Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Analyzing the Factors Affecting the COVID-19 Risk Level in the US Counties

Version 1 : Received: 3 April 2021 / Approved: 5 April 2021 / Online: 5 April 2021 (12:49:33 CEST)

How to cite: Ziyadidegan, S.; Razavi, M.; Pesarakli, H.; Javid, A.H. Analyzing the Factors Affecting the COVID-19 Risk Level in the US Counties. Preprints 2021, 2021040132. https://doi.org/10.20944/preprints202104.0132.v1 Ziyadidegan, S.; Razavi, M.; Pesarakli, H.; Javid, A.H. Analyzing the Factors Affecting the COVID-19 Risk Level in the US Counties. Preprints 2021, 2021040132. https://doi.org/10.20944/preprints202104.0132.v1

Abstract

The COVID-19 disease spreads swiftly, and nearly three months after the first positive case was confirmed in China, Coronavirus started to spread all over the United States. Some states and counties reported an extremely high number of positive cases and deaths, while some reported too few COVID-19 related cases and mortality. In this paper, the factors that could affect the transmission of COVID-19 and its risk level in different counties have been determined and analyzed. Using Pearson Correlation, K-means clustering, and several classification models, the most critical ones were determined. Results showed that mean temperature, percent of people below poverty, percent of adults with obesity, air pressure, percentage of rural areas, and percent of uninsured people in each county were the most significant and effective attributes.

Keywords

multinomial logistic regression; K-means clustering; COVID-19; SARS-CoV-2; meteorological variables

Subject

Computer Science and Mathematics, Algebra and Number Theory

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