To comprehend the dynamics of infectious disease transmission, it is imperative to incorporate human protective behavior into models of disease spreading. While models exist for both infectious disease and behavior dynamics independently, the integration of these aspects has yet to yield a cohesive body of literature. Such an integration is crucial for gaining insights into phenomena like the rise of infodemics, the polarization of opinions regarding vaccines, and the dissemination of conspiracy theories during a pandemic. 
We make a threefold contribution. First, we introduce a framework to describe models coupling infectious disease and behavior dynamics, delineating four distinct update functions. Reviewing existing literature, we highlight a substantial diversity in the implementation of each update function. This variation, coupled with a dearth of model comparisons, renders the literature hardly informative for researchers seeking to develop models tailored to specific populations, infectious diseases, and forms of protection.
Second, we advocate an approach to comparing models' assumptions about human behavior, the model aspect characterized by the strongest disagreement. Rather than representing the psychological complexity of decision-making, we show that "influence-response functions'' allow one to identify which model differences generate different disease dynamics and which do not, guiding both model development and empirical research testing model assumptions. 
Third, we propose recommendations for future modeling endeavors and empirical research aimed at selecting models of coupled infectious disease and behavior dynamics. We underscore the importance of incorporating empirical approaches from the social sciences to propel the literature forward.
Keywords: agent based models; compartmental models; epidemiology; infectious disease dynamics; opinion dynamics; sociophysics.
Creative Commons Attribution license.