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Environmental Factors Influencing Melioidosis Incidence inHigh-Endemic Areas of Thailand: A Spatial and Spatio-temporalCluster Analysis |
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| รหัสดีโอไอ | |
| Creator | Kavin Thinkhamrop |
| Title | Environmental Factors Influencing Melioidosis Incidence inHigh-Endemic Areas of Thailand: A Spatial and Spatio-temporalCluster Analysis |
| Contributor | Phimphisa Theangyotha, Rachan Janon, Apiporn T. Suwannatrai, Chananya Jirapornkul, Mick Soukavong, Nion Leeka, Matthew Kelly |
| Publisher | Thai Society of Higher Education Institutes on Environment |
| Publication Year | 2569 |
| Journal Title | EnvironmentAsia |
| Journal Vol. | 19 |
| Journal No. | 3 |
| Page no. | 129-141 |
| Keyword | Melioidosis, Environment, Spatio-temporal, Northeastern, Thailand |
| URL Website | http://www.tshe.org/ea/index.html |
| Website title | EnvironmentAsia |
| ISSN | 1906-1714 |
| Abstract | Melioidosis remains a significant public health problem globally, particularly in northeastern Thailand,a high-endemic area. Environmental factors strongly influence its spatio-temporal distribution,enabling identification of high-risk clusters. However, limited cluster detection in previous studieshas constrained targeted and sustainable prevention strategies. This study examined environmentaldeterminants of melioidosis incidence in a high-endemic region of Thailand. Poisson regressionmodels were used to assess the associations between environmental factors, including altitude, soilmoisture, wind speed, and rice field coverage, and melioidosis incidence. Spatial and temporal clusterswere identified using SaTScan based on Kulldorff’s scan statistics. A total of 1,136 melioidosiscases were reported in 2016 - 2022, the overall incidence was 71.52 per 100,000 population. Theassociation between environmental factors and incidence of melioidosis indicated that every 1-meterincrease in altitude, the incidence decreased by 0.3% (IRR = 0.997; 95% CI: 0.995 - 0.999), whileeach 1% increase in rice field coverage, the incidence decreased by 41.5% (IRR = 0.585; 95% CI:0.350 - 0.978). Spatio-temporal analysis identified a significant primary cluster during 2020 - 2022,covering 13 sub-districts within a 19.53 km radius. The cluster had 269 observed cases versus175.46 expected cases, with a relative risk of 1.7 and a log-likelihood ratio of 26.11. Higher altitudeand greater rice field coverage were associated with reduced melioidosis incidence. However,the presence of a significant multi-year cluster highlights ongoing localized transmission. Thesefindings underscore the importance of integrating environmental and spatio-temporal analyses toimprove risk identification and inform targeted control and prevention strategies in endemic settings. |
