CCU108: Simulation modelling of aortic disease detection and management: implications for post-COVID policy

Project lead:
Lois Kim, University of Cambridge

The COVID-19 pandemic increased the risk of cardiovascular disease in the population. This increase may have exaggerated existing inequalities in disease risk and access to services, for example, related to sex, ethnicity, social deprivation, and region. This may be particularly true for tears in the aorta – one of the major blood vessels of the body.

Diseases of the aorta – such as thoracic aortic aneurysm (TAA) and aortic dissection (AD) are typically “silent” until a catastrophic clinical event where the blood vessel tears, which carries a high risk to life. Development of these conditions and/or access to services may have shifted during the pandemic, and some groups may have been more impacted than others. We will develop statistical models to answer these questions and will explore whether changes to services offered could help improve clinical outcomes and/or reduce inequalities.

This work will benefit the public and patients through:

  • Identifying the extent to which the COVID-19 pandemic has impacted aortic disease risk and management.
  • Identifying the extent to which the COVID-19 pandemic has impacted inequalities in aortic disease risk and management.
  • Guiding national healthcare policies by exploring policies that reduce aortic disease and/or inequalities in aortic disease.

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