Increased population susceptibility to seasonal influenza during the COVID‐19 pandemic in China and the United States

Abstract To the best of our knowledge, no previous study has quantitatively estimated the dynamics and cumulative susceptibility to influenza infections after the widespread lifting of COVID‐19 public health measures. We constructed an imitated stochastic susceptible‐infected‐removed model using particle‐filtered Markov Chain Monte Carlo sampling to estimate the time‐dependent reproduction number of influenza based on influenza surveillance data in southern China, northern China, and the United States during the 2022–2023 season. We compared these estimates to those from 2011 to 2019 seasons without strong social distancing interventions to determine cumulative susceptibility during COVID‐19 restrictions. Compared to the 2011–2019 seasons without a strong intervention with social measures, the 2022–2023 influenza season length was 45.0%, 47.1%, and 57.1% shorter in southern China, northern China, and the United States, respectively, corresponding to an 140.1%, 74.8%, and 50.9% increase in scale of influenza infections, and a 60.3%, 72.9%, and 45.1% increase in population susceptibility to influenza. Large and high‐intensity influenza epidemics occurred in China and the United States in 2022–2023. Population susceptibility increased in 2019–2022, especially in China. We recommend promoting influenza vaccination, taking personal prevention actions on at‐risk populations, and monitoring changes in the dynamic levels of influenza and other respiratory infections to prevent potential outbreaks in the coming influenza season.