Potential coronavirus hotspots can now be identified using a new online tool developed by Oxford University, and shows the risk of a second wave or Covid-19 spike in each of south London's boroughs.

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.

On of the key features of the tool is a dashboard showing a map of each region's risk of hospitalisation per 1,000 people based on age and hospital capacity when the rate of infection is low and close to zero.

Across south London, Bromley ranked the highest for 'risk of hospitalisation (joint with Dartford), with 2.3 per 1,000.

Bexley and Richmond were shortly behind, with 2.2 per 1,000, Sutton with 2.1, Croydon 2.0, and Merton 1.9.

These are all above the London average of 1.8, but come it at around the UK average also, so are not high-risk.

Greenwich and Lewisham with 1.7, and Wandsworth with 1.6 (the lowest) were judged to be lower risk, with some of the UK's lowest figures.

When the provisional infection rate is raised to 1, the risk of hospitalisation jumps up, but across south London it still remains relatively low for the UK.

Across south London, Bromley and Bexley in the south east had the highest rate per 1,000, with 76.6 and 73.6 respectively.

Both are higher than the London average of 61.6, but are not particularly high for the UK, and are relatively low-risk.

The risk per 1,000 was still lowest lowest in Wandsworth, with 54.7.

In Lewisham its 56.6, Greenwich 57.6, Wimbledon 64.3, Croydon 67.2 and in Sutton 71.3.

Another feature of the tool is to predict the excess demand for general care beds if the infection rate spiked past 1, aka how many people would be at risk of hospitalisation beyond hospital capacity.

Bromley again has the most 'expected excess demand' with 76.6 care beds, whilst Bexley is also high and above the London average with 73.6.

Dartford in Kent and also Richmond are also ranked highly in this category, with 75.1 and 73 respectively.

However, compared to the rest of the UK, this risk remains relatively low. For example, North Norfolk would be predicted to have an excess demand for beds of 106.3.

The figures show that these two boroughs are the most at risk in south London to viruses and a second wave of Covid-19.

In terms of excess demand, Croydon's figure is 66.6, Sutton 69.5, Wimbledon 64.3, Greenwich 57.6, Lewisham 55, and Wandsworth 53.3.

The current rate of Covid-19, released at the end of the week, largely reflects this, with Bexley currently having 4.4 cases per 100,000 population, compared to Lewisham's 0.7.

Greenwich has seen an uptake in infection, recording 2.4 per 100,000, whilst Bromley actually only recorded 1.5.

In total, there have been 33,836 confirmed cases of Covid-19 in London, with 245,483 across the whole of England.

Bromley has recorded 1,517 total cases, Lewisham 1,192, Bexley 1,053 and Greenwich 952.

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.

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.