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Notes 1. Msemburi et al. (2022). 2. World Bank (2022). 3. Heckman (2006). 4. World Bank (2022). 5. Original calculations for this publication. The International Labour Organization (ILO) defines prime-age adults as those between the ages of 25 and 55. 6. Fox, Levi, and Nelson (2010); Johnson (2001); Mukherjee (2016). 7. Spelke and Schus (2022). 8. Egger et al. (2021); Miguel and Mobarak (2021). 9. WHO and UNICEF (2021). 10. Hillis et al. (2022). 11. Bau et al. (2022); Bullinger et al. (2021); Moya et al. (2021). 12. Bailey, Sun, and Timpe (2021). 13. For Bangladesh, Hamadani et al. (forthcoming); for Brazil, Maria Cecilia Souto Vidigal Foundation (2021). 14. Gertler et al. (2021); Grantham-McGregor et al. (1991). 15. These estimates include school-age children from pre-primary to upper-secondary education (ages 5–17) from 140 countries with a school-age population of 500,000 or more. For simplicity, it is assumed that one school year is equal to 32 academic weeks across all countries. World Bank estimations are based on data from the United Nations Educational, Scientific, and Cultural Organization (UNESCO) Institute for Statistics (UIS). 16. UNICEF and ITU (2020). 17. UNICEF, UNDP, and SMERU (2021). 18. Biswas et al. (2020). 19. This estimate is derived from a simple linear regression of learning losses on school closures with no constant. 20. This relationship is robust to a number of specifications, such as including all countries, excluding high-income countries, limiting the sample to the highest-quality studies, or excluding data points that disproportionately influence the regression results. Resulting coefficients are all significant and in the range of −0.28 to −0.42. 21. The chapter uses the terms youth and young people interchangeably. 22. Von Wachter (2020). 23. Chandir et al. (2021). 24. Singh, Romero, and Muralidharan (2022). References Bailey, M. J., S. Sun, and B. Timpe. 2021. "Prep School for Poor Kids: The Long-Run Impacts of Head Start on Human Capital and Economic Self-Sufficiency." American Economic Review 111 (12): 3963–4001. Bau, N., G. Khanna, C. Low, M. Shah, S. Sharmin, and A. Voena. 2022. "Women's Well-Being during a Pandemic and Its Containment." Journal of Development Economics 156: 102839. Biswas, K., T. M. Asaduzzaman, D. K. Evans, S. Fehrler, D. Ramachandran, and S. Sabarwal. 2020. "TV-Based Learning in Bangladesh." World Bank, Washington, DC. Bullinger, L. R., A. Boy, S. Messner, and S. Self-Brown. 2021. "Pediatric Emergency Department Visits Due to Child Abuse and Neglect following COVID-19 Public Health Emergency Declaration in the Southeastern United States." BMC Pediatrics 21 (401): 1–9. Chandir, S., D. A. Siddiqi, M. Mehmood, S. Iikhar, M. Siddique, S. Jai, V. K. Dharma, et al. 2021. "1-Year Impact of COVID-19 on Childhood Immunizations in Pakistan: Analysis of >3.7 Million Children." European Journal of Public Health 31 (Suppl. 3): ckab164.538. Executive Summary 13

• Front Cover
• Contents
• Main Messages
• Executive Summary
• The pandemic destroyed human capital at critical moments in the life cycle
• Policies to reverse human capital losses
• Building agile, resilient, and adaptive human development systems for future shocks
• A human capital recovery: What will it take?
• Notes
• References
• Figures
• Figure ES.1 The pandemic led to steep losses in early childhood development and early learning in very young children in Bangladesh and Brazil
• Figure ES.2 During the pandemic, each month of school closures led to one month of learning losses, and more so in countries with lower GDP per capita
• Figure ES.3 Youth employment fell in most countries during the pandemic
• Figure ES.4 Declines in employment of young people during the pandemic were not offset by increases inschooling or training
• Figure ES.5 What are the paths to recovery?
• Table
• Table ES.1 There are evidence-proven policies that can reverse human capital losses