  We propose an SIR epidemic model coupled with opinion dynamics to study an
epidemic and opinions spreading in a network of communities. Our model couples
networked SIR epidemic dynamics with opinions towards the severity of the
epidemic, and vice versa. We develop an epidemic-opinion based threshold
condition to capture the moment when a weighted average of the epidemic states
starts to decrease exponentially fast over the network, namely the peak
infection time. We define an effective reproduction number to characterize the
behavior of the model through the peak infection time. We use both analytical
and simulation-based results to illustrate that the opinions reflect the
recovered levels within the communities after the epidemic dies out.
