The Interplay of Demographic Variables and Social Distancing Scores in Deep Prediction of U.S. COVID-19 Cases
With the severity of the COVID-19 outbreak, we characterize the nature of the growth trajectories of counties in the United States using a novel combination of spectral clustering and the correlation matrix. As the U.S. and the rest of the world are experiencing a severe second wave of infections, t...
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Zusammenfassung: | With the severity of the COVID-19 outbreak, we characterize the nature of the
growth trajectories of counties in the United States using a novel combination
of spectral clustering and the correlation matrix. As the U.S. and the rest of
the world are experiencing a severe second wave of infections, the importance
of assigning growth membership to counties and understanding the determinants
of the growth are increasingly evident. Subsequently, we select the demographic
features that are most statistically significant in distinguishing the
communities. Lastly, we effectively predict the future growth of a given county
with an LSTM using three social distancing scores. This comprehensive study
captures the nature of counties' growth in cases at a very micro-level using
growth communities, demographic factors, and social distancing performance to
help government agencies utilize known information to make appropriate
decisions regarding which potential counties to target resources and funding
to. |
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DOI: | 10.48550/arxiv.2101.02113 |