Map reveals how Covid-19 infection rates soared in the North of England after PHE’s Excel bungle


Public Health England’s Excel bungle has drastically changed the outlook of England’s coronavirus outbreak, with infection rates in the North soaring overnight.

Following the revelation that almost 16,000 ‘missed’ cases had been added to the system, infection rates spiralled in every authority of the country except four at the weekend — all of which were in the South.

The cases — which were lost in the government system because an Excel spreadsheet reached its maximum size and failed to update — have mostly been added to the North West of the country, with other areas in the North East and Midlands also hit badly. 

The technical glitch meant 15,841 cases between September 25 and October 2 were left out of the reported daily coronavirus cases and were not referred to NHS Test and Trace, meaning potentially tens of thousands of infected Britons were allowed to roam the streets. 

And in a slow recovery from Friday’s Excel blunder almost 6,000 covid carriers are yet to be traced, some of which were given their positive covid-19 diagnosis two weeks ago.

Each of those 6,000 carriers are expected to have made contact with three to four unwitting people who have not been informed that they should be isolating due to potential infection. 

Yesterday’s rolling seven-day infection rate — how many new cases were diagnosed in the seven days to October for every 100,000 people — surged in huge cities including Manchester, Leeds, Sheffield, Nottingham, Newcastle upon Tyne and Liverpool, as a result of the backlogged data being properly recorded. 

Manchester, now the Covid-19 hotspot in England, saw its infection rate rise by 80 per cent from 289.4 before the unreported cases were uncovered, to 529.4 afterwards when some 3,000 were added to the city’s tally. Nottingham’s tripled, from 100.6 to 382.4, Leeds’s doubled from 149.3 to 316.8, and Sheffield’s increased by 2.5-fold from 110.1 to 286.6.

The analysis — based on government data crunched by the Press Association — Babergh in Suffolk suffered the largest spike in infection rate (791 per cent, from 2.2 to 19.6), followed by Exeter (326 per cent from 61.6 to 262.5), and Fenland in Cambridgeshire (323 per cent from 7.9 to 33.4). 

Following the revelation that almost 16,000 ‘missed’ cases had been added to the system, infection rates spiralled in every authority of the country except four at the weekend — all of which were in the South. The cases have mostly been added to the North West of the country, with other areas in the North East and Midlands also hit badly

Manchester, now the Covid-19 hotspot in England, saw its infection rate - expressed as cases per 100,000 people - increase by 80 per cent from 289.4 on October 2 to 529.4 on October 5. Leeds infection rate increased by 112 per cent from 149.3 to 316.8 in the same period

Manchester, now the Covid-19 hotspot in England, saw its infection rate – expressed as cases per 100,000 people – increase by 80 per cent from 289.4 on October 2 to 529.4 on October 5. Leeds infection rate increased by 112 per cent from 149.3 to 316.8 in the same period 

Sheffield's rate shot up 160 per cent from 100.9 to 286.6. In Nottingham, East Midlands, the case rate jump up 3-fold, from 100.6 to 382.4

Sheffield’s rate shot up 160 per cent from 100.9 to 286.6. In Nottingham, East Midlands, the case rate jump up 3-fold, from 100.6 to 382.4

PA news agency gives the rolling seven-day rate of new cases of Covid-19 for every local authority area in England every day.

The rate is expressed as the number of infections per 100,000 people. So in Manchester, 530 people per 100,000 caught Covid-19 during the last week — the equivalent of one in every 189 people. 

PA revealed yesterday the current Covid-19 rates based on data in the seven days to October 2, after the error in case reporting was fixed by PHE on Sunday evening. 

It showed that, compared to data from previous days, the infection rate has gone up in 311 authorities in England, with only four staying stable of slightly dipping; Isle of Wight, Crawley, Cornwall and Isles of Scilly and Maldon.

On average, the infection rate has increased by 90 per cent in each authority from PA’s previous count on October 2. The percentage changes ranged from as low as five per cent in Harlow, London, to 791 per cent in Babergh.

Heat maps show how the North West has suffered considerably as a result of the case-counting blunder, which Matt Hancock faced a grilling over today in the House of Commons. 

Mr Hancock claimed his department were ‘continuing’ to search for contacts but that it was unclear ‘in advance’ exactly how many there were. It followed Labour’s deputy leader Angela Rayner calling for him to stand down from his position for his ‘disgraceful’ handling of the crisis on Good Morning Britain.

EXCEL BLUNDER LOSES 16,000 CASES: HOW DID IT HAPPEN? 

Matt Hancock told MPs yesterday that a technical problem over the weekend occurred with the system ‘that brings together’ data from NHS test sites and tests processed by commercial firms.

Public Health England (PHE) told the PA news agency that the issue had been caused by an Excel file maxing out during an automated process.

The spreadsheet, used in outdated software used by PHE, had too much data from the labs and therefore threw off thousands of cases when they were supposed to be passed onto officials in the NHS to start contact tracing. They were also not uploaded to the Government’s public coronavirus dashboard. 

