Havering areas which could be potentially most at risk for hospitalisation due to coronavirus can now be identified using a new online tool from Oxford University.

The Leverhulme Centre for Demographic Science dashboard does not predict or measure the actual number of infections, only locations that could be more likely to fare worse in the event of a future outbreak. (An outbreak is understood as 10 per cent of the population being infected).

The dashboard was designed to give policymakers concrete insight into which local regions have highest risk of serious complications in case of a second wave, so that those regions can be monitored more closely,with preventative testing and strategically manage their resources.

Lead author of the study, Mark Verhagen explains: “We have felt that many local policymakers are starved of information to address the pandemic, especially in a preventative manner, since most information sources tend to be national or regional and tend to be retrospective.”

The dashboard 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.

Romford Recorder: The figures for Essex show it as having more at risk factors than Barking and Dagenham, but fewer than Havering - more in line with the national average. Picture: Oxford UniversityThe figures for Essex show it as having more at risk factors than Barking and Dagenham, but fewer than Havering - more in line with the national average. Picture: Oxford University (Image: Oxford University)

Nationally, an average shows around seven people per 1,000 would need care if there was an infection spike.

The large majority of Havering, bar Romford and Harold Hill areas, is more at risk than the national average and more than neighbours Essex and Barking and Dagenham.

Romford Recorder: London's peripheral boroughs are more at risk due to having older populations and higher levels of social deprivation than the central boroughs. Picture: Oxford UniversityLondon's peripheral boroughs are more at risk due to having older populations and higher levels of social deprivation than the central boroughs. Picture: Oxford University (Image: Oxford University)

In fact, one small ward measured between Little Gaynes Lane and Harwood Hall Lane in Corbets Tey, which has three care homes inbetween these boundaries, was identified as having 11.3 people in 1,000 that may need hospitalisation in the event of another outbreak, one of the highest ratings in the country.

Figures for neighbouring boroughs Barking and Dagenham and Redbridge indicate they are less at risk, most wards measuring below the national average.

Essex, likewise, measures below Havering but with more at-risk factors than Barking and Dagenham.

In London generally,the peripheral boroughs have been identified as most at risk due to having older populations and higher levels of social deprivation.

Harrow for example, was an area with an exceptionally high age-related risk of hospitalisations due to Covid-19. The Northwick Park Hospital in Harrow was the first in the UK to call for a national emergency due to a lack of capacity early in the pandemic.

Nationally, London and other cities like Birmingham, Manchester and Liverpool, are highlighted as areas of high population density and deprivation, which have potentially higher risk levels for additional outbreaks (but not necessarily hospitalisation).

Dr Verhagen said: “London was hardest hit initially because of the sheer number of infections there, and since London has a relatively young population, the health care demand will in fact have been relatively low.

“To illustrate, if just as large a proportion of the population in the South West would have been infected as in London, the relative number of hospitalisations would have been much higher.”

Although population-based hospitalisation risk tends to be lower in urban centres, some localities in cities may have higher levels of social deprivation and population density, which could counterbalance relatively low age-related risk levels.

Infection rates are assumed as constant across age groups. Hospital capacity is calculated relative to the number of hospital beds available under normal circumstances (measured as of December 2019).