Diffusion-Driven Epidemic Dynamics: Synergy of Awareness, Behavioral Responses, and Healthcare Interventions

Infectious diseases constitute a multifaceted threat, affecting not just public health but also the social, economic, and psychological aspects of society. Here, we propose and analyze a diffusion-driven nonlinear epidemic model to investigate the impact of psychological fear on the direct transmission patterns of infectious diseases. First, we analyzed the equilibrium and stability of steady states derived from the temporal system. The temporal dynamics of the model system exhibit transcritical and Hopf-bifurcation under certain conditions. Moreover, the stability behavior of the endemic steady-state in a spatially extended setting has been examined. To fit our model, we used actual COVID-19 data from India and estimated essential epidemiological parameters. It is noteworthy to see that the increased psychological fear in a community can reduce the amplitude of bifurcating periodic solutions. Once the psychological fear factor reaches a certain threshold, the oscillations can be diminished, and endemic equilibrium stabilizes to a lower value. Our findings suggest that high levels of epidemic preparedness can mitigate infection in the community in the presence of awareness campaigns. The study additionally demonstrates that when the public migrates frequently, regulating infectious disease transmission patterns becomes challenging. We believe these findings could provide valuable insights into the spatial patterns of real epidemics and aid in the implementation of appropriate nonpharmaceutical interventions to suppress the disease burden.