The Risk Prediction on Winter Respiratory Diseases and the Burden on Healthcare Systems: Pre and Since COVID-19 Pandemic
Study code
DAA218
Lead researcher
Ting Shi
Study type
Data only
Institution or company
University of Edinburgh
Researcher type
Academic
Speciality area
COVID
Summary
Winter respiratory diseases, such as COVID-19, flu, and respiratory infections, cause a significant number of hospital visits and deaths each year, placing immense pressure on the NHS (National Health Service), especially during the COVID-19 pandemic. This project aims to improve how we predict and prevent these diseases by using advanced computer models to identify who is most at risk and efficient early actions to protect them.
The project will investigate patterns of respiratory illnesses before and since the COVID-19 pandemic to understand how risk factors,
such as age, existing health conditions, vaccination history, and environmental factors, affect hospitalisation rates. We will develop a prediction system by artificial intelligence to monitor patients who most likely require hospital care, emergency treatment, or facing serious health outcomes. With the assistant of this project identifying those most at risk, healthcare providers can offer earlier interventions, such as vaccinations,
medication, and lifestyle advice, to help prevent severe illness. This research will also assist policymakers in making informed decisions about how to allocate healthcare resources efficiently, particularly in winter when hospitals are under the most strain. In summary, this project will help improve public health, reduce hospital admissions, and support a stronger, more resilient NHS.