Addressing New Modelling and Data Challenges Revealed by The COVID-19 Pandemic

The COVID pandemic and associated interventions revealed a large number of new challenges for mathematical modeling of infectious disease. This research program will focus on an important subset of these questions

• How can mathematical epidemiological models quantify and contrast the ethical or social outcomes of disease interventions, in addition to the clinical?
• How can we provide speed and scalability when transforming data into actionable scenarios and forecasts? In particular, how to develop leaner agent-based models and rapid uncertainty quantification, harnessing larger multi-scale epidemiological, genomic, clinical and behavioural data?

These challenges are intertwined: by integrating public health ethics into the modelling process, we may aspire to avoid pitfalls of model-driven policy applied in fast-paced crisis scenarios. If we cannot balance the need for speed with the requirement of socially responsible policy, mathematical and computational tools will, at best, be subject to consultative bottlenecks in application and at worst, will risk advocating unethical interventions. The research program will focus on these questions, with input from researchers from countries having a wide range of experiences during the COVID pandemic.