From Digital to Quantum Epidemiology: The Quantum Data Lake concept for Big Data related to viral infectious diseases

Abstract

The study is dedicated to the development of quantum epidemiology which is the expected next stage in epidemiology transformation as new quantum technologies have emerged. At the present time, epidemiology is entering the digital era and undergoes a paradigm shift from data-driven to value-driven strategy. The epidemiology data are characterized by uncertainty, multidimensionality, and disconnection, which drive to prefer the quantum approach for data exposition, creation of value, and modeling. The Quantum Data Lake concept is proposed. The data about DNA viruses with symptoms and diseases are shown as example of epidemiology data complexity. The Quantum Data Lake concept consists of several layers and quantum tools, including PT-symmetry and non-Hermiticity as intuitive modeling tools. PT-symmetry breaking is able to detect the hidden shift in the information which is permanently updated in the Data Lake. The duality of PT-symmetry breaking can be compared with the estimation of the best and worst scenarios simultaneously. In contrast to the widely discussed advantages of quantum computing such as high-speed performance and very large parallel scale, the proposed approach emphasizes the fundamental uniqueness of quantum theory for modeling. The study highlights the necessity to investigate the native processes of viruses’ interaction with the human population by relying on quantum theory’s natural properties. Implementation of quantum logic and reliance on a quantum theory is the fundamental difference between the current digital epidemiology and future quantum epidemiology.