PHE said files had now been broken down into smaller, multiple files to avoid the issue happening again. 

Mr Hancock said it had been decided in July that the PHE ‘legacy system’ needed an upgrade, with contracts for a new system awarded in August.

Officials from PHE and Test and Trace said that people who were tested received their Covid-19 test results in a ‘normal way’. 

As soon as the missing cases were reported, officials said that the information was ‘immediately’ handed to NHS Test and Trace so contact tracing could begin and people in contact with those who had the virus were instructed to self isolate.

But the blunder will have led to an inevitable delay in some contacts being reached.  

Labour said yesterday that some 48,000 people who have been in contact with a Covid-19 case may be ‘blissfully unaware’ they are spreading the disease when they should have been told to self isolate. 

Millions of people are already under tighter Covid-19 restrictions in the North West, including a ban on mixing with other households in either their own home or public settings such as the pub.

But the addition of thousands of cases has sparked fears that more areas could be pushed into tougher lockdowns.  

Manchester now has the highest rate in England, at 529.4 cases per 100,000. This is up from 246.4 per 100,000 on October 2, based on data in the seven days to September 25 — before the computer glitch. 

A total 2,927 new cases were recorded in the seven days up until October 2.

The surrounding Greater Manchester boroughs of Salford, Bury and Rochdale saw their seven-day rolling rate jump up to 278.2 (up 77 per cent), 253.4 (up 53 per cent) and 287.3 (up 74 per cent), respectively. 

Knowsley, a metropolitan borough of Merseyside, and Liverpool have the second and third highest rates in England, at 498.5 (up 76 per cent) and 487.1 (up 69 per cent), respectively, according to the PA analysis. 

Other areas of Merseyside that recorded big jumps in their seven-day rates include Wirral, up 39 per cent to 209.6, Sefton, up 61 per cent to 307.9, and St Helens, up 44 per cent to 311.8.

Lancashire was also affected by the cases. Rossendale’s infection rate went up by 55 per cent to 223.8, Blackburn with Darwen’s up by 46 per cent to 207.1, Pendle’s up by 43 per cent to 294.2, Hyndburn’s up 42 per cent to 269, and Burnley’s up 21 per cent to 411.6. 

Further into the Yorkshire and the Humber, university cities Leeds and Sheffield have also seen considerable hikes in their infection rate.  

Sheffield’s rate shot up 160 per cent from 100.9 to 286.6 and Leeds 112 per cent from 149.3 to 316.8. Bradford, in West Yorkshire, also saw a 65 per cent increase, from 153 to 253.1.

The University of Sheffield’s Covid-19 statistics web page showed nearly 500 students and staff had tested positive since the start of the autumn term last week. 

And in Nottingham, where 425 students have been diagnosed with Covid-19 in just one week, the case rate jump up 3-fold, from 100.6 to 382.4. 

Residents in Nottingham, which has two universities, have reportedly been told to brace for tough lockdown measures, according to the Telegraph. 

All the places listed so far have been under tougher restrictions for at least two weeks, some of them for longer. It raises concern that measures are in some way not working to squash cases.

Counted by the date specimens were collected, rather than the date the government published them, the UK had 11,404 cases on September 30, almost as many as were reported in the next two days combined

PHE MEMO REVEALS LOST CASES 

The cases that were missed out of the Department of Health’s count because of Public Health England’s counting blunder have been revealed in a memo leaked to Sky News.

They show there were an average of 8,328 cases per day announced during the September 25 to October 2 period, with a high of 11,754 on October 2 and a low of 4,044 on September 28. The latter number is unchanged from the Department of Health’s own count.

The adjusted data suggest the current average number of daily cases – calculated using the last seven days – is approximately 10,600. This is a rise from the average of 6,100 that would have been recorded in the week up to last Monday. 

Sep-25

Sep-26

Sep-27

Sep-28

Sep-29

Sep-30

Oct-1

Oct-2

6,874

6,042

5,693

4,044

7,143

7,108

6,914

6,968

7,831

6,786

6,450

4,044

8,558

10,157

11,047

11,754

 

The catastrophic failure of officials to release timely data will further exacerbate the problem because it leaves local health teams struggling to understand the outbreak.  

One of the top virus experts in Leeds blasted the test and trace blunder as ‘unacceptable’ following the news the city had breached the 300 cases per 100,000 line.

Dr Stephen Griffin, a viral oncologist based at the University of Leeds, said it would be difficult for local and national governments to plan responses to Covid cases if they can’t trust the numbers. 

He told LeedsLive: ‘My first reaction when I saw this was “good grief”. But if you look back and look at the data, we saw the majority in the last few days.

‘It’s hard to make a decision on these numbers because we are not sure on them – this is a real frustration. I don’t know what (the Government) is going to do now.

‘One important aspect in the mix up was that we really needed to understand whether the local measures were working – it’s going to be hard to understand that now.’ 

