A newly developed online Covid-19 calculator suggests that the Isle of Wight has no chance of becoming a coronavirus hotspot.

The new website devised by Imperial College London, predicts which parts of England and Wales have the greatest probability of seeing cases rise above 50 per 100,000, which it classes as a 'hotspot.'

The calculator devised predictions for the likelihood of the Isle of Wight’s R rate rising above 1 and of more than 50 new cases being recorded in a week.

The possibility of the R rate increasing to dangerous levels was zero per cent on September 5.  

The chance of more than 50 cases within either of the first three weeks of September stays consistent at zero per cent up until September 19.

The probability of R being greater 1 on September 5 was at a moderate 70 per cent.

Lead researcher Professor Axel Gandy, from the Department of Mathematics at Imperial, said: "Covid-19 is, unfortunately, very much still with us, but we hope this will be a useful tool for local and national governments trying to bring hotspots under control.

"The model allows us to project where local hotspots of COVID-19 are likely to develop in England and Wales based on the trends that we’re seeing in those areas."

The website was produced by the Department of Mathemtics, in collaboration with the WHO Collaborating Centre for Infectious Disease Modelling within the MRC Centre for Global Infectious Disease Analysis (GIDA), and Abdul Latif Jameel Institute for Disease and Emergency Analytics (J-IDEA) at Imperial.

It uses data on daily reported cases and weekly reported deaths and mathematics modelling to reported a probability that a local authority will become a hotspot in the following week.

The site also provides estimates for each local authority in England and Wales on whether cases are likely to be increasing or decreasing in the following week and the probability of R(t) being greater than 1 in the following week.

Each local authority is also treated independently and the predictions assume no change in current interventions (lockdowns, school closures, and others) in a local authority beyond those already taken about a week before the end of observations.

The team also note that an increase in cases in a local authority can be due to an increase in testing, which the model does not currently account for.

The model also assumes all individuals within each local authority are equally likely to be infected, so demographic factors such as the age structure of the population are not considered.

Dr Swapnil Mishra, from the MRC Centre for Global Infectious Disease Analysis, said: “We provide weekly predictions of the evolution of COVID-19 at the local authority level in England and Wales. Our model helps to identify hotspots – probable local areas of concern.

"We hope that our estimates will enable swift action at the local level to control the spread of the epidemic.”