Annual vaccination remains the primary public health strategy to mitigate the burden of influenza infection, and there is evidence that repeated influenza vaccination can affect the efficacy of the vaccine. This evidence arises not only from multiple observational studies of vaccine effectiveness but also studies of immunogenicity, including small trials. Understanding what causes influenza vaccines to be more or less effective in different people and populations is critical to the rational deployment of existing vaccines and the development of universal vaccines. But the causes of altered effectiveness and immunogenicity in repeat vaccinees are intrinsically difficult to study in populations in which vaccination is universally recommended, because repeat vaccinees differ from other vaccinees and non-vaccinees in important ways. These differences leave open the possibility of residual confounding in infection and vaccination history, and thus make it difficult to identify the effects of vaccination itself. We propose a randomized, clinical trial to investigate the effects of repeat vaccination and their underlying immunological causes in an adult population with low vaccination coverage and no recommendation for influenza vaccination. Approximately 820 adults in Hong Kong will be randomized into five groups, with one group vaccinated the first year, and other groups receiving placebo (saline) injections; each year, another group will start receiving the influenza vaccine, and will be vaccinated annually until the study ends after four years. This design will allow comparison of vaccine responses and failures (infections) in the placebo, newly vaccinated, and repeatedly vaccinated participants. Additionally, it will provide longitudinal samples of immune status and influenza-specific responses over time, from which we will develop predictive models of the response to vaccination and infection, including repeat vaccination. The proposed high-dimensional immunological profiling, coupled with statistical approaches that can accommodate the complexity of the key hypotheses, should maximize insight into the effects of repeated vaccination on seasonal influenza. The models will formalize, evaluate, and extend current theory, and thus provide a quantitative basis for anticipating vaccine non- responsiveness and improving vaccination strategies. Banked specimens will enable new hypotheses to be tested in the future.
Vaccination is a powerful intervention to reduce the burden of influenza infections, yet how repeated vaccination shapes the long-term development of protective immune responses to influenza is not clear. This research involves measuring immune responses of participants in a randomized, clinical trial of the inactivated influenza vaccine and using such data to fit predictive models of how vaccination and infection change immunity to influenza over time. This will provide important basic information for improving vaccination strategies against influenza.
