Nurfadilah H
Zenodo (CERN European Organization for Nuclear Research)
Data-Driven Disease Surveillance
article

Tracing Tuberculosis: A comprehensive evaluation of surveillance system performance in Kendari District, Southeast Sulawesi

Listy Handayani, Sri Tungga Dewi, Siti Nurfadilah H
article en

Abstract

Tuberculosis (TB) remains a major public health challenge in Indonesia, highlighting the need for a robust and responsive surveillance system to guide effective control strategies. This study aimed to evaluate the performance of the TB surveillance system at Puskesmas Wua-Wua by assessing its input, process, output components, and surveillance attributes. A descriptive qualitative design was employed, using total sampling to recruit key and general informants involved in TB program implementation. Data were collected through semi-structured interviews, direct observation, and document review, and analyzed using Miles and Huberman’s interactive model with methodological and source triangulation to enhance data credibility. The findings show that digital transformation through the SITB platform has substantially improved data processing, reporting efficiency, and timeliness, enabling real-time access to surveillance information and supporting evidence-based decision-making. Several surveillance attributes including simplicity, flexibility, completeness, and timeliness performed strongly, and structured validation mechanisms supported data quality. However, the most critical gaps were observed in the input components: limited human resource capacity, dual workloads, insufficient certified training, and inadequate funding for essential operational needs. These constraints hindered optimal data validity, analytical capacity, and long-term system sustainability. Although reporting and cross-sectoral collaboration largely complied with national regulations, the absence of epidemiological analysis at the health center level and logistical shortages indicated areas requiring strengthening. Despite notable digital progress, the TB surveillance system’s effectiveness relies on strengthened workforce capacity, sustainable financing and improved interfacility coordination to ensure a system that is both technologically advanced and operationally resilient.

Zenodo (CERN European Organization for Nuclear Research)
Universitas Halu Oleo (ID)
Openalex Percentile: Top 27%
Data-Driven Disease Surveillance
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