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Evidence of global relevance

Spatial Autocorrelation and High-Risk Area Identification of Food Poisoning in Thailand, 2003–2022

Analysis of 2,329,463 Report 506 cases from 2003-2022 found significant spatial clustering every year, with Moran's I of 0.317-0.522. High-high clusters persisted in the Northeast and North, while low-low clusters predominated in the South. The pattern supports surveillance prioritisation but cannot identify individual causes and may reflect reporting differences.

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Key findings

  • Global Moran's I ranged from 0.317 to 0.522, significant in every year. The Northeast contained 9-14 high-high provinces annually, with persistent high clusters also in the North, while low-low clusters predominated in the South. Patterns persisted across five-year periods.
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Why this matters globally

Persistent clusters can guide targeted food inspection, laboratory capacity, risk communication and supply-chain investigation rather than uniform resource allocation.

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Thai researcher contribution

O. Timpong of NIDA's Graduate School of Environmental Development Administration analysed national surveillance and geography across every Thai province.

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Limitations to consider

Province-level ecological surveillance depends on care seeking, diagnosis and reporting completeness. Socioeconomic, dietary or market factors were not directly tested and should not be treated as established causes. Provincial boundaries may hide local clusters and introduce the modifiable areal unit problem.

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Verify the original sources

International Journal of GeoinformaticsRead the original article

DOI: 10.52939/ijg.v22i6.5045

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