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Prediction of COVID-19 Social Distancing Adherence (SoDA) on the United States county-level

Medicine and Health

Prediction of COVID-19 Social Distancing Adherence (SoDA) on the United States county-level

M. Ingram, A. Zahabian, et al.

This enlightening study by Myles Ingram, Ashley Zahabian, and Chin Hur delves into the fascinating relationship between demographic factors and social distancing adherence across US counties. With a robust prediction model achieving 90.8% accuracy, their findings shed light on how economic, health, and political elements influence social behavior, offering crucial insights for health policy and interventions.

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Playback language: English
Abstract
This study investigates the correlation between demographic features and social distancing adherence (SoDA) across US counties. Using mobile phone data and population statistics from 3054 counties, the researchers identified key demographic features correlated with SoDA. A multivariable bagging regression algorithm was developed to predict SoDA, achieving 90.8% accuracy. The study highlights the impact of economic, health, and political factors on SoDA and proposes the prediction model as a valuable tool for informing health policy and interventions.
Publisher
Humanities and Social Sciences Communications
Published On
Mar 23, 2021
Authors
Myles Ingram, Ashley Zahabian, Chin Hur
Tags
social distancing
demographic features
US counties
predictive modeling
health policy
mobile phone data
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