  Sexually transmitted infections (STIs) continue to present a complex and
costly challenge to public health programs. The preferences and social dynamics
of a population can have a large impact on the course of an outbreak as well as
the effectiveness of interventions intended to influence individual behavior.
In addition, individuals may alter their sexual behavior in response to the
presence of STIs, creating a feedback loop between transmission and behavior.
We investigate the consequences of modeling the interaction between STI
transmission and prophylactic use with a model that links a
Susceptible-Infectious-Susceptible (SIS) system to evolutionary game dynamics
that determine the effective contact rate. The combined model framework allows
us to address protective behavior by both infected and susceptible individuals.
Feedback between behavioral adaptation and prevalence creates a wide range of
dynamic behaviors in the combined model, including damped and sustained
oscillations as well as bistability, depending on the behavioral parameters and
disease growth rate. We found that disease extinction is possible for multiple
regions where R0 > 1, due to behavior adaptation driving the epidemic downward,
although conversely endemic prevalence for arbitrarily low R0 is also possible
if contact rates are sufficiently high. We also tested how model
misspecification might affect disease forecasting and estimation of the model
parameters and R0. We found that alternative models that neglect the behavioral
feedback or only consider behavior adaptation by susceptible individuals can
potentially yield misleading parameter estimates or omit significant features
of the disease trajectory.
