University of Oulu

Juuso, Esko K.. "Intelligent temporal analysis of coronavirus statistical data" Open Engineering, vol. 11, no. 1, 2021, pp. 1223-1232. https://doi.org/10.1515/eng-2021-0118

Intelligent temporal analysis of coronavirus statistical data

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Author: Juuso, Esko K.1
Organizations: 1Control Engineering, Environmental and Chemical Engineering, Faculty of Technology, University of Oulu, P.O. Box 4300, FI-90014, Oulu, Finland
Format: article
Version: published version
Access: open
Online Access: PDF Full Text (PDF, 4.2 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe2022032324624
Language: English
Published: De Gruyter, 2021
Publish Date: 2022-03-23
Description:

Abstract

The coronavirus COVID-19 is affecting around the world with strong differences between countries and regions. Extensive datasets are available for visual inspection and downloading. The material has limitations for phenomenological modeling but data-based methodologies can be used. This research focuses on the intelligent temporal analysis of datasets in developing compact solutions for early detection of levels, trends, episodes, and severity of situations. The methodology has been tested in the analysis of daily new confirmed COVID-19 cases and deaths in six countries. The datasets are studied per million people to get comparable indicators. Nonlinear scaling brings the data of different countries to the same scale, and the temporal analysis is based on the scaled values. The same approach can be used for any country or a group of people, e.g., hospital patients, patients in intensive care, or people in different age categories. During the pandemic, the scaling functions expanded for the confirmed cases but remained practically unchanged for the confirmed deaths, which is consistent with increasing testing.

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Series: Open engineering
ISSN: 2391-5439
ISSN-E: 2391-5439
ISSN-L: 2391-5439
Volume: 11
Issue: 1
Pages: 1223 - 1232
DOI: 10.1515/eng-2021-0118
OADOI: https://oadoi.org/10.1515/eng-2021-0118
Type of Publication: A1 Journal article – refereed
Field of Science: 113 Computer and information sciences
Subjects:
Copyright information: © 2021 Esko K. Juuso, published by De Gruyter. This work is licensed under the Creative Commons Attribution 4.0 International License.
  https://creativecommons.org/licenses/by/4.0/