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A statistical look at the COVID-19 vaccine development and vaccine policies.
Apio, Catherine; Han, Kyulhee; Heo, Gyujin; Park, Taesung.
  • Apio C; Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, South Korea.
  • Han K; Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, South Korea.
  • Heo G; Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul, South Korea.
  • Park T; Department of Statistics, Seoul National University, Seoul National University, Seoul, South Korea.
Front Public Health ; 10: 1048062, 2022.
Article in English | MEDLINE | ID: covidwho-2199523
ABSTRACT
The global outbreak of COVID-19 caused by the SARS-CoV-2 virus elicited immense global interest in the development and distribution of safe COVID-19 vaccines by various governments and researchers, capable of stopping the spread of COVID-19 disease. After COVID-19 was declared a global pandemic, several vaccines have been developed for emergency use authorization. The accelerated development of the vaccines was attributed to many factors but mainly by capitalizing on years of research and technology development. Although several countries tried to develop COVID-19 vaccines only a few countries succeeded. Therefore, we applied statistical methods to find factors that have contributed to the fast development of COVID-19 vaccines. All 11 countries that developed vaccines were considered and chose other 24 countries for comparison purposes according to different criteria of their R&D. Fourteen R&D indicator variables that are a measure of the R&D for all countries [World Development Indicators (WDI)] were obtained from the World Bank DataBank and data on the COVID-19 vaccine R&D were obtained from The Knowledge Portal of the Graduate Institute Geneva and Global Health Center. The World Bank records WDI yearly, and 2019 was chosen because of a few missing values. Also, different vaccine policies were adopted by different countries during the COVID-19 vaccination period, producing different impacts of vaccinations on the population. So, we applied the generalized estimating equations (GEE) approach to find policies that contributed greatly to decreasing the spread of COVID-19 using data from the Oxford COVID-19 Government Response Tracker (OxCGRT) and age-specific vaccination data from the European Center for Disease and Prevention and Control. Logistic regression, two-sample t-test, and Wilcoxon rank-sum test found scientific and technical journals, liability, and COVID-19 Vaccine R&D Funding (investment in pharmaceutical industry US$) are significantly associated with fast COVID-19 vaccine development. Vaccine prioritization and government vaccine financial support were significantly associated with COVID-19 daily cases. The impact of vaccination on lowering the rate of new cases is greatly observed among the mid-aged populations (25-64 years) and lower or non-significant among the younger (<25 years) and (>65 years) older populations. Therefore, these age-groups especially > 79 can be prioritized during vaccine roll-out.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Vaccines / COVID-19 Type of study: Experimental Studies / Observational study / Randomized controlled trials Topics: Vaccines / Variants Limits: Humans / Middle aged Language: English Journal: Front Public Health Year: 2022 Document Type: Article Affiliation country: Fpubh.2022.1048062

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Vaccines / COVID-19 Type of study: Experimental Studies / Observational study / Randomized controlled trials Topics: Vaccines / Variants Limits: Humans / Middle aged Language: English Journal: Front Public Health Year: 2022 Document Type: Article Affiliation country: Fpubh.2022.1048062