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Using Twitter to Track Unplanned School Closures: Georgia Public Schools, 2015-17

Published online by Cambridge University Press:  14 May 2020

Jennifer O. Ahweyevu ,
Ngozi P. Chukwudebe ,
Brittany M. Buchanan ,
Jingjing Yin ,
Bishwa B. Adhikari ,
Xiaolu Zhou ,
Zion Tsz Ho Tse Open the ORCID record for Zion Tsz Ho Tse [Opens in a new window] ,
Gerardo Chowell Open the ORCID record for Gerardo Chowell [Opens in a new window] ,
Martin I. Meltzer Open the ORCID record for Martin I. Meltzer [Opens in a new window]  and
Isaac Chun-Hai Fung Open the ORCID record for Isaac Chun-Hai Fung [Opens in a new window]
Jennifer O. Ahweyevu
Affiliation:
Department of Biostatistics, Epidemiology and Environmental Health Sciences, Jiann-Ping Hsu College of Public Health, Georgia Southern University, Statesboro, Georgia
Ngozi P. Chukwudebe
Affiliation:
Department of Biostatistics, Epidemiology and Environmental Health Sciences, Jiann-Ping Hsu College of Public Health, Georgia Southern University, Statesboro, Georgia
Brittany M. Buchanan
Affiliation:
Department of Biostatistics, Epidemiology and Environmental Health Sciences, Jiann-Ping Hsu College of Public Health, Georgia Southern University, Statesboro, Georgia
Jingjing Yin
Affiliation:
Department of Biostatistics, Epidemiology and Environmental Health Sciences, Jiann-Ping Hsu College of Public Health, Georgia Southern University, Statesboro, Georgia
Bishwa B. Adhikari
Affiliation:
Health Economics and Modeling Unit, Division of Preparedness and Emerging Infections, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia
Xiaolu Zhou
Affiliation:
Department of Geology and Geography, College of Science and Mathematics, Georgia Southern University, Statesboro, Georgia Department of Geography, Texas Christian University, Fort Worth, Texas
Zion Tsz Ho Tse
Affiliation:
School of Electrical and Computer Engineering, College of Engineering, The University of Georgia, Athens, Georgia Department of Electronic Engineering, University of York, Heslington, York, United Kingdom
Gerardo Chowell
Affiliation:
Department of Population Health Sciences, School of Public Health, Georgia State University, Atlanta, Georgia
Martin I. Meltzer
Affiliation:
Health Economics and Modeling Unit, Division of Preparedness and Emerging Infections, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia
Isaac Chun-Hai Fung*
Affiliation:
Department of Biostatistics, Epidemiology and Environmental Health Sciences, Jiann-Ping Hsu College of Public Health, Georgia Southern University, Statesboro, Georgia Health Economics and Modeling Unit, Division of Preparedness and Emerging Infections, National Center for Emerging and Zoonotic Infectious Diseases, Centers for Disease Control and Prevention, Atlanta, Georgia
*
Correspondence and reprint requests to Isaac Chun-Hai Fung, Department of Biostatistics, Epidemiology & Environmental Health Sciences, Jiann-Ping Hsu College of Public Health, P.O. Box 7989, Georgia Southern University, Statesboro, GA30460-7989 (e-mail: cfung@georgiasouthern.edu).
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Abstract

Objectives:

To aid emergency response, Centers for Disease Control and Prevention (CDC) researchers monitor unplanned school closures (USCs) by conducting online systematic searches (OSS) to identify relevant publicly available reports. We examined the added utility of analyzing Twitter data to improve USC monitoring.

Methods:

Georgia public school data were obtained from the National Center for Education Statistics. We identified school and district Twitter accounts with 1 or more tweets ever posted (“active”), and their USC-related tweets in the 2015-16 and 2016-17 school years. CDC researchers provided OSS-identified USC reports. Descriptive statistics, univariate, and multivariable logistic regression were computed.

Results:

A majority (1,864/2,299) of Georgia public schools had, or were in a district with, active Twitter accounts in 2017. Among these schools, 638 were identified with USCs in 2015-16 (Twitter only, 222; OSS only, 2015; both, 201) and 981 in 2016-17 (Twitter only, 178; OSS only, 107; both, 696). The marginal benefit of adding Twitter as a data source was an increase in the number of schools identified with USCs by 53% (222/416) in 2015-16 and 22% (178/803) in 2016-17.

Conclusions:

Policy-makers may wish to consider the potential value of incorporating Twitter into existing USC monitoring systems.

Keywords

digital healthpublic health surveillancesocial distancingsocial media
Type
Brief Report
Information
Disaster Medicine and Public Health Preparedness , Volume 15 , Issue 5 , October 2021 , pp. 568 - 572
Copyright
© 2020 Society for Disaster Medicine and Public Health, Inc.

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