Commentary: Strategies to Address COVID-19 Vaccine Hesitancy and Mitigate Health Disparities in Minority Populations.

Jason Teo

doi:10.3389/fpubh.2021.723583

Abstract

Commentary: Strategies to Address COVID-19 Vaccine Hesitancy and Mitigate Health Disparities in Minority Populations.

Highlights

This commentary builds upon the article recently published by Strully et al(1), which highlights vaccine hesitancy among minority groups and proposes strategies to mitigate this serious setback in combating the pandemic
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

Summary

Introduction

This commentary builds upon the article recently published by Strully et al(1), which highlights vaccine hesitancy among minority groups and proposes strategies to mitigate this serious setback in combating the pandemic. 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.

Results

Conclusion