Israel COVID-19 Data Verification by Multimodal Gaidai Reliability Method

Abstract Coronavirus disease spread throughout the world during the years 2020–2022, exhibited high transmission rates, low rates of morbidity and mortality, and posed challenges to national public health systems. The current case study presents a novel multimodal biosystem bioreliability approach, suitable for long-term epidemiological prognostics, particularly for biological, health, and environmental multiregional systems, measured across representative periods. The primary purpose of the current case study was assessment of future clinical risks and hazards, associated with excessive coronavirus death rates in any particular area/region of interest, at any specified time horizon. The study aims to provide a baseline for the advocated state-of-the-art method, enabling forecasting of the public health system's risks, based on raw (unprocessed) clinical histories. Existing statistical approaches lack the ability to effectively incorporate large regional dimensionality and complex multivariate intercorrelations between distinct regional observations. This case study provided a novel biosystem bioreliability approach, particularly appropriate for multiregional environmental and health systems, monitored across a representative observational period. Long-term excessive mortality rate prognostics have been reported. The proposed bioreliability methodology, being based on clinical survey raw data, may be applied to a variety of environmental and clinical public health applications.