A machine learning and clustering-based approach for county-level COVID-19 analysis.

A machine learning and clustering-based approach for county-level COVID-19 analysis.

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COVID-19 is a global pandemic threatening the lives and livelihood of millions of people across the world.Due to its novelty and quick spread, scientists have had difficulty in creating accurate forecasts for this disease.In part, this is due to variation in human behavior and environmental factors that impact disease propagation.This is especially true for regionally caroline gardner cards sale specific predictive models due to either limited case histories or other unique factors characterizing the region.This paper employs both supervised and unsupervised methods to identify the critical county-level demographic, mobility, weather, medical capacity, and health related county-level factors for studying COVID-19 propagation prior to the widespread availability of a hot topic guy funko pop vaccine.

We use this feature subspace to aggregate counties into meaningful clusters to support more refined disease analysis efforts.