UK-based in-depth study of early COVID-19 detection

The study will measure antibodies to determine how many people have previously been infected with COVID-19 in the first wave of the pandemic and will observe the development of antibodies over the next months. It will use information collected by participants and new digital biomarkers to develop new predictive models for early identification of COVID-19 infection. The study will also allow researchers to investigate the effects of public health and policy responses such as social distancing on health-related behaviours, well-being and mental health. 

The research team will use remote patient monitoring (RPM) technology from Huma to collect real-world data from participants, which can be combined with the existing Fenland dataset alongside to unlock new insights. Participants will use a novel Drawbridge One Draw device to take blood samples at home which can be sent into the laboratory for analysis of COVID 19 antibodies without the need for a direct interface with the health care system. 

The Fenland Study, led by Chief Investigator Professor Nick Wareham, is a population-based study set in Cambridgeshire. Participants were recruited at random from a population-based sampling frame to investigate the interaction between genetic and behavioural factors on diabetes, obesity, and related metabolic disorders. What makes the Fenland Study unique is the level of detail it collects about the health and lifestyle of participants, and the objective measurement techniques that have been used to quantify behaviours like physical activity. The Study has tracked 12,500 patients for up to 15 years, combining detailed genetic profiles with objective clinical measurements including blood-based biomarkers, resting metabolic rate, cardio-respiratory fitness, physical activity, energy expenditure and body composition, as well as information from questionnaires on diet, physical activity and other behaviours.

Professor Nick Wareham commented: “The representative recruitment strategy of the Fenland study makes it an ideal setting in which to investigate how the first wave of COVID-19 has affected the population. Our close contact with the participants and our strategic ambition to obtain data from participants in real time has been married with the aim of developing digital biomarkers of COVID-19 in this exciting new study. We are launching this study now as early detection of possible COVID-19 infection and efficient diagnostic testing and tracing are the cornerstone of efforts to minimise the impacts of any subsequent waves of infection.”

Through Huma’s smartphone app, researchers will ask participants to provide detailed health data to provide critical insights into the detection and progression of COVID-19. The new study will measure participants’ COVID-19 signs and symptoms, such as heart rate, heart rate variability, respiratory rate, blood oxygen, and temperature; activity measures collected through smartphones sensors and connected devices; risk factors and health information such as body weight and diet changes; medication and supplement use; and information on mental health and wellbeing.

The use of Huma’s digital platform allows the research team to efficiently and safely collect information without in-person contact between participants and researchers. The study has begun recruitment and the participant app will go live in late July. It is planned to go on for at least six months, but may be extended depending on the extent of COVID-19 spread and containment this winter.

Dan Vahdat, Founder and CEO of Huma, said: “The COVID-19 pandemic has made clear to the world that the traditional way of looking after patients is limited. For the first time in history, we have platforms, devices, and data collection and analysis capabilities that can change how healthcare is delivered, putting a mini hospital in your pocket. We are excited to work with the University of Cambridge to discover new digital biomarkers and health insights based on the Fenland study of 12,500 individuals and their health data for up to fifteen years. With this in-depth health data, we look forward to uncovering new insights and digital biomarkers that can aid in understanding the early indicators and disease progression of COVID-19 and far beyond.”