Unplanned Closure of Public Schools in Michigan, 2015-2016: Cross-Sectional Study on Rurality and Digital Data Harvesting.

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.