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

Submitted: 6 June 2024
Accepted: 19 August 2024
Published: 3 September 2024
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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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Aceh Province Bureau of Statistics (2021) Aceh Province in Figures. Available from https://aceh.bps.go.id/id/publication/2021/02/26/632c7b89c74d88e9db9a9944/provinsi-acehdalam-angka-2021.html
Aditama W, Sitepu FY, Saputra R, 2019. Relationship between physical condition of house environment and the incidence of pulmonary tuberculosis, Aceh, Indonesia. Internat J Sci Healthc Res 4:227–31.
ArcGIS Pro, 2022. How Spatial Autocorrelation (Global Moran’s I) works. Accessed: 1 July 2022. Available from: https://pro.arcgis.com/en/pro-app/2.8/tool-reference/spatial-statistics/h-how-spatial-autocorrelation-moran-s-i-spatial-st.htm
Endy TP, Nisalak A, Chunsuttiwat S, Libraty DH, Green S, Rothman AL, Vaughn DW, Ennis FA, 2002. Spatial and temporal circulation of dengue virus serotypes : a prospective study of primary school children in Kamphaeng Phet , Thailand. 156:52–9. DOI: https://doi.org/10.1093/aje/kwf006
Fahdhienie F, Mudatsir M, Abidin TF, Nurjannah N, 2024. Risk factors of pulmonary tuberculosis in Indonesia: A case-control study in a high disease prevalence region. Narra J 4:943. DOI: https://doi.org/10.52225/narra.v4i2.943
Fahdhienie F, Sitepu FY, 2022. Spatio-temporal analysis of tuberculosis incidence in North Aceh District, Indonesia 2019-2021. Geospatial Health 17:1148. DOI: https://doi.org/10.4081/gh.2022.1148
GeoDa, 2021a. An Introduction to Spatial Data Science. Accessed: 18 June 2021. Available from: https://geodacenter.github.io/workbook/6a_local_auto/lab6a.html
GeoDa, 2021b. Download GeoDa Software. Accessed: 18 June 2021. Available from: https://geodacenter.github.io/download.html
Gwitira I, Karumazondo N, Shekede MD, Sandy C, Siziba N, Chirenda J, 2021. Spatial patterns of pulmonary tuberculosis (TB) cases in Zimbabwe from 2015 to 2018. PLoS One 16:1–15. DOI: https://doi.org/10.1371/journal.pone.0249523
Im C, Kim Y, 2021. Spatial pattern of tuberculosis (TB) and related socio-environmental factors in South Korea, 2008-2016. PLoS One 16:2008–16. DOI: https://doi.org/10.1371/journal.pone.0255727
Kibuuka D, Mpofu C, Neave P, Manda S, 2021. A spatial analysis of tuberculosis related mortality in South Africa. Int J Environ Res Public Health 18:11865. DOI: https://doi.org/10.3390/ijerph182211865
Kulldorf, M. (2005) SaTScan, SaTScanTM - Software for the spatial, temporal, and space-time scan statistics. Available from: https://www.satscan.org/
Laohasiriwong W, Puttanapong N, Luenam A, 2017. A comparison of spatial heterogeneity with local cluster detection methods for chronic respiratory diseases in Thailand. F1000Research 6:1819. DOI: https://doi.org/10.12688/f1000research.12128.1
Lee JY, Kwon N, Goo GY, Cho SI, 2022. Inadequate housing and pulmonary tuberculosis: a systematic review. BMC Public Health 22:622. DOI: https://doi.org/10.1186/s12889-022-12879-6
Maina T, Willetts A, Ngari M, Osman A, 2021. Tuberculosis infection among youths in overcrowded university hostels in Kenya: a cross-sectional study. Trop Med Health 49:100. DOI: https://doi.org/10.1186/s41182-021-00391-3
McAllister S, Wiem Lestari B, Sujatmiko B, Siregar A, Sihaloho ED, Fathania D, Dewi NF, Koesoemadinata RC, Hill PC, Alisjahbana B, 2017. Feasibility of two active case finding approaches for detection of tuberculosis in Bandung City, Indonesia. Public Health Action 7:206-11. DOI: https://doi.org/10.5588/pha.17.0026
Michelsen SW, Soborg B, Koch A, Carstensen L, Hoff ST, Agger EM, Lillebaek T, Sorensen HC, Wohlfahrt J, Melbye M, 2014. The effectiveness of bcg vaccination in preventing mycobacterium tuberculosis infection and disease in greenland. Thorax 69:851–6. DOI: https://doi.org/10.1136/thoraxjnl-2014-205688
