Optimizing social assistance strategies in response to the COVID-19 crisis

The COVID-19 pandemic highlighted significant challenges in designing social assistance strategies for crisis management. This study investigates optimal approaches using theoretical modeling and multinomial logit analysis of data from 47 countries during the pre-vaccination phase of 2020. The findings underscore the importance of combining conditional (targeted) and unconditional (universal) social assistance measures, with unconditional assistance prioritized in severe crises due to its rapid implementation and broad reach. By addressing the complexities of resource allocation and policy implementation under crisis conditions, this study provides actionable insights for public policy design, emphasizing the need for robust budgetary systems to sustain multifaceted strategies, mitigate immediate impacts, and build resilience against future disruptions.