Singapore COVID-19 data cross-validation by the Gaidai reliability method

Abstract

AbstractNovel coronavirus infection (COVID-19) has exserted certain burden on global public health, spreading around the world with reportedly low mortality and morbidity. This study advocates novel bio and health system reliability approach, especially suitable for multi-regional environmental and health systems. Advocated spatiotemporal method has been cross-validated, versus well established bivariate Weibull method, based on available raw clinical dataset. The purpose of this study was to assess risks of excessive coronavirus death rates, that may occur within any given time horizon, and in any region or district of interest. This study aims at benchmarking of the novel Gaidai bio-reliability method, allowing accurate assessment of national public health system risks, for the years to come. Novel bio-system reliability approach is particularly suitable for multi-regional environmental and health systems, monitored for a sufficiently representative period of time. In case when underlying bio-system is stationary, or the underlying trend is known, long-term future death rate risk assessment can be done, and confidence intervals can be generated. Advocated methodology may to be useful for a wide variety of public health applications, thus, it is not limited to the example, considered here.