The role of good governance in the race for global vaccination during the COVID-19 pandemic.


Journal

Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288

Informations de publication

Date de publication:
17 11 2021
Historique:
received: 17 04 2021
accepted: 03 11 2021
entrez: 18 11 2021
pubmed: 19 11 2021
medline: 15 12 2021
Statut: epublish

Résumé

Governments have developed and implemented various policies and interventions to fight the COVID-19 pandemic. COVID-19 vaccines are now being produced and distributed globally. This study investigated the role of good governance and government effectiveness indicators in the acquisition and administration of COVID-19 vaccines at the population level. Data on six World Bank good governance indicators for 172 countries for 2019 and machine-learning methods (K-Means Method and Principal Component Analysis) were used to cluster countries based on these indicators and COVID-19 vaccination rates. XGBoost was used to classify countries based on their vaccination status and identify the relative contribution of each governance indicator to the vaccination rollout in each country. Countries with the highest COVID-19 vaccination rates (e.g., Israel, United Arab Emirates, United States) also have higher effective governance indicators. Regulatory Quality is the most important indicator in predicting COVID-19 vaccination status in a country, followed by Voice and Accountability, and Government Effectiveness. Our findings suggest that coordinated global efforts led by the World Health Organization and wealthier nations may be necessary to assist in the supply and distribution of vaccines to those countries that have less effective governance.

Identifiants

pubmed: 34789826
doi: 10.1038/s41598-021-01831-0
pii: 10.1038/s41598-021-01831-0
pmc: PMC8599507
doi:

Substances chimiques

COVID-19 Vaccines 0
Vaccines 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

22440

Informations de copyright

© 2021. The Author(s).

Références

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Auteurs

Moosa Tatar (M)

Matheson Center for Health Care Studies, University of Utah, 295 Chipeta Way, Salt Lake City, UT, 84108, USA. moosa.tatar@utah.edu.
Department of Population Health Sciences, University of Utah, Salt Lake City, UT, USA. moosa.tatar@utah.edu.

Mohammad Reza Faraji (MR)

Department of Computer Science and Information Technology, Institute for Advanced Studies in Basic Sciences (IASBS), 444 Sobouti Blvd, Zanjan, Iran.

Jalal Montazeri Shoorekchali (J)

Institute for Humanities and Cultural Studies, Tehran, Iran.

José A Pagán (JA)

Department of Public Health Policy and Management, School of Global Public Health, New York University, 715/719 Broadway 10th Fl., New York, NY, 10003, USA.

Fernando A Wilson (FA)

Matheson Center for Health Care Studies, University of Utah, 295 Chipeta Way, Salt Lake City, UT, 84108, USA.
Department of Population Health Sciences, University of Utah, Salt Lake City, UT, USA.

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Classifications MeSH