Differences in infectious disease risk, acquisition, and severity arise from intersectional systems of oppression and resulting historical injustices that shape individual behavior and circumstance. We define historical injustices as distinct events and policies that arise out of intersectional systems of oppression. We view historical injustices as a medium through which structural forces affect health both directly and indirectly, and are thus important to study in the context of infectious disease disparities. In this critical analysis we aim to highlight the importance of incorporating historical injustices into mathematical models of infectious disease transmission and provide context on the methodologies to do so. We offer two illustrations of elements of model building (i.e., parameterization, calibration and validation) that can allow for a better understanding of health disparities in infectious disease outcomes. Mathematical models that do not recognize the historical forces that underlie infectious disease dynamics inevitably lead to the individualization of our focus and the recommendation of untenable individual-behavioral prescriptions to address the burden of infectious disease.