School of Public Health and Preventive Medicine, Monash University, Melbourne, Victoria, Australia.
Centre for Youth Mental Health, University of Melbourne, Parkview, Victoria, Australia.
PLoS One. 2023 Mar 1;18(3):e0281655. doi: 10.1371/journal.pone.0281655. eCollection 2023.
Environmental disasters such as wildfires, floods and droughts can introduce significant interruptions and trauma to impacted communities. Children and young people can be disproportionately affected with additional educational disruptions. However, evaluating the impact of disasters is challenging due to difficulties in establishing studies and recruitment post-disasters.
We aimed to (1) develop a Bayesian model using aggregated school-level data to evaluate the impact of environmental disasters on academic achievement and (2) evaluate the impact of the 2014 Hazelwood mine fire (a six-week fire event in Australia).
Bayesian hierarchical meta-regression was developed to evaluate the impact of the mine fire using easily accessible 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.
Major academic interruptions across NAPLAN domains were evident in high exposure schools in the year post-mine fire (greatest interruption in Writing: 11.09 [95%CI: 3.16-18.93], lowest interruption in Reading: 8.34 [95%CI: 1.07-15.51]). The interruption was comparable to a four to a five-month delay in educational attainment and had not fully recovered after several years.
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 environmental disasters.
野火、洪水和干旱等环境灾害会给受灾社区带来重大的中断和创伤。儿童和年轻人受到的影响不成比例，他们的教育也会受到额外的中断。然而，由于在灾难后进行研究和招募存在困难，评估灾害的影响具有挑战性。
我们旨在 (1) 使用汇总的学校层面数据开发贝叶斯模型，以评估环境灾害对学业成绩的影响，(2) 评估 2014 年黑泽伍德矿火灾（澳大利亚持续六周的火灾事件）的影响。
采用贝叶斯层次元回归方法，使用国家评估计划-读写和计算能力测试（NAPLAN）中易于获取的汇总学校层面数据，评估矿火灾的影响。NAPLAN 结果和来自 69 所具有不同程度矿火相关烟雾暴露的小学/中学的学校特征（2008-2018 年）被用于估计该事件的影响。使用中断时间序列设计，该模型使用全贝叶斯统计推断估计事件发生后的即时效应和中断后趋势差异。
在矿火灾发生后的一年中，高暴露学校的 NAPLAN 各个领域都出现了重大的学业中断（写作中断最大：11.09[95%CI：3.16-18.93]，阅读中断最小：8.34[95%CI：1.07-15.51]）。这种中断相当于教育程度延迟了四到五个月，并且在几年后仍未完全恢复。
由于矿火灾，发现了相当大的学业延迟，这凸显了在应对未来事件时提供教育和社区支持的必要性。重要的是，这项工作提供了一种使用现成的汇总数据评估应对其他环境灾害的教育影响的统计方法。
