Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Tang, Francesca, Feng, Yang, Chiheb, Hamza, Fan, Jianqing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cornell University 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7805455/
https://www.ncbi.nlm.nih.gov/pubmed/33442559
_version_ 1783636314313195520
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
work_keys_str_mv AT tangfrancesca theinterplayofdemographicvariablesandsocialdistancingscoresindeeppredictionofuscovid19cases
AT fengyang theinterplayofdemographicvariablesandsocialdistancingscoresindeeppredictionofuscovid19cases
AT chihebhamza theinterplayofdemographicvariablesandsocialdistancingscoresindeeppredictionofuscovid19cases
AT fanjianqing theinterplayofdemographicvariablesandsocialdistancingscoresindeeppredictionofuscovid19cases
AT tangfrancesca interplayofdemographicvariablesandsocialdistancingscoresindeeppredictionofuscovid19cases
AT fengyang interplayofdemographicvariablesandsocialdistancingscoresindeeppredictionofuscovid19cases
AT chihebhamza interplayofdemographicvariablesandsocialdistancingscoresindeeppredictionofuscovid19cases
AT fanjianqing interplayofdemographicvariablesandsocialdistancingscoresindeeppredictionofuscovid19cases