Mathematical and computational models are useful for predicting the fate of an epidemic, and while such models have become increasingly complex and realistic in recent times, a key ingredient is often ignored: human behavioral responses to the threat and/or presence of a disease [6] . How people assess risk of infection and how such risk assessment drives behavioral change is of great interest as individual social distancing can greatly affect the spread of an epidemic [7, 8, 9] . While the effect of behavioral change in response to perceived health threats on the spread of infectious diseases has been investigated theoretically for some time, particularly in the context of sexually transmitted diseases [8] , recent work has started addressing the problem in a broader context that is also applicable to the spread of influenza [6, 7] . This work has a strong, though as yet under-explored relationship to work on risk perception and health threats [10, 11, 12] .