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

2019冠状病毒病大流行催生了将数学模型与工程和社会背景联系起来的研究呈指数级增长。最大的悬而未决的问题之一是如何将人口水平的疾病传播模型与高保真度的个体在建筑物内的行为联系起来。这发展了工程学、计算机和数学之间的联系，以研究室内环境中的人类行为建模和风险。将创建用于预测表面接触的新方法，该方法将通过机器学习，观察研究和微生物验证与暴露模型相结合。

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.