BAME COMMUNITY AND CORONAVIRUS: OXFORD UNIVERSITY SPIN-OUT ZEGAMI OFFERS MEDICAL PROFESSION ITS DATA VISUALISATION SERVICES FOR FREE TO HELP FIND REASONS WHY BAME PEOPLE ARE AT GREATER RISK FROM CORONAVIRUS
- Zegami calls on Government to review what Coronavirus related data it is collecting by ethnicity
- Analysing the millions of data points collected on the rate of infection of COVID-19 by different ethnic groups and the medical outcome of these in a quick, efficient, and technologically advanced way holds the key to why BAME people are more at risk from Coronavirus
Zegami, the Oxford University data visualisation spin-out, is offering its services for free to help discover why members of the BAME community are at greater risk of contracting COVID-19 than people from white ethnic backgrounds, suffering more serious health implications from it and an increased chance of dying from the virus. It says analysing the millions of data points collected on the rate of infection of COVID-19 by different ethnic groups and the medical outcome of these in a quick, efficient, and technologically advanced way holds the key to this question.
It is also calling on the Government to review urgently what data it is collecting on the Coronavirus crisis by ethnic groups to ensure it is capturing all relevant information.
Roger Noble, CEO and founder of Zegami said: “All the evidence shows that members of the BAME community are at greater risk of contracting COVID-19 than the white community, and they also face a higher risk of suffering serious health implications or even death. As a matter of urgency, we need to review how Coronavirus data by ethnicity is being collected, and more specifically what information is being gathered. If we are confident that we are collecting everything needed, technology and data visualisation can speed up the process of finding an answer to the question of why the BAME community is so more adversely affected by this virus.”
A review by Public Health England found that the highest age standardised diagnosis rates of COVID-19 per 100,000 population were in people of Black ethnic groups and the lowest were in people of White ethnic groups. An analysis of survival among confirmed COVID-19 cases showed that, after accounting for the effect of sex, age, deprivation and region, people of Bangladeshi ethnicity had around twice the risk of death when compared to people of White British ethnicity. People of Chinese, Indian, Pakistani, Other Asian, Caribbean and Other Black ethnicity had between 10 and 50% higher risk of death when compared to White British people.
Several explanations have been put forward for why the BAME community has been hit harder by Coronavirus than white ethnic groups. These include:
· Variations in cardiovascular disease risk by ethnic groups
· Vitamin D levels. It has been suggested that BAME people may face higher risk of dying from coronavirus because of their higher rates of vitamin D deficiencies
· Socio-economic, and behavioural factors. Some BAME groups are more likely to live in overcrowded accommodation than white communities
· BAME communities have a higher proportion of people employed in key worker roles increasing their exposure to the virus
· It has been reported that members of the BAME community can sometimes have poorer access to healthcare services, which can make them less inclined to seek medical help
Zegami is a data visualisation platform that allows you to easily explore large image datasets and unlock powerful insight by combining advanced analysis tools with a unique visualisation interface. The Zegami platform enables users to rapidly analyse, categorise, label and clean large image datasets, invaluable for many applications including training machine learning. It also creates insightful visualisations from the widest range of structured and unstructured data in business and scientific research.
Zegami and the medical sector
Zegami believes that over the next few years, the medical professional will be one of the biggest adopters of data visualisation tools, and it’s already working on several projects in this sector. They include:
· A project collaborating with Professor Jim Hughes at the MRC Weatherall Institute for Molecular Medicines (MRC WIMM) Centre for Computational Biology to help clean its data and assist with the training of its machine learning models, specifically around developing a better understanding of which proteins in genes bind, and where they do this in the genome.
· After winning Cancer Research UK’s Early Cancer Detection Sandpit Challenge in 2019, Zegami is currently working with Professor Barbara Braden (Oxford University), Dr Xiohang Gao (Middlesex University) and Dr Wei Pan (Herriot Watt University) to develop a real-time detection system for oesophageal cancers. These cancers are mainly detected by endoscopy, and are only usually noticed when they have reached an advanced stage and treatment is less effective and patient prognosis is poor.
· Working with Professor Paul Lesson at Cardiovascular Clinical Research Facility (CCRF) at Oxford University to help improve its diagnosis of cardiovascular diseases such as coronary heart and aortic diseases. The aim is to identify trends for early detection of disease by applying advanced data visualisation and analysis techniques to echocardiogram data.