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USING HEALTH DATA TO UNDERSTAND HEART DISEASE AND COVID-19 RISK

6:00pm-7:00pm on Monday 4 April

Times shown are in GMT (UTC +0) up to the 26th March. For events on or after 27th March times are in BST (UTC +1).

Join scientists from the Cardiovascular Epidemiology Unit (Department of Public Health and Primary Care) to find out how they are trying to understand heart disease and COVID-19, using a variety of approaches.

Heart disease is the leading cause of death globally, taking over 15 million lives every year. In addition, over 5 million people have died during the COVID-19 pandemic. The number of people living with these diseases and experiencing a poor quality of life is, unfortunately, even higher and growing.

It is therefore very important 1) to predict which people are at a higher risk of developing these diseases, to enable a timely prevention or treatment, and 2) to understand which factors drive such higher risk, so that prevention or treatment can operate on the actual causes of disease and not on factors that are only apparently related. For example, grouping people based on whether they have grey hair would likely enable doctors to capture people at a higher risk for heart disease (because it affects people at an older age), but hair dyeing would probably not be very effective at reducing such risk!

Researchers at the Cardiovascular Epidemiology Unit use various approaches, such as artificial intelligence, genomics and data linkage, to address the two points above. During this event, researchers will explain how your data, and everyone else’s, can help them prevent deadly and widespread diseases.

The event will be followed by a short Q&A panel discussion, where the speakers will answer your questions about the talks and the ways health data is used to study disease risk.

Speakers include: Dr Samantha Ip, Dr Samuel Lambert and Dr Elias Allara.

This research is conducted by the Department of Public Health and Primary Care, University of Cambridge.

Children under the age of 16 must be accompanied by an adult.

Keywords: heart disease, COVID-19, artificial intelligence, machine learning, genetics, genomics, polygenic score, linkage, ethnicity, health data, disease risk, cardiovascular disease.

Research studies websites: https://www.pgscatalog.org/; https://isaric4c.net/
Cardiovascular Epidemiology Unit Twitter: @CAMBRIDGE_CEU

Booking/Registration is: REQUIRED

Children under the age of 16 must be accompanied by an adult.

Additional Information

Age: Adults, Young Adults 12 – 18
Format: Talk
Timing: Available on Demand, Live Stream
Cost: Free
Theme: Health
Accessibility: Closed Captions
Image copyright: https://search.creativecommons.org/photos/656aebe5-2bc1-4c47-beca-266bf4532100

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