The Spatial Distribution of Pulmonary Tuberculosis in Kabanjahe District, Karo Regency, Indonesia

Tanjung, Risnawati; Mahyuni, Eka Lestari; Tanjung, Nelson; Simarmata, Oster Suriani; Sinaga, Jernita; Nolia, Helfi

doi:10.3889/oamjms.2021.6808

Cited by 2 publications

(1 citation statement)

References 25 publications

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“…Another study in Indonesia found that the dominant factor in the incidence of tuberculosis is humidity. Houses that have ineligible humidity are at risk of developing tuberculosis by 3.1 times compared to houses that have sufficient humidity [12]. Another study in Semarang found that people living in homes with ineligible humidity are more at risk of contracting…”

Section: Resultsmentioning

confidence: 99%

Prediction of pulmonary tuberculosis incidence based on epidemiological triad as a preventive measure

Sutriyawan,

Anri,

Imbar

et al. 2023

IJPHS

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The decline in the incidence of tuberculosis to date still looks very slow, although some efforts have been made to improve case identification and treatment adherence. This study aimed to assess the factors associated with the incidence of pulmonary tuberculosis. The research design for this study was observational analytical with a cross-sectional design. A total of 830 people suspected of tuberculosis, aged over 15 years, and not drug-resistant were selected by simple random sampling. Overall, 59.9% of people are infected with pulmonary tuberculosis. There was a significant association between age (p=0.002) (OR=1.69; 95% CI: 1.22, 2.35), smoking behavior (p=0.000) (OR=2.3; 95% CI: 1.67, 3.30), temperature (p=0.000) (OR=4.2; 95% CI: 2.84, 6.47), humidity (p=0.000) (OR=6.7; 95% CI: 4.69, 9.77), lighting (p=0.000) (OR=4.174; 95% CI: 2.94, 5.92) and incidence of pulmonary tuberculosis. The study showed that tuberculosis was more common among productive age and smokers living in homes with unqualified temperature, humidity, and lighting. Room humidity is the most associated factor with the incidence of pulmonary tuberculosis. Therefore, education on the importance of paying attention to the physical environment of the house to avoid pulmonary tuberculosis is highly recommended.

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Section: Resultsmentioning

confidence: 99%

Prediction of pulmonary tuberculosis incidence based on epidemiological triad as a preventive measure

Sutriyawan,

Anri,

Imbar

et al. 2023

IJPHS

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Geo-spatial high-risk clusters of Tuberculosis in the global general population: a systematic review

Teibo,

Andrade,

Rosa

et al. 2023

BMC Public Health

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Introduction The objective of this systematic review is to identify tuberculosis (TB) high-risk among the general population globally. The review was conducted using the following steps: elaboration of the research question, search for relevant publications, selection of studies found, data extraction, analysis, and evidence synthesis. Methods The studies included were those published in English, from original research, presented findings relevant to tuberculosis high-risk across the globe, published between 2017 and 2023, and were based on geospatial analysis of TB. Two reviewers independently selected the articles and were blinded to each other`s comments. The resultant disagreement was resolved by a third blinded reviewer. For bibliographic search, controlled and free vocabularies that address the question to be investigated were used. The searches were carried out on PubMed, LILACS, EMBASE, Scopus, and Web of Science. and Google Scholar. Results A total of 79 published articles with a 40-year study period between 1982 and 2022 were evaluated. Based on the 79 studies, more than 40% of all countries that have carried out geospatial analysis of TB were from Asia, followed by South America with 23%, Africa had about 15%, and others with 2% and 1%. Various maps were used in the various studies and the most used is the thematic map (32%), rate map (26%), map of temporal tendency (20%), and others like the kernel density map (6%). The characteristics of the high-risk and the factors that affect the hotspot’s location are evident through studies related to poor socioeconomic conditions constituting (39%), followed by high population density (17%), climate-related clustering (15%), high-risk spread to neighbouring cities (13%), unstable and non-random cluster (11%). Conclusion There exist specific high-risk for TB which are areas that are related to low socioeconomic conditions and spectacular weather conditions, these areas when well-known will be easy targets for intervention by policymakers. We recommend that more studies making use of spatial, temporal, and spatiotemporal analysis be carried out to point out territories and populations that are vulnerable to TB.

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The Spatial Distribution of Pulmonary Tuberculosis in Kabanjahe District, Karo Regency, Indonesia

Cited by 2 publications

References 25 publications

Prediction of pulmonary tuberculosis incidence based on epidemiological triad as a preventive measure

Prediction of pulmonary tuberculosis incidence based on epidemiological triad as a preventive measure

Geo-spatial high-risk clusters of Tuberculosis in the global general population: a systematic review

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