Taube, J. C.; Merritt, A.; Bansal, S.

Publication practices accumulate to affect credibility and career advancement. Understanding authorship and citation practices is critical to addressing inequities. While citation bias has been demonstrated in several fields, it remains uncharacterized in infectious disease dynamics (IDD), a quantitative, interdisciplinary domain highly visible during the COVID-19 pandemic. We analyze IDD articles and their bibliographies from 2000-2019 using machine-learning algorithms to infer the gender and race/ethnicity of each article\'s lead and senior author. We examine authorship and citation patterns by gender and racial group across geographic scales, including characterizing the author composition of each article\'s bibliography relative to the field. Our analysis reveals persistent gender and race imbalances in IDD research. Man-authored and White-authored publications dominate the field, with little progress in racial diversification of US and UK publications over the last two decades. Woman-authored articles have the most representative citation practices but are undercited, especially when women are senior authors. In the US and UK, most citations feature White lead and senior authors, even when citing articles with lead or senior authors of color. These findings underscore the urgent need for more inclusive IDD research practices. We discuss possible mechanisms and solutions to create opportunities for researchers from underrepresented groups.