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School closures are one of several non-pharmaceutical interventions (NPI) that governments may employ to minimize the spread of an infectious disease during an epidemic (Jackson et al. 2013; Fumanelli et al 2016). However, extended school closures may have wide ranging socioeconomic effects for children and their families, including a reduction in educational achievement for children (Eyles et al 2020). In terms of educational access, “experience from other crises has shown that the longer children stay out of school, the less likely they are to return” (UNICEF, 2015).
While it is too early to conclude how the ongoing COVID-19 pandemic related school closures will affect school enrolment in the mid-to-long term, evidence from previous experience provides insight. The 2014-16 Ebola epidemic in West Africa led to extended school closures of 5 to 9 months in Guinea, Liberia and Sierra Leone, interrupting the education of an estimated 5 million children. A few studies have explored the effects of these school closures on educational outcomes.
A phone survey of households by the World Bank in Liberia following school reopening found that 25 per cent of households with primary age children reported that their children did not return to school in the immediate aftermath of the crisis (World Bank 2015a). A similar survey in Sierra Leone estimated that 13 per cent did not return to school (Selbervick, 2020; World Bank 2015b). However, year-on-year analysis of school enrolment after the following school year in Liberia found that enrolment recovered over time and ultimately exceeded pre-Ebola levels (Darvas, et al 2016).
In an ethnographic study in Sierra Leone, Kostelny (2018) reported evidence of numerous cognitive harms related to full year school closures, particularly that children had forgotten what they had learned and some lost interest in learning and dropped out of school altogether.
With the above concerns, this study aims to take a deeper look at the effects of these school closures on access to education. It compares the prevalence and situation of OOS children in districts of higher and lower concentration of Ebola in the three most affected countries, before and after the outbreak. In sum, this study conducts an aggregated Difference-in-Differences (DID) design to identify how the 2014-16 Outbreak affected the number/rate of OOS children (of pre-primary, primary, lower secondary and upper secondary age) in the mid-to-long term.
The main data sources comprise eight DHS and four MICS. Districts within the three affected countries will be evenly grouped as high Ebola concentration vs. low Ebola concentration based on the infection rate. These surveys span from 2005 to 2020, sufficient to make assumption of pre-outbreak OOS trends for each district.
This study will also apply additional analyses to enable possible policy suggestions for the ongoing COVID-19 response. All analyses will be replicated for sub-groups based on gender, age group, wealth, and accessibility to improved water and sanitation. Furthermore, the study will take a deeper look at outlier districts to see what interventions were relatively effective in buffering OOS.