A MAP has identified the areas in our region that could become a "Covid-19 hotspot" next month - as one area stands out.

The interactive map, which has been created by Imperial College London, has predicted which areas could see a surge in cases, based on existing data.

The map looks at data on daily reported cases, weekly reported deaths and mathematical modelling to forecast the probability of weekly Covid rates.

Covid rates are an expression of the number of new cases in an area in relation to its population.

They are calculated by dividing the number of new weekly cases by the area's population, then multiplying this by 100,000.

The map looks at the chance of each area seeing cases rise by more than 100 in seven days - known as a "Covid-19 hotspot 100."

The Northern Echo:

The map predicts Stockton is at most risk Picture: IMPERIAL COLLEGE LONDON

In the North-East, five areas have been identified as with the highest probability of Covid cases increasing by more than 100.

The map shows Stockton has a 30 per cent chance of becoming a hotspot in the week ending April 10 - the highest prediction in our region.

This is followed by Hartlepool, which has a 23 per cent probability of becoming a Covid hotspot over the same timeframe.

Meanwhile Darlington, County Durham and Sunderland are also listed with a probability of 15, 13 and five per cent respectively.

All other areas across the region appear to have a probability of between zero and one per cent, meaning cases are not forecast to surge.

Imperial College states that its projections for hotspots assume no change in interventions and human behaviour has been made since a week before the last observed data. The data was last updated on Saturday, March 27 at 8.42pm.

Imperial College also lists a number of limitations to its predictions.

It explains: "Predictions on this page assume no change in current interventions (lockdowns, school closures, and others) in the local area beyond those already taken about a week before the end of observations.

"An increase in cases in an area can be due to an increase in testing. The model currently does not account for this.

"Each area (local authority) is treated independently apart from the overall Rt estimate for its region. Thus the epidemic in a region is neither affected by nor affects any other region. It also does not include importations from other countries.

"The population within an area is considered to be homogeneous - i.e. all individuals are considered equally likely to be affected by the disease progression."