Predictive Modeling of Influenza-Pneumococcal Coinfection

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Influenza A virus (IAV) and secondary bacterial infections (SBI) are responsible for a significant number of illnesses and deaths each year. Management of these diseases is difficult, in part due to a lack of understanding of complex interplay of host-pathogen interactions and inability to study pneumonia in clinical settings. To advance the goal of developing effective therapeutics and predicting IAV and SBI risk, new microbiologic tools that can assess how host immune responses work to limit viral burden and enhance bacterial invasion in quantitative detail is essential. This project addresses gaps in immunological knowledge of IAV and SBIs and gaps in developing predictive models and interpreting infection data by using a tandem mathematical-experimental approach to quantify alveolar macrophage loss (Aim 1) and SBI related type I interferon exacerbation (Aim 2). These studies will exploit the predictive models to establish the intricate feedbacks in these responses, identify controlling parameters and dynamics that govern different clinical outcomes, improve interpretation of immunological and clinical data, and reveal new targets for treatment and prevention of influenza and related bacterial infections.