Commentary: strategies to address COVID-19 vaccine hesitancy and mitigate health disparities in minority populations - Teo, Jason Tze Wi (Frontiers Media S.A., 2021)
This commentary builds upon the article recently published by Strully et al., which highlights vaccine hesitancy particularly among minority groups and proposes strategies to mitigate this serious setback in combating the pandemic. In light of the surging third wave of COVID-19 due to more virulent variants, the aim of this commentary is to generate further discussion and debate on the urgent need to focus efforts in making available datasets for prediction of adverse reactions from COVID-19 vaccinations. The goal of achieving herd immunity is at the moment hampered by antivaxxers and general skepticism from the unvaccinated arising from concerns regarding the safety of COVID-19 vaccines. With a publicly-available COVID-19 vaccine adverse reaction dataset, the machine learning community would be able to conduct predictive analytics studies and develop prediction tools to allay fears of adverse reactions based on the individual health backgrounds of the potential vaccine candidates, and this could arguably increase the confidence of the unvaccinated to get vaccinated.