Is my area at risk of Tier 3 lockdown? Coronavirus map shows 8 places that could move alert level

THIS new map reveals the next eight places that could be soon be put into Tier 3 coronavirus lockdown.

Manchester tops the list compiled using the latest data from the Covid Symptom Tracker App, followed by Newcastle.

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Greater Manchester is already under pressure to agree to the new restrictions set out by Prime Minister Boris Johnson earlier this week.

But Mayor Andy Burnham has refused to move to Tier 3 and has instead called for a national "circuit breaker" lockdown.

The next place predicted to move into the highest lockdown level is Newcastle, which has had a surge in Covid cases in recent weeks.

It's followed by other hotspot areas in the North of England, including Nottingham and Bury.

Hartlepool, Salford, Sheffield and Leeds also make the top eight places which could be plunged into the toughest restrictions, according to experts.

Burnley and Pendle were previously on the list for regions most likely to be put into Tier 3 – now put into the highest level of restrictions overnight.

TIER PREDICTOR MODEL

Researchers at King's College London, who run the app, say they are now using their estimates to predict which region could be next to be put under Tier 3 restrictions.

Using predicted symptomatic cases means that predictions can be made up to ten days before confirmed tested cases are made public, they say.

Their new "Tier Prediction model" takes the Tier 2 regions as defined by the Government (100,000 cases per million), uses the average estimated cases over the last seven days and ranks the regions in descending order.

The area with the largest weekly average prevalence is ranked the highest.



Prof Tim Spector, a genetic epidemiologist, said: "Our new Tier Prediction model highlights that nine out of 10 are in the North of England, where most of the cases currently are concentrated.

"Unlike the North which is accelerating, London has been showing a steady linear increase, doubling every 21 (range 14-28) days so it will be interesting to see how the new Tier 2 restrictions influence the rate of new cases in the next two weeks.”

He added: "The data is no longer showing the exponential increases that we were seeing a couple of weeks ago.

The North West still has the most cases and the fastest acceleration of cases with doubling times of around 10 days

"But it is clearly showing new cases continuing to rise.

"The North West still has the most cases and the fastest acceleration of cases with doubling times of around 10 days.

"Slowing this rapid rise is a priority.

 

"Scotland, Wales, London and the Midlands are slowly increasing with a doubling time of 14-28 days and the South and East of England remaining relatively flat with five-fold fewer cases than the worst hit regions.

"Our data is roughly 7-10 days ahead of other sources meaning that it acts like an early warning system, whilst we wait for the data from the confirmed cases."

CASES RISING

According to the app data, there are currently an average of 27,762 daily new symptomatic cases of Covid in the UK over the two weeks up to 11 October.

This compares to 21,903 daily new symptomatic cases a week ago.

This figure is based on the number of newly symptomatic app users per day, and the proportion of these who give positive swab tests.

 

The latest survey figures were based on the data from 13,361 recent swab tests done between 27 September to 11 October and doesn't include figures from care homes.

The app’s data continues to show a big disparity between the North and South of England.

This week the North West has 7,313 new cases per day and has overtaken the North East and Yorkshire with 5,762 daily infections.

The South West remains the lowest region, followed by East of England and South East.

The Covid Symptom Study UK Infection Survey has been running since early May and has so far recorded over a million swab results from app users – the largest of its kind.

It estimates the number of current Covid-19 positive cases in the community based on the information logged by users in the app and the results from the swab testing programme.

 

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