ABSTRACT
The COVID-19 pandemic remains a public health emergency, although effective vaccines are available. Unfortunately, vaccine hesitancy (VH) has mitigated the effectiveness of vaccination campaigns. Preferred approaches to estimate VH are surveys, polls, and questionnaires;however, these methods are limited in scope because they capture VH at a single point in time and mostly in highly populated (urban) areas. A dearth of published research points to a knowledge gap that limits the ability to explain changes in VH over time at the county level. The proposed research uses open-access databases and data-driven approaches to fill this knowledge gap. We present a systematic, data-driven framework that analyzes sentiments on social media and news coverage on COVID-19 to estimate VH changes over time at the county level in the U.S. Understanding how sentiments and topics contribute to VH can help public health officials develop tailored strategies to increase vaccine uptake for different counties of the U.S., especially when data is limited. Our study indicates that the use of social media and online news coverage led to more reliable predictions of VH estimates for urban than rural areas. Future research will consider other factors which impact VH, such as social/demographic factors, weather conditions, vaccine mandates, etc. © 2022 IISE Annual Conference and Expo 2022. All rights reserved.