Association mining based approach to analyze COVID-19 response and case growth in the United States

Abstract Containing the COVID-19 pandemic while balancing the economy has proven to be quite a challenge for the world. We still have limited understanding of which combination of policies have been most effective in flattening the curve; given the challenges of the dynamic and evolving nature of th...

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Autores principales:	Satya Katragadda, Raju Gottumukkala, Ravi Teja Bhupatiraju, Azmyin Md. Kamal, Vijay Raghavan, Henry Chu, Ramesh Kolluru, Ziad Ashkar
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/9c4eb2b71e70453394f9045aaa6119b0
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spelling	oai:doaj.org-article:9c4eb2b71e70453394f9045aaa6119b02021-12-02T15:15:05ZAssociation mining based approach to analyze COVID-19 response and case growth in the United States10.1038/s41598-021-96912-52045-2322https://doaj.org/article/9c4eb2b71e70453394f9045aaa6119b02021-09-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-96912-5https://doaj.org/toc/2045-2322Abstract Containing the COVID-19 pandemic while balancing the economy has proven to be quite a challenge for the world. We still have limited understanding of which combination of policies have been most effective in flattening the curve; given the challenges of the dynamic and evolving nature of the pandemic, lack of quality data etc. This paper introduces a novel data mining-based approach to understand the effects of different non-pharmaceutical interventions in containing the COVID-19 infection rate. We used the association rule mining approach to perform descriptive data mining on publicly available data for 50 states in the United States to understand the similarity and differences among various policies and underlying conditions that led to transitions between different infection growth curve phases. We used a multi-peak logistic growth model to label the different phases of infection growth curve. The common trends in the data were analyzed with respect to lockdowns, face mask mandates, mobility, and infection growth. We observed that face mask mandates combined with mobility reduction through moderate stay-at-home orders were most effective in reducing the number of COVID-19 cases across various states.Satya KatragaddaRaju GottumukkalaRavi Teja BhupatirajuAzmyin Md. KamalVijay RaghavanHenry ChuRamesh KolluruZiad AshkarNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-12 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Satya Katragadda Raju Gottumukkala Ravi Teja Bhupatiraju Azmyin Md. Kamal Vijay Raghavan Henry Chu Ramesh Kolluru Ziad Ashkar Association mining based approach to analyze COVID-19 response and case growth in the United States
description	Abstract Containing the COVID-19 pandemic while balancing the economy has proven to be quite a challenge for the world. We still have limited understanding of which combination of policies have been most effective in flattening the curve; given the challenges of the dynamic and evolving nature of the pandemic, lack of quality data etc. This paper introduces a novel data mining-based approach to understand the effects of different non-pharmaceutical interventions in containing the COVID-19 infection rate. We used the association rule mining approach to perform descriptive data mining on publicly available data for 50 states in the United States to understand the similarity and differences among various policies and underlying conditions that led to transitions between different infection growth curve phases. We used a multi-peak logistic growth model to label the different phases of infection growth curve. The common trends in the data were analyzed with respect to lockdowns, face mask mandates, mobility, and infection growth. We observed that face mask mandates combined with mobility reduction through moderate stay-at-home orders were most effective in reducing the number of COVID-19 cases across various states.
format	article
author	Satya Katragadda Raju Gottumukkala Ravi Teja Bhupatiraju Azmyin Md. Kamal Vijay Raghavan Henry Chu Ramesh Kolluru Ziad Ashkar
author_facet	Satya Katragadda Raju Gottumukkala Ravi Teja Bhupatiraju Azmyin Md. Kamal Vijay Raghavan Henry Chu Ramesh Kolluru Ziad Ashkar
author_sort	Satya Katragadda
title	Association mining based approach to analyze COVID-19 response and case growth in the United States
title_short	Association mining based approach to analyze COVID-19 response and case growth in the United States
title_full	Association mining based approach to analyze COVID-19 response and case growth in the United States
title_fullStr	Association mining based approach to analyze COVID-19 response and case growth in the United States
title_full_unstemmed	Association mining based approach to analyze COVID-19 response and case growth in the United States
title_sort	association mining based approach to analyze covid-19 response and case growth in the united states
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/9c4eb2b71e70453394f9045aaa6119b0
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Association mining based approach to analyze COVID-19 response and case growth in the United States

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