Evaluating the risk of adverse outcomes following vaccination during a typical respiratory infection season

Seasonal respiratory viruses (RSV, influenza, and SARS-CoV-2) cause substantial morbidity and mortality, and although vaccination reduces infection and severe disease, rare autoimmune, neurologic, and cardiovascular adverse events complicate assessment of the net health impact of vaccination. A key challenge is that viral infection both increases the risk of these outcomes and influences healthcare seeking and vaccination, acting as a time-varying confounder and mediator that is incompletely and differentially captured in real-world data. The objective of this project is to quantify the net individual- and population-level health effects of respiratory virus vaccination on infection and downstream adverse outcomes while rigorously accounting for the causal role and imperfect measurement of infection. We will evaluate epidemiologic designs and analytic methods for estimating vaccine effectiveness under incomplete infection ascertainment, apply g-formula–based causal methods to estimate total and infection-mediated effects of vaccination on autoimmune, neurologic, and cardiovascular outcomes, and integrate these estimates into a multi-pathogen agent-based model to assess how alternative vaccination policies shape population health burden. This work will provide methodologically rigorous, policy-relevant evidence to inform vaccination risk–benefit assessment and guidelines for endemic respiratory viruses.