Extreme Weather and Melioidosis: An endemic tropical disease in Penampang district of Sabah, Malaysia

Jiee, Sam Froze; Lim, Kai Joo; Vui, Daryl Sin Choon; Marius, Dina Peter; Illyana, Nurul Syafiqah; Jantim, Anisah

doi:10.56808/2586-940x.1023

Cited by 2 publications

(4 citation statements)

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“…Analysis of the explanatory variables in August and November, as well as in September and October, demonstrated a strong association between rainfall and melioidosis morbidity rate. Although previous studies have identified this relationship in numerous countries [5,[45][46][47][48], it is not significant in Thailand [49]. The GPR model revealed significant associations between rainfall and melioidosis morbidity rate in certain months (e.g.…”

Section: Discussionmentioning

confidence: 70%

“…Our study revealed a negative coefficient for rainfall, with nearly half of the associated melioidosis cases displaying high deviance percentages. Nonetheless, an association between melioidosis and rainfall has been reported in various countries, such as Australia [45,46], Taiwan [47], Malaysia [48], and Singapore [5]. Additionally, Shaharudin et al [59] reported a 1% detection rate of B. pseudomallei in soil, indicating a potential risk of melioidosis among flood victims in Kelantan, Malaysia.…”

Section: Discussionmentioning

confidence: 99%

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Exploring the Relationship between Melioidosis Morbidity Rate and Local Environmental Indicators Using Remotely Sensed Data

Wongbutdee,

Jittimanee,

Dandee

et al. 2024

Preprint

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Melioidosis is an endemic infectious disease caused by Burkholderia pseudomallei bacteria, which contaminates soil and water. To better understand the environmental changes that have contributed to melioidosis outbreaks, this study used spatiotemporal analyses to clarify the distribution pattern of melioidosis and the relationship between melioidosis morbidity rate and local environmental indicators (land surface temperature, normalised difference vegetation index, normalised difference water index) and rainfall. A retrospective study was conducted from January 2013 to December 2022, covering data from 219 sub-districts, with each exhibiting varying morbidity rate of melioidosis on a monthly basis. Spatial autocorrelation was determined using local Moran’s I, and the relationship between melioidosis morbidity rate and the environmental indicators was evaluated using geographically weighted Poisson regression. The results revealed clustered spatiotemporal patterns of melioidosis morbidity rate across sub-districts, with hotspots predominantly observed in the northern region. Furthermore, we observed a range of coefficients for the environmental indicators, varying from negative to positive, which provided insights into their relative contributions to melioidosis in each local area and month. These findings highlight the presence of spatial heterogeneity driven by environmental indicators and underscore the importance of public health offices implementing targeted monitoring and surveillance strategies for melioidosis in different locations.

show abstract

Section: Discussionmentioning

confidence: 70%

Section: Discussionmentioning

confidence: 99%

Exploring the Relationship between Melioidosis Morbidity Rate and Local Environmental Indicators Using Remotely Sensed Data

Wongbutdee,

Jittimanee,

Dandee

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

Section: Discussionmentioning

confidence: 77%

“…Our study revealed a negative coefficient for rainfall, with nearly half of the associated melioidosis cases displaying high deviance percentages. Nonetheless, an association between melioidosis and rainfall has been reported in various countries, such as Australia [45,46], Taiwan [47], Malaysia [48], and Singapore [5]. Additionally, Shaharudin et al [60] reported a 1% detection rate of B. pseudomallei in soil, indicating a potential risk of melioidosis among flood victims in Kelantan, Malaysia.…”

Section: Discussionmentioning

confidence: 99%

Exploring the Relationship between Melioidosis Morbidity Rate and Local Environmental Indicators Using Remotely Sensed Data

Wongbutdee,

Jittimanee,

Daendee

et al. 2024

IJERPH

View full text Add to dashboard Cite

Melioidosis is an endemic infectious disease caused by Burkholderia pseudomallei bacteria, which contaminates soil and water. To better understand the environmental changes that have contributed to melioidosis outbreaks, this study used spatiotemporal analyses to clarify the distribution pattern of melioidosis and the relationship between melioidosis morbidity rate and local environmental indicators (land surface temperature, normalised difference vegetation index, normalised difference water index) and rainfall. A retrospective study was conducted from January 2013 to December 2022, covering data from 219 sub-districts in Northeast Thailand, with each exhibiting a varying morbidity rate of melioidosis on a monthly basis. Spatial autocorrelation was determined using local Moran’s I, and the relationship between the melioidosis morbidity rate and the environmental indicators was evaluated using a geographically weighted Poisson regression. The results revealed clustered spatiotemporal patterns of melioidosis morbidity rate across sub-districts, with hotspots predominantly observed in the northern region. Furthermore, we observed a range of coefficients for the environmental indicators, varying from negative to positive, which provided insights into their relative contributions to melioidosis in each local area and month. These findings highlight the presence of spatial heterogeneity driven by environmental indicators and underscore the importance of public health offices implementing targeted monitoring and surveillance strategies for melioidosis in different locations.

show abstract

Extreme Weather and Melioidosis: An endemic tropical disease in Penampang district of Sabah, Malaysia

Cited by 2 publications

References 0 publications

Exploring the Relationship between Melioidosis Morbidity Rate and Local Environmental Indicators Using Remotely Sensed Data

Exploring the Relationship between Melioidosis Morbidity Rate and Local Environmental Indicators Using Remotely Sensed Data

Exploring the Relationship between Melioidosis Morbidity Rate and Local Environmental Indicators Using Remotely Sensed Data

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