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BACKGROUND: For pandemic preparedness, researchers used online systematic searches to track unplanned school closures (USCs). We determine if Twitter provides complementary data. METHODS: Twitter handles of Michigan public schools and school districts were identified. All tweets associated with these handles were downloaded. USC‐related tweets were identified using 5 keywords. Descriptive statistics and multivariable logistic regression were performed in R. RESULTS: Among 3469 Michigan public schools, 2003 maintained their own active Twitter accounts or belonged to school districts with active Twitter accounts. Of these 2003 schools, in 2015‐2016 school year, at least 1 USC announcement was identified for 349 schools via the current method only, 678 schools via Twitter only, and 562 schools via both methods. No USC announcements were identified for 414 schools. Rural schools were less likely than city schools to have active Twitter coverage (adjusted relative risk [adjRR] = 0.3956, 95% confidence interval [CI] 0.3312‐0.4671), and to announce USCs on Twitter (adjRR = 0.5692, 95% CI 0.4645‐0.6823), but more likely to have USCs identified by the current method (adjRR = 1.4545, 95% CI 1.3545‐1.5490). CONCLUSIONS: Each method identified USCs that were missed by the other. Our results suggested that identifying USCs on Twitter is complementary to the current method. [ABSTRACT FROM AUTHOR]

Background: The Office of Advanced Molecular Detection (OAMD), Centers for Disease Control and Prevention (CDC), manages a Twitter profile (@CDC_AMD). To our knowledge, no prior study has analyzed a CDC Twitter handle's entire contents and all followers. Objective: This study aimed to describe the contents and followers of the Twitter profile @CDC_AMD and to assess if attaching photos or videos to tweets posted by @CDC_AMD would increase retweet frequency. Methods: Data of @CDC_AMD were retrieved on November 21, 2016. All followers (N=809) were manually categorized. All tweets (N=768) were manually coded for contents and whether photos or videos were attached. Retweet count for each tweet was recorded. Negative binomial regression models were applied to both the original and the retweet corpora. Results: Among the 809 followers, 26.0% (210/809) were individual health professionals, 11.6% (94/809) nongovernmental organizations, 3.3% (27/809) government agencies' accounts, 3.3% (27/809) accounts of media organizations and journalists, and 0.9% (7/809) academic journals, with 54.9% (444/809) categorized as miscellaneous. A total of 46.9% (360/768) of @CDC_AMD's tweets referred to the Office's website and their current research; 17.6% (135/768) referred to their scientists' publications. Moreover, 80% (69/86) of tweets retweeted by @CDC_AMD fell into the miscellaneous category. In addition, 43.4% (333/768) of the tweets contained photos or videos, whereas the remaining 56.6% (435/768) did not. Attaching photos or videos to original @CDC_AMD tweets increases the number of retweets by 37% (probability ratio=1.37, 95% CI 1.13-1.67, P=.002). Content topics did not explain or modify this association. Conclusions: This study confirms CDC health communicators' experience that original tweets created by @CDC_AMD Twitter profile sharing images or videos (or their links) received more retweets. The current policy of attaching images to tweets should be encouraged. [ABSTRACT FROM AUTHOR]