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DOI 10.2196/33231

Медицинская библиотека · Journal of medical Internet research · 2021

Predictive Modeling of Vaccination Uptake in US Counties: A Machine Learning-Based Approach.

Cheong Queena, Au-Yeung Martin, Quon Stephanie, Concepcion Katsy, Kong Jude Dzevela

СтатьяПоддержка исследования: вне правительства СШАПеревод пока не подготовлен

Аннотация

BACKGROUND

Although the COVID-19 pandemic has left an unprecedented impact worldwide, countries such as the United States have reported the most substantial incidence of COVID-19 cases worldwide. Within the United States, various sociodemographic factors have played a role in the creation of regional disparities. Regional disparities have resulted in the unequal spread of disease between US counties, underscoring the need for efficient and accurate predictive modeling strategies to inform public health officials and reduce the burden on health care systems. Furthermore, despite the widespread accessibility of COVID-19 vaccines across the United States, vaccination rates have become stagnant, necessitating predictive modeling to identify important factors impacting vaccination uptake.

OBJECTIVE

This study aims to determine the association between sociodemographic factors and vaccine uptake across counties in the United States.

METHODS

Sociodemographic data on fully vaccinated and unvaccinated individuals were sourced from several online databases such as the US Centers for Disease Control and Prevention and the US Census Bureau COVID-19 Site. Machine learning analysis was performed using XGBoost and sociodemographic data.

RESULTS

Our model predicted COVID-19 vaccination uptake across US counties with 62% accuracy. In addition, it identified location, education, ethnicity, income, and household access to the internet as the most critical sociodemographic features in predicting vaccination uptake in US counties. Lastly, the model produced a choropleth demonstrating areas of low and high vaccination rates, which can be used by health care authorities in future pandemics to visualize and prioritize areas of low vaccination and design targeted vaccination campaigns.

CONCLUSIONS

Our study reveals that sociodemographic characteristics are predictors of vaccine uptake rates across counties in the United States and, if leveraged appropriately, can assist policy makers and public health officials to understand vaccine uptake rates and craft policies to improve them.

Для цитирования: Cheong Queena, Au-Yeung Martin, Quon Stephanie, Concepcion Katsy, Kong Jude Dzevela. Predictive Modeling of Vaccination Uptake in US Counties: A Machine Learning-Based Approach.. Journal of medical Internet research. 2021. DOI: 10.2196/33231.

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