Our experts are developing models to help regional health services predict and understand outcomes for COVID-19 patients.
Led by Wolfson Fellows Dr Camila Caiado from our Mathematical Sciences department and Professor Brian Castellani from Sociology, the work involves using data and statistics to predict outcomes, known as predictive modelling.
The models can be used by hospitals to support planning for critical care capacity and to investigate effectiveness of treatment for different groups of patients.
Our research is particularly relevant to the COVID-19 pandemic, which has seen cases and transmission rates vary across regions in England.
While places such as London experienced a high number of cases early on in the crisis, areas such as the North East of England have ‘peaked’ much later.
Local-level insights are crucial because they can help to develop more realistic short and medium-term predictions that inform strategies to exit lockdown.
While national models have been helpful in predicting worst-case scenarios throughout the pandemic, a regional approach takes into account different health needs and how these vary across the country.
It is now planned that the models will be used to support decision making around the re-opening of suspended non-critical services, such as elective (non-urgent) surgery, as well as curbing the future spread of the virus.
The work is a part of a long-standing partnership with the Academic Health Science Network (AHSN) North East and North Cumbria, an organisation which works with regional health organisations.
In the future, we hope to work with all trusts in the region on the longer-term planning of health and social care.
Durham is home to the highly-regarded Wolfson Research Institute for Health and Wellbeing. Our research excellence makes us well-placed to tackle today’s health challenges, ensuring our health research expertise makes a real difference.
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