Resurgence of Large-Scale Influenza A (H1N1) Outbreaks: the Interplay of Transmission, Loss of Immunity, and Vaccination.

Influenza is a highly transmissible respiratory virus that can cause devastating pandemics. The last influenza pandemic, caused by a strain of A(H1N1) virus, resulted in millions of cases and hundreds of thousands of deaths worldwide. After the initial outbreaks, many regions experienced subsequent waves driven by environmental conditions, waning immunity, and other factors. More dramatically, several locations saw large resurgent outbreaks, yet the mechanisms behind these severe resurgences remain poorly understood. Here we investigate the dynamics of these large-scale H1N1 outbreaks using a mechanistic model with time-varying rates of infection, loss of immunity, and vaccination. In particular, we explore two mathematical functions to model dynamic loss of immunity, capturing how viral evolution may reduce the duration of immune protection. Numerical simulations reveal regimes that influence resurgence timing, and the model reproduces key features of H1N1 flu case data. We also fit the model to data from nine locations, demonstrating its ability to capture resurgence patterns and track associated changes in infection and immunity-loss rates. Our findings highlight the complex interplay among environmental drivers, population immunity, and viral mutation, contributing to a better understanding of large-scale H1N1 dynamics in the post-pandemic era.