Development of melioidosis mapping in Malaysia using various relative risk models
Melioidosis is a significant infectious disease caused by Burkholderia pseudomallei, which is commonly found in soil and water. The disease is highly endemic in Malaysia, with an estimated 2000 deaths annually, surpassing fatalities from dengue and tuberculosis. Despite its severity, understanding t...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | en |
| Published: |
Penerbit Universiti Kebangsaan Malaysia
2025
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| Online Access: | http://journalarticle.ukm.my/26460/1/SS%2018.pdf http://journalarticle.ukm.my/26460/ https://www.ukm.my/jsm/english_journals/vol54num10_2025/contentsVol54num10_2025.html |
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| Summary: | Melioidosis is a significant infectious disease caused by Burkholderia pseudomallei, which is commonly found in soil and water. The disease is highly endemic in Malaysia, with an estimated 2000 deaths annually, surpassing fatalities from dengue and tuberculosis. Despite its severity, understanding the geographical distribution of melioidosis remains a challenge. In this study, the melioidosis data from 2014 to 2023 in Malaysia were analyzed using Excel and WinBUGS software. Relative risk, a measure comparing the risk in one group to another, was used to map melioidosis risk geographically by using ArcGIS. Four models - Susceptible-Infected-Recovered (SIR), Standardized Morbidity Ratios (SMR), PoissonGamma, and Besag-York-Mollie (BYM) - were applied to assess their effectiveness. Mapping highlighted consistently higher relative risk in northern Malaysia, particularly in Perlis and Kedah across multiple models while most other states remained in the very low risk category. Besides, the model performance was compared using the Deviance Information Criterion (DIC) to assess goodness of fit. Findings suggest the Poisson-Gamma model is most suitable and reliable for accurate disease risk mapping to better epidemiological surveillance and targeted public health interventions as it accounts for local variations while maintaining computational efficiency in Malaysia. |
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