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Using interpretable machine learning identify factors contributing to COVID-19 cases in the United States
Novel AI and Data Science Advancements for Sustainability in the Era of COVID-19 ; : 113-158, 2022.
Article in English | Scopus | ID: covidwho-2035528
ABSTRACT
COVID-19 has been declared as a “pandemic” by the World Health Organization (WHO) and has claimed more than a million lives and over 50 million confirmed cases worldwide as of 7th November 2020. This virus can be curbed in only two ways vaccination and other by imposing non-pharmaceutical interventions (NPIs), which are behavioral changes to a person and community. Most of the nations worldwide have imposed NPIs in the form of social distancing and lockdowns, which have been effective in reducing the pace of the virus's spread, but continued implementation has deemed social and economic losses. Hence strategic implementation of NPIs in a burst of periods should be done based on educated decisions using data about population mobility trends to find hot zones that lead to a spike in cases. These decisions will positively impact the virus's spread with lower damage to social and economic aspects. © 2022 Elsevier Inc. All rights reserved.
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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: Novel AI and Data Science Advancements for Sustainability in the Era of COVID-19 Year: 2022 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Scopus Language: English Journal: Novel AI and Data Science Advancements for Sustainability in the Era of COVID-19 Year: 2022 Document Type: Article