Document Type

Thesis or dissertation

Date of this Version

12-2020

Advisor

Mark V. Pauly

Abstract

Importance: This study provides a prompt analysis of the effectiveness of COVID-19 policies on a comparative scale. Ultimately, this study aims to foster national and international-level institutional learnings to better prepare for future infectious disease outbreaks.

Objective: To analyze the variations in COVID-19 control outcomes and understand what factors contribute to such disparities in eight different Asian countries/regions: Beijing, Henan Province, Guangdong Province, Zhejiang Province, Hong Kong, Taiwan, South Korea, and Singapore.

Study Design: This study first utilizes a comprehensive literature review to summarize the current sentiments and scholarly comments about the COVID policy response. Then the study proposes five different hypotheses to explain the differences in outcomes. Finally, the study implements both quantitative and qualitative analyses to validate the proposed hypotheses

Data and Methods: This research relies heavily on both primary and secondary data collection. Primary data centers around the policy collection and secondary data focus on outcome-related variables. Then a correlation analysis and regression models are provided with different variations of the input and output variables.

Results: Strength of the economy, experiences dealing with past pandemics, and timeliness of response are the three most important factors influencing the effectiveness of COVID responses.

Conclusion and Relevance: These findings suggest that to have effective control of infectious disease outbreaks, it’s important to react early. Regions with more experience should be more careful about future disease outbreaks as they may be more susceptible to transmission in general. Future studies should focus on discovering more details about different local-level policies and expand the regions of comparison to a larger context.

Keywords

COVID-19, policy, pandemics, effective control, institutional learnings

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Date Posted:20 January 2021

 

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