Resilience of School Systems Following Severe Earthquakes

Abstract

Natural disasters may have catastrophic and long-lasting impacts on communities' physical, economic, and social infrastructure. Slow recovery of educational services following such events is likely to cause traumatic stress in children, lead families to out-migrate, and affect the community's overall social stability. Methods for quantifying and assessing the restoration process of educational systems and their dependencies on other supporting infrastructure have not received adequate attention. This study introduces, for the first time, a new framework to evaluate the functionality, recovery, and resilience of a school system following severe earthquake events. The framework considers both the quantity and quality of education services provided, school enrollment, and staff employment, as well as the interaction between various agents such as staff, students, parents, administration, and community. A virtual testbed community, Centerville, is utilized to highlight the application of this framework. The impact of school reopening policies on the number of students enrolled as well as the potential for homeschooling is also considered. The availability of various enrollment alternatives for students, backup classroom space and functioning utility systems, and facilitation of staff and supplies transfer between schools substantially increase the resilience of the education service. Plain Language Summary Recovery of educational services following natural disasters is key for ensuring the well-being of communities and for maintaining the overall social stability. Currently, there is a lack of quantifiable methodologies for assessing the restoration process of educational systems while accounting for their dependencies on other supporting infrastructure and the society. In this study, a new sociotechnical approach is devised for evaluating functionality, recovery, and resilience of a school system following severe earthquake events. The framework is applied to a virtual testbed to highlight its application. Various social and physical parameters are shown to have a substantial impact on the recovery trajectory and the overall resilience of the schools.

Healthcare and education networks interaction as an indicator of social services stability following natural disasters

“…There are eight schools distributed as four primary, two middle, and two high schools as the education service providers. The total number of students is 925, 871, and 1155 with the corresponding number of staff of 97, 91, and 161 for the primary, middle, and high school, respectively 35 .

Figure 1 Healthcare and education facilities distribution in the U.S. in 2020: ( a ) healthcare, ( b ) education, and ( c ) the investigated virtual community, which is a mid-size community in the Mid-America region with 50,000 total population served by three hospitals and eight schools.

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“…Hospitals and schools’ relevant data are obtained to construct the agent-based model as summarized in Table S1 in the Supplementary Information (SI) for the investigated community. These data include the functionality of different sub-components, available mitigation strategies, and resources at each facility 34 , 35 , 56 . Hospitals and school’s total functionalities are modeled (Section S1 and S2 in the SI, respectively).…”

“…To model these complicated systems, various components need to be considered. The main components of the healthcare system are healthcare providers, patients, regulators, payers, and suppliers 33 , 34 , while the main components of the education system are education providers, students, parents, administration, community, regulators, and suppliers 35 . Each of these providers, with hospitals or schools as the central components, comprises of various sub-components.…”

“…However, most previous studies were limited to a single facility 36 , 37 , neglected the interdependency between the investigated facilities and other community lifelines 38 , 39 , stopped short of including the system dynamics in terms of capacity and demand 40 , 41 , or only considered the quantity part of the offered services 31 , 41 . To overcome some of these limitations, however, recent studies focused on developing new physical-based frameworks, based on components’ realistic behavior, to model healthcare 34 and education systems 35 . In these frameworks, the healthcare service functionality was measured as a combination of the available staffed beds as an indicator of the healthcare service quantity and patient waiting time and patient treatment time as indicators of the healthcare service quality 34 .…”

“…In these frameworks, the healthcare service functionality was measured as a combination of the available staffed beds as an indicator of the healthcare service quantity and patient waiting time and patient treatment time as indicators of the healthcare service quality 34 . On the other hand, education service functionality was quantified in terms of the school enrollment capacity as an indicator of the education service quantity and a combination of teacher, classroom, and school qualities as indicators of the education service quality 35 .…”