Evaluating the impact of Hazelwood mine fire event on students' educational development with Bayesian interrupted time-series hierarchical meta-regression [article]

Caroline X Gao, Jonathan C. Broder, Sam Brilleman, Emily Berger, Jill Ikin, Catherine L. Smith, Tim C.H. Campbell, Rory Wolfe, Fay Johnston, Yuming Guo, Matthew Carroll
2021 medRxiv   pre-print
Disasters and other community-wide events can introduce significant interruptions and trauma to impacted communities. Children and young people can be disproportionately affected with additional educational disruptions. With the increasing threat of climate change, establishing a timely and adaptable framework to evaluate the impact of disasters on academic achievement is needed. However, analytical challenges are posed by the availability issue of individual-level data. Methods: A new method,
more » ... ayesian hierarchical meta-regression, was developed to evaluate the impact of the 2014 Hazelwood mine fire (a six-week fire event in Australia) using only aggregated school-level data from the standardised National Assessment Program-Literacy and Numeracy (NAPLAN) test. NAPLAN results and school characteristics (2008-2018) from 69 primary/secondary schools with different levels of mine fire-related smoke exposure were used to estimate the impact of the event. Using an interrupted time-series design, the model estimated immediate effects and post-interruption trend differences with full Bayesian statistical inference. Results: Major academic interruptions across NAPLAN domains were evident in high exposure schools in the year post-mine fire (highest in Writing: 11.09 [95%CI: 3.16-18.93], lowest in Reading: 8.34 [95%CI: 1.07-15.51]). The interruption was comparable to a three to four-month delay in educational attainment and had not fully recovered after several years. Conclusions: Considerable academic delays were found as a result of a mine fire, highlighting the need to provide educational and community-based supports in response to future events. Importantly, this work provides a statistical method using readily available aggregated data to assess the educational impacts in response to other disasters
doi:10.1101/2021.03.28.21254516 fatcat:g4lqq5kf3zd55klclg2dy6ptfa