AbstractFear and anxiety about COVID-19 have swept across the globe. Understanding the factors that contribute to increased emotional distress regarding the pandemic is paramount—especially as experts warn about rising cases. Despite large amounts of data, it remains unclear which variables are essential for predicting who will be most affected by the distress of future waves. We collected cross-sectional data on a multitude of socio-psychological variables from a sample of 948 United States participants during the early stages of the pandemic. Using a cross-validated hybrid stepwise procedure, we developed a descriptive model of COVID-19 emotional distress. Results reveal that trait anxiety, gender, and social (but not government) media consumption were the strongest predictors of increasing emotional distress. In contrast, commonly associated variables, such as age and political ideology, exhibited much less unique explanatory power. Together, these results can help public health officials identify which populations will be especially vulnerable to experiencing COVID-19-related emotional distress.