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A nationwide study of 331 rare diseases among 58 million individuals: prevalence, demographics and COVID-19 outcomes

Johan H Thygesen, Huayu Zhang, Hanane Issa, Jinge Wu, Tuankasfee Hama, Ana Caterina Pinho Gomes, Tudor Groza, Sara Khalid, Tom Lumbers, Mevhibe Hocaoglu, Kamlesh Khunti, Rouven Priedon, Amitava Banerjee, Nikolas Pontikos, Chris Tomlinson, Ana Torralbo, Paul Taylor, Cathie Sudlow, Spiros Denaxas, Harry Hemingway, Honghan Wu, on behalf of the CVD-COVID-UK/COVID-IMPACT Consortium

Project description

We know individuals with underlying health conditions have greater risk of developing severe COVID-19 and ending up with poorer outcomes. That is why governments and public health services have been providing dedicated and prioritised protections for these more clinically vulnerable people – for example, via recommending shielding or being prioritised to have COVID-19 vaccinations.

However, the majority of those living with rare diseases – around 5.8% of the UK population, or 3.7 million people - are often overlooked. Rare diseases are often poorly recorded in clinical data leading to a challenge in identifying patients whose rare condition makes them clinically vulnerable. We don’t know the most effective way to personalise and manage treatments for patients with rare diseases who contracted COVID-19.

In this project, we aim to tackle these challenges by bringing together a comprehensive set of knowledge about rare diseases, and applying the most up to date data science technologies to use such knowledge and resources on CVD-COVID-UK datasets. In this way, we hope to develop a more accurate identification system for people living with rare diseases who are clinically vulnerable. We will also provide the much needed information on the risk of severe COVID-19 in people with rare diseases, hopefully leading to an improvement in their care by providing evidence on treatments that may work better for them.

How to cite this work

Preprint available here: https://doi.org/10.1101/2023.10.12.23296948

Contents

Project approval

This is a sub-project of project CCU019 approved by the CVD-COVID-UK / COVID-IMPACT Approvals & Oversight Board (sub-project: CCU019_01).

License

Licensed under the Apache License, Version 2.0 (the "License"); you may not use this software except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0. Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.