POTENTIAL coronavirus hotspots in north Essex have been revealed thanks to a new online tool created by Oxford University.

The Leverhulme Centre for Demographic Science dashboard is designed to add to the government's test and trace programme by highlighting which regions and local areas are most likely to suffer disproportionate infections and hospital demand if an outbreak occurs.

It combines data about groups known to be especially vulnerable to Covid-19, using factors such as age, social deprivation, population density, ethnicity and hospital capacity.

Given the constantly evolving situation, it also allows users to adjust for changing infection rates and hospital resource levels.

The dashboard features a map down to a ward level showing the risk of hospitalisation per 1,000 people based on age and hospital capacity.

Essex as whole, with a rate of 8.1 per 1,000, is average for the UK and broadly in line with neighbouring counties, although lower than Suffolk.


  • A map showing the coronavirus rate across Essex

The majority of Colchester is orange, although some areas towards the town centre classed as red, with a rate above 9 per 1,000 people.

For instance parts of Lexden currently have a risk of 10 in 1,000.


  • Some areas in Colchester are more at risk than others

Much of Tendring, including parts of Clacton, Walton and Manningtree, are also red, with rates above 9 per 1,000 people.

Read more >>> Colchester's hospital trust incurs extra £3.4m cost in single month

Professor Melinda Mills, director of the Leverhulme Centre for Demographic Science, said: “With additional outbreaks and second waves, thinking not only regionally, but at much smaller scale at the neighbourhood level will be the most effective approach to stifle and contain outbreaks, particularly when a lack of track and trace is in place.”

She pointed to the tool showing Harrow in London would have been a local area with an exceptionally high age-related risk of hospitalisations due to Covid-19. The Northwick Park Hospital in Harrow was, in fact, also the first to call for a national emergency due to a lack of capacity early on in the pandemic.

Read more >>> Coronavirus cases in Essex increase by 2,000 as data is updated

Mark Verhagen, lead author of the study, said: “By using our online tool, policymakers would immediately have identified Harrow as a potential hotspot of hospital demand.

"Ensuring that local decision-makers have this type of fine-grained information available was a key goal of this study.”

The research has also shown areas such as the Isle of Wight and Lincolnshire to have some of the highest risk factors.

These areas not only have older populations, but also higher levels of social deprivation.

According to the study: "We estimate specific pressure points where Covid-19 demand is likely to outstrip the baseline local supply.

"This includes rural areas in Wales as well as the North East and South West of England where high expected hospitalisation rates combine with relatively low bed capacity. Importantly, these areas are often more isolated and further away from alternative hospital services."

Read more >>> Data shows rate of new coronavirus cases in Southend and Essex

Meanwhile, London and other inner city areas, from Birmingham to Manchester and Liverpool, are highlighted as areas of high population density and deprivation, which have potentially higher risk levels for additional outbreaks.

Although population-based hospitalisation risk tends to be lower in urban centres, some areas in cities may have higher levels of social deprivation and population density, which could counterbalance relatively low age-related risk levels such as in Oxford's Rose Hill & Iffley ward.

The study concluded: "As countries across the globe exit strict lockdown and enter the ‘new normal’ of co-existence with Covid-19, monitoring new infection hotspots will be crucial. Our geospatial estimates illustrate the importance of considering demographic and socioeconomic factors in anticipating local spikes in health care demand related to the Covid-19 pandemic."

To view the data click here.