Epidemiological impacts of post-infection mortality

Area of Science:

• Epidemiology
• Mathematical Biology
• Public Health

Background:

• Infectious diseases can cause long-term damage and mortality after recovery, a phenomenon known as post-infection mortality (PIM).
• The impact of PIM on the dynamics of infectious disease epidemics remains largely unknown.
• Long COVID serves as a recent example of potential long-term health consequences and mortality following infection.

Purpose of the Study:

• To investigate the influence of post-infection mortality (PIM) on epidemic dynamics using an epidemiological model.
• To determine how PIM affects disease cycling and stability compared to mortality during the acute infection phase.
• To assess the role of host immunity robustness in modulating the effects of PIM on epidemics.

Main Methods:

• Development and analysis of an epidemiological model that explicitly incorporates post-infection mortality (PIM).
• Mathematical modeling to examine the conditions under which PIM can induce epidemic cycling.
• Analysis of the interaction between PIM, host susceptibility, and the robustness of immunity.

Main Results:

• Post-infection mortality (PIM), unlike mortality during infection, can induce epidemic cycling.
• Epidemic cycling is driven by the interplay between elevated mortality and reinfection dynamics in the susceptible pool.
• Robust immunity reduces the likelihood of cycling, while weak PIM can generate periodicity when interacting with disease-induced mortality.

Conclusions:

• Post-infection mortality (PIM) is a significant, often overlooked, factor that can destabilize epidemic dynamics.
• Characterizing heterogeneity in host susceptibility, including PIM and immunity robustness, is essential for accurate epidemiological predictions.
• For diseases like SARS-CoV-2 lacking robust immunity, PIM may drive complex epidemic patterns, particularly with seasonal influences.