4.3 Article

Gaidai reliability method for high-dimensional spatio-temporal biosystems

期刊

BIOSYSTEMS
卷 235, 期 -, 页码 -

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ELSEVIER SCI LTD
DOI: 10.1016/j.biosystems.2023.105073

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COVID-19; Epidemic outbreak; Public health; Risk; Mathematical biology; AI; Bioinformatics

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This study presents a new methodology for assessing pandemic risks in a national health system. The suggested approach addresses the highdimensionality and complex cross-correlations between regional observations, enabling accurate epidemiological risk forecasts for multi-regional biological and health systems.
This study presents novel methodology for pandemic risks assessment for a national health system of interest. The 2019 coronavirus disease (COVID-19) is a contagious disease with certain potential for worldwide spread and potentially significant effects on public health globally. Suggested methodology enables risks assessment of an epidemic, that may happen in the near future at any time, and in any national region of interest. Traditional spatio-temporal reliability methodologies do not have benefit of easily handling health system's highdimensionality and complex cross-correlations between regional observations. Contrarily, advocated Gaidaireliability approach successfully addresses spatiotemporal clinical observations, as well as multi-regional epidemiological dynamics. This study aimed at benchmarking of a novel bio-statistical technique, enabling national health risk assessment, based on available clinical surveys with dynamically observed patient numbers, while accounting for relevant territorial mappings. The method developed in this study opens up the possibility of accurate epidemiological risk forecast for multi-regional biological and health systems. Suggested bioinformatical methodology may be used in a wide range of public health applications.

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