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Published in: Network Modeling Analysis in Health Informatics and Bioinformatics 1/2023

01-12-2023 | Original Article

Policy analysis and data mining tools for controlling COVID-19 policies

Author: Yoshiyasu Takefuji

Published in: Network Modeling Analysis in Health Informatics and Bioinformatics | Issue 1/2023

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Abstract

Much research has been done on the efficacy of vaccines against the COVID-19 pandemic, but the claims have not yet been realized in the real world. This paper proposes three COVID-19 policy outcome analysis tools such as jpscore for scoring and revealing the best prefecture policy in Japan, scorecovid for scoring and revealing the best country policy in the world, and finally hiscovid for visualizing and identifying when policymakers made mistakes in time-series scores. Poorly scored countries or prefectures can learn good strategies from the best country or prefecture with excellent scores. Three tools are based on a single metric dividing the number of COVID-19 deaths by the population in millions. Three tools suggest us that the sustainable mandatory test-isolation strategy should be adopted in the world for mitigating the pandemic. This paper also addresses what is lacking in Japan for scientific evidence-based research for mitigating the pandemic. Visualization tools and sorted and time-series scores of policy outcomes help policymakers make the right decisions.

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Metadata
Title
Policy analysis and data mining tools for controlling COVID-19 policies
Author
Yoshiyasu Takefuji
Publication date
01-12-2023
Publisher
Springer Vienna
Published in
Network Modeling Analysis in Health Informatics and Bioinformatics / Issue 1/2023
Print ISSN: 2192-6662
Electronic ISSN: 2192-6670
DOI
https://doi.org/10.1007/s13721-022-00400-3

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