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.

Objective: Researchers at the Centers for Disease Control and Prevention monitor unplanned school closure (USC) reports through online systematic searches (OSS) to assist public health emergency responses. We counted the additional reports identified through social media along with OSS to improve USC monitoring. Methods: Facebook and Twitter data of public-school districts and private schools in counties affected by California wildfires in October and December of 2017 and January of 2018 were retrieved. We computed descriptive statistics and performed multivariable logistic regression for both OSS and social media data. Results: Among the 362 public-school districts in wildfire-affected counties, USCs were identified for 115 (32%) districts, of which OSS identified 104 (90%), Facebook, 59 (52%), and Twitter, 37 (32%). These data correspond to 4622 public schools, among which USCs were identified for 888 (19.2%) schools, of which OSS identified 722 (81.3%), Facebook, 496 (55.9%), and Twitter, 312 (35.1%). Among 1289 private schools, USCs were identified for 104 schools, of which OSS identified 47 (45.2%), Facebook, 67 (64.4%), and Twitter, 29 (27.9%). USC announcements identified via social media, in addition to those via OSS, were 11 public school districts, 166 public schools, and 57 private schools. Conclusion: Social media complements OSS as additional resources for USC monitoring during disasters.