A NEW online tool has revealed the potential coronavirus hotspots across Winchester.

Experts from Oxford University have created an interactive map which highlights and shades the local areas expected to have the highest rate of hospitalisations from Covid-19.

The data is created by combining census estimates and hospital capacity data from ONS and NHS at the Administrative Region, Ceremonial Country (CC), Clinical Commissioning Group (CCG) and Lower Layer Super Output Area (LSOA) level from England and Wales.

The Leverhulme Centre for Demographic Science project has been calculated using data known to correlate to vulnerability to coronavirus. This includes factors such as age, social deprivation, population density, ethnicity and hospital capacity.

Users are able to adjust the 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.

Hampshire Chronicle:

Some areas of Winchester appear in the red including Easton, Northington, Alresford, Oliver’s Battery, Weeke, along with Stockbridge and Bishop's Waltham indicating a risk of more than 10 people per 1,000 needing care if there was a second spike.

But, Stanmore, Fulflood, Winnall and part of Bar End were shown to be in the lowest risk category, indicating a risk of less than seven people per 1,000 needing care.

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."

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 virtual map click here