Tuberculosis in Aceh Province, Indonesia: a spatial epidemiological study covering the period 2019–2021

The purpose of this study was to determine whether there were any TB clusters in Aceh Province, Indonesia and their temporal distribution during the period of 2019-2021. A spatial geo-reference was conducted to 290 sub-districts coordinates by geocoding each sub-district's offices. By using SaTScan TM v9.4.4, a retrospective space-time scan statistics analysis based on population data and annual TB incidence was carried out. To determine the regions at high risk of TB, data from 1 January 2019 to 31 December 2021 were evaluated using the Poisson model. The likelihood ratio (LLR) value was utilized to locate the TB clusters based on a total of 999 permutations were performed. A Moran's I analysis (using GeoDa) was chosen for a study of both local and global spatial autocorrelation. The threshold for significance was fixed at 0.05. At the sub-district level, the spatial distribution of TB in Aceh Province from 2019-2021 showed 19 clusters (three most likely and 16 secondary ones), and there was a spatial autocorrelation of TB. The findings can be used to provide thorough knowledge on the spatial pattern of TB occurrence, which is important for designing effective TB interventions.

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Publication Details

Journal
Geospatial health
Published
2024-09-03
DOI
https://doi.org/10.4081/gh.2024.1318
Citations
2
Primary Topic
Tuberculosis Research and Epidemiology
Type
article
Field-Weighted Citation Impact
0.78
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article

Tuberculosis in Aceh Province, Indonesia: a spatial epidemiological study covering the period 2019–2021

Elpiani Depari, Farrah Fahdhienie, Frans Yosep Sitepu
2 citations
Geospatial health
Tuberculosis Research and Epidemiology
0.78
article

Tuberculosis in Aceh Province, Indonesia: a spatial epidemiological study covering the period 2019–2021

Elpiani Depari, Farrah Fahdhienie, Frans Yosep Sitepu
article en
2 citations

Abstract

The purpose of this study was to determine whether there were any TB clusters in Aceh Province, Indonesia and their temporal distribution during the period of 2019-2021. A spatial geo-reference was conducted to 290 sub-districts coordinates by geocoding each sub-district's offices. By using SaTScan TM v9.4.4, a retrospective space-time scan statistics analysis based on population data and annual TB incidence was carried out. To determine the regions at high risk of TB, data from 1 January 2019 to 31 December 2021 were evaluated using the Poisson model. The likelihood ratio (LLR) value was utilized to locate the TB clusters based on a total of 999 permutations were performed. A Moran's I analysis (using GeoDa) was chosen for a study of both local and global spatial autocorrelation. The threshold for significance was fixed at 0.05. At the sub-district level, the spatial distribution of TB in Aceh Province from 2019-2021 showed 19 clusters (three most likely and 16 secondary ones), and there was a spatial autocorrelation of TB. The findings can be used to provide thorough knowledge on the spatial pattern of TB occurrence, which is important for designing effective TB interventions.

Geospatial healthVol. 19(2)
Yahoo (Spain) (ES), Universitas Muhammadiyah Jember (ID), Universitas Muhammadiyah Aceh (ID), Faculty of Public Health (GB), Universitas Islam Negeri Sumatera Utara (ID)
Good health and well-being
Openalex Percentile: Top 28%
Tuberculosis Research and Epidemiology
0.78
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