Since the beginning of the coronavirus pandemic, the CCIMI and its faculty and students have been heavily involved in varying aspects of the research into the virus. Most prominently, Julia Gog has been providing advice to the Government through SPI-M, the specialist pandemic modelling group that feeds into SAGE, the Scientific Advisory Group for Emergencies, as well as through Cambridge’s Centre for Science and Policy (CSaP). Mike Cates has been chairing the Royal Society’s Rapid Assistance in Modelling the Pandemic (RAMP) initiative. And Tim Gowers has been serving in the Steering Committee of the Royal Society’s Data Evaluation and Learning for Viral Epidemics (DELVE) initiative. Ronojoy Adhikari and colleagues have released open source epidemiological modelling codes PyRoss and PyRossGeo for age-resolved and spatially-resolved modelling of pandemics.

Another project of note is co-led by CCIMI Director Carola Schönlieb and involves CCIMI students Derek Driggs and Jan Stanczuk. The AIX-COVNET project is a collaboration of mathematicians, clinicians, and researchers from around the world and aims to support COVID-19 patient triaging and prognosis by developing an artificial intelligence tool that can accurately diagnose patients from clinical and lab data, along with chest X-ray and CT images.

A strength of the collaboration is the close links forged across discipline boundaries, such as between the data scientists and clinicians. This discussion helps to inform the research objectives throughout the process by way of a consistent feedback loop. With such ambitious aims for the project, this will be key to future successes. There remains much to do but current results (published on the project website) are positive.

You can find out more about this specific project on its website and in this article previously published by Plus Magazine.