Population effect of influenza vaccination under co-circulation of non-vaccine variants and the case for a bivalent A/H3N2 vaccine component

Message in a bottle: mRNA vaccination for influenza

Current influenza vaccines, while being the best method of managing viral outbreaks, have several major drawbacks that prevent them from being wholly-effective. They need to be updated regularly and require extensive resources to develop. When considering alternatives, the recent deployment of mRNA vaccines for SARS-CoV-2 has created a unique opportunity to evaluate a new platform for seasonal and pandemic influenza vaccines. The mRNA format has previously been examined for application to influenza and promising data suggest it may be a viable format for next-generation influenza vaccines. Here, we discuss the prospect of shifting global influenza vaccination efforts to an mRNA-based system that might allow better control over the product and immune responses and could aid in the development of a universal vaccine.

Models to predict the public health impact of vaccine resistance: A systematic review

Pathogen evolution is a potential threat to the long-term benefits provided by public health vaccination campaigns. Mathematical modeling can be a powerful tool to examine the forces responsible for the development of vaccine resistance and to predict its public health implications. We conducted a systematic review of existing literature to understand the construction and application of vaccine resistance models. We identified 26 studies that modeled the public health impact of vaccine resistance for 12 different pathogens. Most models predicted that vaccines would reduce overall disease burden in spite of evolution of vaccine resistance. Relatively few pathogens and populations for which vaccine resistance may be problematic were covered in the reviewed studies, with low- and middle-income countries particularly under-represented. We discuss the key components of model design, as well as patterns of model predictions.

Intermediate levels of vaccination coverage may minimize seasonal influenza outbreaks

For most pathogens, vaccination reduces the spread of the infection and total number of cases; thus, public policy usually advocates maximizing vaccination coverage. We use simple mathematical models to explore how this may be different for pathogens, such as influenza, which exhibit strain variation. Our models predict that the total number of seasonal influenza infections is minimized at an intermediate (rather than maximal) level of vaccination, and, somewhat counter-intuitively, further increasing the level of the vaccination coverage may lead to higher number of influenza infections and be detrimental to the public interest. This arises due to the combined effects of: competition between multiple co-circulating strains; limited breadth of protection afforded by the vaccine; and short-term strain-transcending immunity following natural infection. The study highlights the need for better quantification of the components of vaccine efficacy and longevity of strain-transcending cross-immunity in order to generate nuanced recommendations for influenza vaccine coverage levels.