A NEW tool created by Oxford University researchers reveals how Gwent could be affected by a second wave of the coronavirus.

Experts from the Russell Group university have created an interactive map which shows hotspots that could be adversely affected by a second wave of Covid-19 cases.

At-risk regions have been identified based on the number of ‘vulnerable’ people and available hospital resources.

And it also considers data on population age, density, social deprivation and density.

The map shows that Gwent is mid-risk area, with just over eight hospitalisations per 1,000 people in ‘general care’ and just under three people in acute care.

In Gwent, the critical care capacity is 23 beds and the map predicts that just under three of these could be taken up by coronavirus patients.

South Wales Argus:

(The map reveals how Gwent would be affected. Picture: leverhulme centre for demographic science)

Gwent has a higher hospitalisation rate than neighbouring South Glamorgan – which includes Cardiff – where there could seven general care hospitalisations per 1,000 people, with just over two in acute care.

The worst hit region in Wales could be Powys, researchers say.

There could be ten people in general care and just over three in acute care.

South Wales Argus:

(How the rest of Wales would be hit compared to Gwent. Picture: leverhulme centre for demographic science)


The Leverhulme Centre for Demographic Science dashboard is designed to add to the UK 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.

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

According to the report, published in BMC Medicine: "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."