Title | Rethinking Lockdown Policies in the Pre-Vaccine Era of COVID-19: A Configurational Perspective |
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Type | Journal article |
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Authors | Zhang, Ziang, Liu, C., Nunkoo, R., Sunnassee, Vivek A. and Chen, Xiaoyan |
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Abstract | The significance of lockdown policies for controlling the COVID-19 pandemic is widely recognized. However, most studies have focused on individual lockdown measures. The effectiveness of lockdown policy combinations has not been examined from a configurational perspective. This research applies fuzzy-set qualitative comparative analysis (fsQCA) to examine different lockdown policy combinations associated with high-epidemic situations in 84 countries. A high-epidemic situation can occur through three different "weak-confined" patterns of lockdown policy combinations. The findings demonstrate that a combination of lockdown policies is more successful than any single lockdown policy, whereas the absence of several key measures in policy combinations can lead to a high-epidemic situation. The importance of international travel controls can become obscured when they are the only measures adopted, and a high-epidemic situation can still arise where restrictions are placed on international travel but not on public transport or when workplaces are closed but schools remain open. |
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Keywords | COVID-19 - epidemiology - prevention & control |
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| lockdown policy |
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| high epidemic |
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| Pandemics - prevention & control |
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| Humans |
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| comparative policy analysis |
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| fsQCA |
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| Communicable Disease Control |
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| Policy |
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| COVID-19 |
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| SARS-CoV-2 |
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| Vaccines |
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| pandemic |
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Article number | 7142 |
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Journal | International Journal of Environmental Research and Public Health |
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Journal citation | 19 (12) |
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ISSN | 1660-4601 |
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Year | 2022 |
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Publisher | MDPI |
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Publisher's version | License CC BY 4.0 File Access Level Open (open metadata and files) |
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Digital Object Identifier (DOI) | https://doi.org/ijerph19127142 |
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| https://doi.org/10.3390/ijerph19127142 |
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PubMed ID | 35742409 |
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Publication dates |
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Published online | 10 Jun 2022 |
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Project | 51808392 |
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Funder | National Natural Science Foundation of China |
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