ArticleInternational journal of environmental research and public health2015
Spatial Pattern Detection of Tuberculosis: A Case Study of Si Sa Ket Province, Thailand.
Article in International journal of environmental research and public health, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.
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Who cites it
12 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Methods used in the spatial analysis of tuberculosis epidemiology: a systematic review.BMC medicine · 2018Pooled it
- Geo-mapping of government healthcare facilities providing diagnostic laboratory services in Delhi, India: a pilot study.BMJ public health · 2025Article
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- mHealth Technology Translation in a Limited Resources Community-Process, Challenges, and Lessons Learned From a Limited Resources Community of Chiang Mai Province, Thailand.IEEE journal of translational engineering in health and medicine · 2021Article
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- Geospatial Clustering of Mobile Phone Use and Tuberculosis Health Outcomes Among African Health Systems.Frontiers in public health · 2021Article
- Tuberculosis associated with the living conditions in an endemic municipality in the North of Brazil.Revista latino-americana de enfermagem · 2020Article
- Space-time clustering and associated risk factors of pulmonary tuberculosis in southwest China.Infectious diseases of poverty · 2018Article
- Geographical variations and influential factors in prevalence of cardiometabolic diseases in South Korea.PloS one · 2018Article
- Spatio-temporal analysis of the incidence of colorectal cancer in Guangzhou, 2010-2014.Chinese journal of cancer · 2017Article
- Spatial-temporal analysis of pulmonary tuberculosis in the northeast of the Yunnan province, People's Republic of China.Infectious diseases of poverty · 2017Article
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3 authors.
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Abstract
This retrospective population-based study was conducted to analyze spatial patterns of tuberculosis (TB) incidence in Si Sa Ket province, Thailand. TB notification data from 2004 to 2008 collected from TB clinics throughout the province was used along with population data to reveal a descriptive epidemiology of TB incidences. Global clustering patterns of the occurrence were assessed by using global spatial autocorrelation techniques. Additionally, local spatial pattern detection was performed by using local spatial autocorrelation and spatial scan statistic methods. The findings indicated clusters of the disease occurred in the study area. More specifically, significantly high-rate clusters were mostly detected in Mueang Si Sa Ket and Khukhan districts, which are located in the northwestern part of the province, while significantly low-rate clusters were persistent in Kantharalak and Benchalak districts, which are located at the southeastern area.
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