Ministry of Health of Republic of Indonesia (2020) National guidelines of TB case management.
Novita R, Abdullah A, Hermasnyah H, 2021. Risk factors associated with pulmonary TB incidence in children in Banda Aceh. Jurnal Kesehatan Masyarakat Aceh 7(1). DOI: https://doi.org/10.37598/jukema.v7i1.1066
Pasaribu AP, Tsheten T, Yamin M, Maryani Y, Fahmi F, Clements ACA, Gray DJ, Wangdi K, 2021. Spatio-temporal patterns of dengue incidence in Medan City, North Sumatera, Indonesia. Trop Med Infect Dis 6:30. DOI: https://doi.org/10.3390/tropicalmed6010030
Provincial Health Office of Aceh (2021) Health profile of Aceh province.
QGIS (2024) QGIS. Accessed: 30 June 2024. Available from: https://www.qgis.org/download/
Richie, 2022. Spatial Autocorrelation with GeoDa, Mobile Statistik. Accessed: 1 July 2022. Available from: https://www.mobilestatistik.com/autokorelasi-spasial-dengan-geoda/
Sasilia S, Amir Z, Nasution TA, Santi DN, 2017. Relationship among same house contact with tuberculosis patients with associated risk factors in East Aceh Regency. Adv Health Sci Res doi: 10.2991/phico-16.2017.64. DOI: https://doi.org/10.2991/phico-16.2017.64
SaTScan, 2021a. SaTScan software for the spatial, temporal, and space-time scan statistics. Available from: https://www.satscan.org/download_satscan_for_win.html (Accessed: 20 June 2021).
SaTScan, 2021b. SaTScan Tutorials. Accessed: 20 June 2021. Available from: https://www.satscan.org/tutorials.html
Srivastava GN, Mishra AP, 2019. The association of household Crowding and tuberculosis incidence among women of Varanasi City: a study in medical geography. Nat Geograph J India 65:198–205.
Sweeney E, Dahly D, Seddiq N, Corcoran G, Horgan M, Sadlier C, 2019. Impact of BCG vaccination on incidence of tuberculosis disease in southern Ireland. BMC Infect Dis 19:397. DOI: https://doi.org/10.1186/s12879-019-4026-z
Trollfors B, Sigurdsson V, Dahlgren-Aronsson A, 2021. Prevalence of latent TB and effectiveness of BCG vaccination against latent tuberculosis: an observational study. Internat J Infect Dis 109:279–82. DOI: https://doi.org/10.1016/j.ijid.2021.06.045
Wang Q, Guo L, Wang J, Zhang L, Zhu W, Yuan Y, Li J, 2019. Spatial distribution of tuberculosis and its socioeconomic influencing factors in mainland China 2013–2016. Trop Med Internat Health 24:1104–1113. DOI: https://doi.org/10.1111/tmi.13289
Wang T, Xue F, Chen Y, Ma Y, Liu Y, 2012. The spatial epidemiology of tuberculosis in Linyi. pp. 0–7.
World Health Organization (WHO) (2021) Global Tuberculosis Report 2021.
World Health Organization (WHO) (2023) Tuberculosis, World Health Organization. Accessed: 2 May 2023. Available from: https://www.who.int/news-room/fact-sheets/detail/tuberculosis
Yu Y, Wu B, Wu C, Wang Q, Hu D, Chen W, 2020. Spatial-temporal analysis of tuberculosis in Chongqing, China 2011-2018. BMC Infect Dis 20:531. DOI: https://doi.org/10.1186/s12879-020-05249-3
Yue Y, Sun J, Liu X, Ren D, Liu Q, Xiao X, Lu L, 2018. Spatial analysis of dengue fever and exploration of its environmental and socio-economic risk factors using ordinary least squares: A case study in five districts of Guangzhou City. Internat J Infect Dis 75:39–48. DOI: https://doi.org/10.1016/j.ijid.2018.07.023
Zulfikar, Sitepu FY, Depari EB, Debataradja B, 2020. Space time clusters of dengue fever in Medan Municipality, North Sumatera, Indonesia. Malaysian J Public Health Med 20:543. DOI: https://doi.org/10.37268/mjphm/vol.20/no.2/art.543

How to Cite

Fahdhienie, F., Sitepu, F. Y., & Depari, E. B. (2024). Tuberculosis in Aceh Province, Indonesia: a spatial epidemiological study covering the period 2019–2021. Geospatial Health, 19(2). https://doi.org/10.4081/gh.2024.1318

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