A MAP created by Imperial College London has predicted whether Slough will become a "Covid-19 hotspot" this month.

Data on daily reported cases, weekly reported deaths and mathematical modelling is used to forecast the probability of weekly coronavirus rates in local authority areas across the UK surpassing 50 in the week leading up to March 20.

Coronavirus rates are an expression of the number of new cases in an area in relation to its population, and are calculated by dividing the number of new weekly cases by the area's population, then multiplying this by 100,000.

Slough Observer:

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The map also predicts the chance of the R number - the average number of people that one infected person will pass on a virus to - in each local authority rising above one.

Figures in Slough

The map shows Slough has a 42 per cent chance of being a "Covid-19 hotspot 50" in the week ending March 20. 

A "Covid-19 hotspot 50 " is an area which has a rate of more than 50 new weekly cases per 100,000 population.

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Slough still has one of the highest rates for Covid-19 in Berkshire with a rolling rate of 143.8.

The map also notes there is 2 per cent probability in new infections increasing this month.

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 Tuesday, March 2.

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."