Aggregation, Storing, Multidimensional Representation and Processing of COVID-19 Data

Abstract

An outbreak of a new coronavirus disease (COVID-19) has spread rapidly around the world, which in turn has necessitated the prompt detection of people with symptoms in public. To do this, it is necessary to develop information systems for the accumulation and processing of large data collections obtained from various information sources. The article presents a prototype of a subsystem for storing an extensive list of information about COVID-19. The developed prototype includes the structure of the subsystem for storage, retrieval and processing of information on the detection, dissemination, rapid response to COVID-19 outbreaks. The multidimensional representation of information on COVID-19 formed on the basis of data hypercubes is considered. Describes the composition and purpose of measurements to provide information on devices used to detect and identify individuals with COVID-19 symptoms. Measurements for storing information of the mobile operator, which are used to establish the trajectories of citizens in order to identify cases of intersection of trajectories with a person infected with COVID-19, are considered. Based on the proposed information model of detection processes in public places of persons with suspected COVID-19 infection, a method of search and identification of such persons has been developed. The method is formed using procedures for finding intersections of trajectories of citizens.