Analyzing Response Efficiency to COVID-19 and Underlying Factors of the Outbreak With Deep Assessment Methodology and Fractional Calculus

This study focuses on modeling the daily deaths per new case of COVID-19 by using the Fractional Calculus and the Least Squares Method. Based on our prior work, we proposed a new modeling approach, assessed the strength of outbreak response, and analyzed possible underlying factors of the outbreak f...

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Autores principales:	Ertugrul Karacuha, Esra Ergun, Nisa Ozge Onal Tugrul, Kamil Karacuha, Vasil Tabatadze
Formato:	article
Lenguaje:	EN
Publicado:	IEEE 2021
Materias:	COVID-19 deep assessment methodology (DAM) fractional calculus mathematical modeling correlation analysis Electrical engineering. Electronics. Nuclear engineering TK1-9971
Acceso en línea:	https://doaj.org/article/482ec1fd5cc94bce9a83f625e2399002
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spelling	oai:doaj.org-article:482ec1fd5cc94bce9a83f625e23990022021-12-03T00:01:13ZAnalyzing Response Efficiency to COVID-19 and Underlying Factors of the Outbreak With Deep Assessment Methodology and Fractional Calculus2169-353610.1109/ACCESS.2021.3129904https://doaj.org/article/482ec1fd5cc94bce9a83f625e23990022021-01-01T00:00:00Zhttps://ieeexplore.ieee.org/document/9623535/https://doaj.org/toc/2169-3536This study focuses on modeling the daily deaths per new case of COVID-19 by using the Fractional Calculus and the Least Squares Method. Based on our prior work, we proposed a new modeling approach, assessed the strength of outbreak response, and analyzed possible underlying factors of the outbreak for 8 countries including China, France, Germany, Italy, Russia, Spain, the UK, and the US. First, we modeled weekly deaths per new case of COVID-19 using our new modeling method Deep Assessment Methodology - Second Derivative (DAM-SD). Later, we defined a performance indicator to understand how well each country copes with the pandemic. Lastly, Pearson correlations between the performance indicator and several economic, social, and environmental indices, such as Human Development Index, Human Freedom, Democracy, Competitiveness, and Trust Index are computed, and <inline-formula> <tex-math notation="LaTeX">$p$ </tex-math></inline-formula>-values are reported. Results showed that DAM-SD successfully models the daily new cases of COVID-19 with 3.7390% Mean Average Precision Error and outperforms the DAM by 1.5678% MAPE. China is the best-modeled country with 4.0975e-08% MAPE whereas the model produced the highest error rate for France as 8.8317% MAPE. According to the analysis with the performance indicators, China is the most successful country against the pandemic while the United States and France fail to confine COVID-19 outbreak compared to the others. Indicators such as Human Development Index, Human Freedom, Human Democracy, GINI Index, Workers Rights, the Trust Index, and Air Pollution are found significant for COVID-19 response according to the p-values. In the correlation analysis, Average Class Size, Government’s Long Term Vision, Responsiveness to Change, Better Life Index, and Population Density were the least significant indicators. Long Term Care Beds, Social Capital, and Global Social Mobility indicators are found correlated with the COVID-19 response. Household Spending and Student Skills are found insignificant.Ertugrul KaracuhaEsra ErgunNisa Ozge Onal TugrulKamil KaracuhaVasil TabatadzeIEEEarticleCOVID-19deep assessment methodology (DAM)fractional calculusmathematical modelingcorrelation analysisElectrical engineering. Electronics. Nuclear engineeringTK1-9971ENIEEE Access, Vol 9, Pp 157812-157824 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	COVID-19 deep assessment methodology (DAM) fractional calculus mathematical modeling correlation analysis Electrical engineering. Electronics. Nuclear engineering TK1-9971
spellingShingle	COVID-19 deep assessment methodology (DAM) fractional calculus mathematical modeling correlation analysis Electrical engineering. Electronics. Nuclear engineering TK1-9971 Ertugrul Karacuha Esra Ergun Nisa Ozge Onal Tugrul Kamil Karacuha Vasil Tabatadze Analyzing Response Efficiency to COVID-19 and Underlying Factors of the Outbreak With Deep Assessment Methodology and Fractional Calculus
description	This study focuses on modeling the daily deaths per new case of COVID-19 by using the Fractional Calculus and the Least Squares Method. Based on our prior work, we proposed a new modeling approach, assessed the strength of outbreak response, and analyzed possible underlying factors of the outbreak for 8 countries including China, France, Germany, Italy, Russia, Spain, the UK, and the US. First, we modeled weekly deaths per new case of COVID-19 using our new modeling method Deep Assessment Methodology - Second Derivative (DAM-SD). Later, we defined a performance indicator to understand how well each country copes with the pandemic. Lastly, Pearson correlations between the performance indicator and several economic, social, and environmental indices, such as Human Development Index, Human Freedom, Democracy, Competitiveness, and Trust Index are computed, and <inline-formula> <tex-math notation="LaTeX">$p$ </tex-math></inline-formula>-values are reported. Results showed that DAM-SD successfully models the daily new cases of COVID-19 with 3.7390% Mean Average Precision Error and outperforms the DAM by 1.5678% MAPE. China is the best-modeled country with 4.0975e-08% MAPE whereas the model produced the highest error rate for France as 8.8317% MAPE. According to the analysis with the performance indicators, China is the most successful country against the pandemic while the United States and France fail to confine COVID-19 outbreak compared to the others. Indicators such as Human Development Index, Human Freedom, Human Democracy, GINI Index, Workers Rights, the Trust Index, and Air Pollution are found significant for COVID-19 response according to the p-values. In the correlation analysis, Average Class Size, Government’s Long Term Vision, Responsiveness to Change, Better Life Index, and Population Density were the least significant indicators. Long Term Care Beds, Social Capital, and Global Social Mobility indicators are found correlated with the COVID-19 response. Household Spending and Student Skills are found insignificant.
format	article
author	Ertugrul Karacuha Esra Ergun Nisa Ozge Onal Tugrul Kamil Karacuha Vasil Tabatadze
author_facet	Ertugrul Karacuha Esra Ergun Nisa Ozge Onal Tugrul Kamil Karacuha Vasil Tabatadze
author_sort	Ertugrul Karacuha
title	Analyzing Response Efficiency to COVID-19 and Underlying Factors of the Outbreak With Deep Assessment Methodology and Fractional Calculus
title_short	Analyzing Response Efficiency to COVID-19 and Underlying Factors of the Outbreak With Deep Assessment Methodology and Fractional Calculus
title_full	Analyzing Response Efficiency to COVID-19 and Underlying Factors of the Outbreak With Deep Assessment Methodology and Fractional Calculus
title_fullStr	Analyzing Response Efficiency to COVID-19 and Underlying Factors of the Outbreak With Deep Assessment Methodology and Fractional Calculus
title_full_unstemmed	Analyzing Response Efficiency to COVID-19 and Underlying Factors of the Outbreak With Deep Assessment Methodology and Fractional Calculus
title_sort	analyzing response efficiency to covid-19 and underlying factors of the outbreak with deep assessment methodology and fractional calculus
publisher	IEEE
publishDate	2021
url	https://doaj.org/article/482ec1fd5cc94bce9a83f625e2399002
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_version_	1718373984264781824

Analyzing Response Efficiency to COVID-19 and Underlying Factors of the Outbreak With Deep Assessment Methodology and Fractional Calculus

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