Combining multiple or high-dimensional biomarkers to improve accuracy for detecting COVID-19 virus infection and antibody
In recent decades, powerful biomarkers have become an important tool in diagnosis to identify subjects with a disease, or at high risk of developing the disease. However, single biomarker is not accurate enough and may incur considerable false positives and false negatives which will have serious implications on patients and public health. Thus, researchers have considered the problem of combining biomarkers to improve diagnosis of a disease. To date, the coronavirus SARS-CoV-2 that causes the severe acute respiratory syndrome COVID-19 was reported to have infected over 380 million people, leading to over 5 million deaths worldwide. Better and faster COVID-19 test for virus infection or antibody is urgently needed to help guide the improvement of detection and treatment. Therefore, our aim of this project is to find more effective and quicker ways for better diagnosis and prediction of COVID-19 virus infection and antibody, using the existing data available in the UK Biobank database on biomarkers and test results for COVID-19 virus infection and antibody. The diagnostic methods developed from this research project will substantially improve the accuracy for detection of COVID-19 virus and antibody, while maintaining the advantage of reducing cost and time for screening.