This study investigated the association of socioeconomic and demographic factors with changes in workplaces mobility during the COVID-19 pandemic in the US, using a Bayesian spatial modeling framework. The analysis found that counties with higher income, older population, and lower density but larger workforce experienced larger drops in workplaces mobility during the lockdown phase, while those with higher household density observed increases in workplaces mobility during the recovery phase. The results also showed that neighboring counties exhibited similar patterns in changes in workplaces mobility, possibly due to state-wise regulations and their effect on neighboring states. These findings provide evidence of socioeconomic and demographic disparities in the US response to the pandemic and highlight the importance of considering neighborhood effects when modeling spatial data.