Abstract

Spread of novel coronavirus and other flu-like illnesses, periodically causing increased death and morbidity rates, places pressures on national health systems. In order to provide a reliable long-term forecast of the new coronavirus infection rate, this research employs novel Gaidai bio-system reliability technique, especially suitable for multi-regional biological, environmental and public health systems. The goal of this study was to directly apply state of art statistical techniques to unprocessed raw clinical data, utilizing a multicenter, population-based biostatistical methodology. Epidemiological risks have been accurately forecasted, specifically for European Union member states. Based on their clinical survey data, suggested spatiotemporal methodology may be applied in a variety of public biological and health applications.

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