https://doi.org/10.4081/gh.2023.1189

Spatiotemporal distribution and geostatistically interpolated mapping of the melioidosis risk in an endemic zone in Thailand

Vol. 18 No. 2 (2023)
Submitted: 25 January 2023
Accepted: 21 June 2023
Published: 5 July 2023
Melioidosis, interpolated mapping, spatial autocorrelation, Burkholderia pseudomallei Thailand
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Authors

Jaruwan Wongbutdee
https://orcid.org/0009-0009-1884-9006
Geospatial Health Research Group, College of Medicine and Public Health, Ubon Ratchathani University, Thailand.
Jutharat Jittimanee
Geospatial Health Research Group, College of Medicine and Public Health, Ubon Ratchathani University, Thailand.
Wacharapong Saengnill
watcharapong.s@ubu.ac.th
https://orcid.org/0000-0001-7293-0635
Geospatial Health Research Group, College of Medicine and Public Health, Ubon Ratchathani University, Thailand.

Melioidosis, a bacterial, infectious disease contracted from contaminated soil or water, is a public health problem identified in tropical regions and endemic several regions of Thailand. Surveillance and prevention are important for determining its distribution patterns and mapping its risk, which have been analysed in the present study. Case reports in Thailand were collected from 1 January 2016 to 31 December 2020. Spatial autocorrelation was analyzed using Moran’s I and univariate local Moran’s I. Spatial point data of melioidosis incidence were calculated, with riskmapping interpolation performed by Kriging. It was highest in 2016, at 32.37 cases per 100,000 people, and lowest in 2020, at 10.83 cases per 100,000 people. General observations revealed that its incidence decreased slightly from 2016 to 2018 and drastically in 2019 and 2020. The Moran’s I values for melioidosis incidence exhibited a random spatial pattern in 2016 and clustered distribution from 2017 to 2020. The risk and variance maps show interval values. These findings may contribute to the monitoring and surveillance of melioidosis outbreaks.

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How to Cite

Wongbutdee, J., Jittimanee, J., & Saengnill, W. (2023). Spatiotemporal distribution and geostatistically interpolated mapping of the melioidosis risk in an endemic zone in Thailand. Geospatial Health, 18(2). https://doi.org/10.4081/gh.2023.1189
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