Unpredictability in seasonal infectious diseases spread

In this work, we study the unpredictability of seasonal infectious diseases considering a SEIRS model with forcing. To investigate dynamical behaviour, compute bifurcation diagrams type hysteresis and their respective Lyapunov exponents. Our results from bifurcations largest exponent show bistable dynamics for all parameters model. Choosing inverse latent period as control parameter, over 70% interval comprises coexistence periodic chaotic attractors, dynamics. Despite competition between these ones are preferred. The bistability occurs in two wide regions. One regions is limited by while attractors bound other. As boundary second region composed it possible to interpret critical points tipping points. other words, depending on period, attractor (predictability) can evolve (unpredictability). Therefore, that associated preferably chaotic, and, furthermore, there point unpredictable