Building an epidemiological modelling toolkit for epidemic preparedness

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This proposal aims to change how we predict and manage infectious diseases through the application of advanced mathematical methods to the development and analysis of models of infectious disease transmission. Recognizing limitations in current models exposed by the COVID-19 pandemic, such as delayed response times and challenges in adapting models to a new disease, this project proposes a novel approach. It centres on creating a flexible, transparent toolkit for building transmission models that can rapidly adapt to new information, enabling real-time decision-making during health crises.The methodology combines applied category theory (ACT) with operational modeling to simplify the construction and adaptation of complex disease models. ACT is a mathematical framework to describe complex systems in a structured and relational way, like a language for understanding how different parts of a system can fit together and interact, making it particularly useful for building and analyzing models in various fields, including epidemiology. By decomposing models into reusable components, the project intends to make the process of modeling more accessible and adaptable, fostering an environment where models can be quickly tailored to specific diseases or scenarios. Moreover, the research addresses the integration of these models with decision-making processes, acknowledging the uncertainty inherent in predicting disease spread and the effectiveness of interventions. It explores optimizing decisions under this uncertainty, aiming to provide robust support for public health strategies.Applications of this research will be demonstrated through models of measles and SARS-CoV-2, the virus that causes COVID-19, showcasing the toolkit's ability to replicate existing models and create new ones that can inform policy decisions. These demonstrations will benefit from a large and detailed dataset on the transmission dynamics of these infections, and will be run in a trusted research environment, where detailed epidemiological information can be used in the models in a safe, secure manner. Through workshops and open-source distribution of the underlying software, the project seeks to empower modelers, policymakers, and researchers, enhancing preparedness for future pandemics. This initiative not only advances the field of epidemiological modeling but also contributes to a more informed and flexible response to public health threats, potentially saving lives and resources by enabling swift, evidence-based action.