Identifying Best Practices for Future Pandemic Preparedness: A Comparative Policy Analysis

Heewon Choi and Eli Epstein-Deutsch

No 7mwbj, SocArXiv from Center for Open Science

Abstract: Background: This comparative policy analysis studies government responses to the COVID-19 pandemic, with a focus on countries severely impacted by the virus. The study aims to assess the impact of various confounding variables, including GDP, healthcare spending per capita, poverty rate, and population density, on the effectiveness of pandemic response policies. Methods: The data obtained for the policies employs a multifaceted approach that incorporates both economic and non-economic policies. The analysis includes fiscal policies encompassing healthcare and economic sectors, adaptability in policy adjustments, and non-economic measures. The study also utilizes a principal component analysis (PCA) to identify similarities and differences among countries with varying levels of success. Results: Key findings indicate that successful countries adopted proactive fiscal policies addressing healthcare and economic challenges simultaneously. Flexibility and adaptability in policy adjustments emerged as significant traits among effective responses. Stricter non-economic policies were generally associated with improved pandemic outcomes. Additionally, effective contact tracing played a pivotal role in case identification and isolation. Conclusions: This research underscores the importance of a comprehensive and adaptable approach to pandemic response, considering economic, healthcare, and social factors. The study's insights offer valuable guidance to governments and policymakers seeking to enhance preparedness plans for future global health crises. As the world continues to grapple with ongoing and evolving pandemic challenges, the lessons drawn from the pandemic can be used as a model of future success.

Date: 2024-01-02
New Economics Papers: this item is included in nep-hea
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Persistent link: https://EconPapers.repec.org/RePEc:osf:socarx:7mwbj

DOI: 10.31219/osf.io/7mwbj

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