Coupling homogeneous population infection risk models with high-fidelity human behaviour predictions

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The COVID-19 pandemic has spawned an exponential growth in research that links mathematical models with an engineering and social context. One of the biggest unanswered question is how to link population level disease spread models with high fidelity ones of how individuals behave within buildings. This develops connections between engineering, computing and mathematics to study human behaviour modelling and risk in indoor environments. New methodology will be created for predicting surface touching which will be coupled with exposure models through machine learning, observational studies and microbiological validation.