Dr Jen Barcroft presents her work in collaboration with i-sense colleagues at the International Society of Ultrasound in Obstetrics and Gynecology (ISUOG) World Congress: “Can Online Search Engine Patterns Predict Gynecological Diagnoses?”.
Many of our i-sense team members have received awards or fellowships over the past year - let’s take a closer look at a few of our award updates.
An observational study of patients at UCLH and North Middlesex University Hospital, published in The Lancet Infectious Diseases, suggests that the B.1.1.7 variant of COVID-19 – sometimes known as the UK or Kent variant – is not associated with more severe illness and death, but appears to lead to higher virus load.
Online search data can help inform the public health response to COVID-19, according to a report from UCL. The data allows experts to predict a peak in cases on average 17 days in advance.
i-sense members, Dr Vasileios Lampos and Prof Ingemar Cox at UCL Computer Science, have received USD$200,000 in funding to support their research into modelling the prevalence and understanding the broader impac
UCL has launched Virus Watch, inviting 50,000 households to take part in one of the largest and most comprehensive studies of COVID-19 in the UK.
The study, which will require participants to complete regular online symptom surveys, seeks to better understand community spread of the virus.
Pandemics, such as COVID-19, are usually assumed to spread rapidly within the population. In reality, the population is more heterogeneous with regard to risk, and there will be large variation on the basis of geography, workplace and other key factors.
Analysing data on a national level therefore risks hiding this heterogeneity and compromises the most effective public health response. New analysis from i-sense researchers at University College London suggests COVID-19 has such diverse effects on the different local authorities in the UK.
A recent feature on real-time tracking of influenza in Nature Outlook discusses how scientists are using social media and online search data to monitor potential outbreaks.