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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Cornell University
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7805455/ https://www.ncbi.nlm.nih.gov/pubmed/33442559 |
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author | Tang, Francesca Feng, Yang Chiheb, Hamza Fan, Jianqing |
author_facet | Tang, Francesca Feng, Yang Chiheb, Hamza Fan, Jianqing |
author_sort | Tang, Francesca |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-7805455 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Cornell University |
record_format | MEDLINE/PubMed |
spelling | pubmed-78054552021-01-14 The Interplay of Demographic Variables and Social Distancing Scores in Deep Prediction of U.S. COVID-19 Cases* Tang, Francesca Feng, Yang Chiheb, Hamza Fan, Jianqing ArXiv Article 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. Cornell University 2021-01-06 /pmc/articles/PMC7805455/ /pubmed/33442559 Text en https://creativecommons.org/licenses/by-nc-sa/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (https://creativecommons.org/licenses/by-nc-sa/4.0/) , which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format for noncommercial purposes only, and only so long as attribution is given to the creator. If you remix, adapt, or build upon the material, you must license the modified material under identical terms. |
spellingShingle | Article Tang, Francesca Feng, Yang Chiheb, Hamza Fan, Jianqing The Interplay of Demographic Variables and Social Distancing Scores in Deep Prediction of U.S. COVID-19 Cases* |
title | The Interplay of Demographic Variables and Social Distancing Scores in Deep Prediction of U.S. COVID-19 Cases* |
title_full | The Interplay of Demographic Variables and Social Distancing Scores in Deep Prediction of U.S. COVID-19 Cases* |
title_fullStr | The Interplay of Demographic Variables and Social Distancing Scores in Deep Prediction of U.S. COVID-19 Cases* |
title_full_unstemmed | The Interplay of Demographic Variables and Social Distancing Scores in Deep Prediction of U.S. COVID-19 Cases* |
title_short | The Interplay of Demographic Variables and Social Distancing Scores in Deep Prediction of U.S. COVID-19 Cases* |
title_sort | interplay of demographic variables and social distancing scores in deep prediction of u.s. covid-19 cases* |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7805455/ https://www.ncbi.nlm.nih.gov/pubmed/33442559 |
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