Waning immunity and reinfection are critical features of many infectious diseases, but epidemiological models often fail to capture the interaction between an individual’s immunity history and their current infection status, or do so only simplistically. We develop a dual-age structured model tracking immunity age (time since last recovery) and infection age (time since infection) to analyze epidemic dynamics under waning immunity and reinfection. The model is formulated as a system of age-structured partial differential equations describing susceptible and infected populations stratified by both age variables. The contact rate, mortality and recovery rates, susceptibility, and pathogen load are all treated as parameter functions depending on both immunity and infection age. We derive basic reproduction numbers and numerically solve the system using a second-order Runge-Kutta scheme along characteristic lines. We further extend the model to treat vaccination interventions, specifically booster vaccination strategies targeting individuals by immunity age - interventions that cannot be formulated in standard models. Numerical results reveal that higher contact rates produce larger oscillation amplitudes with longer inter-epidemic periods. However, long-term oscillation amplitude and cumulative infections depend non-monotonically on the initial infected population size, indicating that the relationship between initial infection levels and long-term epidemic outcomes is not straightforward. Vaccination efficiency depends critically on the pathogen load profile, with more concentrated distributions requiring higher vaccination rates for elimination. Most efficient strategies target intermediate immunity ages rather than only fully waned individuals.

KOVACEVIC Raimund;  STILIANAKIS Nikolaos;  VELIOV Vladimir; 

2026-07-01

SPRINGER

JRC144489

1522-9602 (online),   

https://doi.org/10.1007/s11538-026-01686-4,    https://publications.jrc.ec.europa.eu/repository/handle/JRC144489,   

10.1007/s11538-026-01686-4 (online),