Speaker
Description
Post-infection mortality is an important yet often overlooked factor in epidemiological modeling, as it directly influences both disease prevalence and long-term population structure. In this work, we revisit and analyze compartmental models that explicitly incorporates post-infection mortality along with partial immunity, and we investigate how disease outcomes depend on the choice of incidence function. Under mass-action incidence, the inclusion of post-infection mortality can generate complex dynamics, including bifurcations that lead to recurrent outbreaks. In contrast, when standard incidence is used, such oscillatory behavior is greatly reduced or eliminated, and the system typically converges to a stable endemic state. Our results show that modeling post-infection mortality in combination with different transmission assumptions leads to markedly different qualitative and quantitative outcomes, underscoring its significance for understanding persistent infections and for guiding more realistic epidemiological predictions.