Newcastle, in the North East, saw one of the biggest spikes in reported cases following the addition of the thousands of new cases, with 399.6 per 100,000 people in the seven days up to October 1 – up from 256.6 the week before. 

And nearby Gateshead, South Tyneside and North Tyneside all saw an uptick in infection rates by at least 50 per cent. County Durham’s went up by 81 per cent.  

Nick Forbes – the Labour leader of Newcastle City Council – asked how local authorities could make ‘life-altering decisions’ for residents and businesses when they cannot be confident about Government data.

Mr Forbes said: ‘This is yet another catastrophic failure from an incompetent Government that is moving recklessly from one avoidable disaster to another.

‘Across the north-east we called for additional restrictions and measures built around the data we had, we did not call for these changes lightly and made the decisions based on intelligence and insight.

‘If we cannot be confident in the data we are receiving from the Government, how can we make these life-altering decisions and do what is best for our residents and businesses? 

‘It is essential we have the right data at the right time in order for us to protect our residents, support our businesses and enable our region to recover from this pandemic.’    

Ministers blamed an Excel spreadsheet error they had been concerned about for weeks, and an aged computer software, for the 16,000 cases disappearing in the transfer from PHE to NHS Test and Trace.   

Although positive Covid-19 people were told they had the disease, only half have been contacted by the NHS to discuss their movements since the blunder was first revealed on Friday, Health Secretary Matt Hancock said yesterday.

Prime Minister Boris Johnson was unable to say on Monday morning how many contacts of positive coronavirus cases had been missed. 

Labour said yesterday that some 48,000 people who have been in contact with a Covid-19 case may be ‘blissfully unaware’ they are spreading the disease when they should have been told to self isolate. Shadow health secretary Jonathan Ashworth said problems with testing were ‘putting lives at risk’. 

It’s not clear exactly what the repercussions of the ‘shambolic’ event will be. But local health chiefs have been left aghast and wondering how they can make decisions based on such unreliable Government data. 

Mr Hancock said in the Commons yesterday: ‘I want to reassure the house that outbreak control in care homes, schools and hospitals has not been directly affected because dealing with outbreaks in these settings does not primarily rely on this PHE system.’

He said it had been decided in July that the PHE ‘legacy system’ needed an upgrade, with contracts for a new system awarded in August. 

Mr Hancock said it was ‘critical that we work together to fix these issues that were themselves identified by PHE staff working hard late on Friday night’.

He added: ‘This incident should never have happened but the team has acted swiftly to minimise its impact and now it is critical that we work together to put this right and make sure it never happens again.’

Regarding the scale of the pandemic, Mr Hancock said the Government’s assessment has ‘not substantially changed’ after the error.

‘This morning the Joint Biosecurity Centre (JBC) presented to me their updated analysis of the epidemic based on the new figures,’ he said.

‘The chief medical officer (Chris Whitty) has analysed that our assessment of the disease and its impact has not substantially changed as a result of these data.

‘The JBC has confirmed that this has not impacted the basis on which decisions about local action were taken last week. Nevertheless, this is a serious issue that is being investigated fully.’

It came after a frightening rise in coronavirus cases was recorded in Britain yesterday. The Department of Health announced 12,594 more positive tests – more than triple the 4,368 that were recorded a fortnight ago – and the first ‘clean’ count since the Excel problem was fixed.

Last Monday’s data, which would usually be a good point of reference, is now unreliable because of a catastrophic counting error at Public Health England, meaning September 21 is the most recent Monday with an accurate number.

HOW HAS THE INFECTION RATE CHANGED WHERE YOU LIVE? LOCAL AUTHORITIES ARE LISTED FROM HIGH TO LOW BASED ON THEIR SEVEN-DAY ROLLING RATE IN THE WEEK TO OCTOBER 2
Local authority Infection rate (cases per 100,000) before (October 2) Infection rate (cases per 100,000) after (October 5) Percentage change Case change (cases per 100,000)
Manchester 289.4 529.4 83% 240
Knowsley 283 498.5 76% 215.5
Liverpool 287.7 487.1 69% 199.4
Newcastle upon Tyne 239.4 434.9 82% 195.5
Burnley 340.8 411.6 21% 70.8
Nottingham 100.6 382.4 280% 281.8
Leeds 149.3 316.8 112% 167.5
St Helens 216.5 311.8 44% 95.3
Sefton 191.4 307.9 61% 116.5
Halton 220.2 299 36% 78.8
Preston 216.6 294.8 36% 78.2
Pendle 205.2 294.2 43% 89
Rochdale 165.5 287.3 74% 121.8
Sheffield 110.1 286.6 160% 176.5
Salford 157.6 278.2 77% 120.6
Hyndburn 188.8 269 42% 80.2
Exeter 61.6 262.5 326% 200.9
South Tyneside 162.9 255 57% 92.1
Sunderland 165.6 254.6 54% 89
Bury 165.5 253.4 53% 87.9
Bradford 153 253.1 65% 100.1
Oldham 169.5 244.2 44% 74.7
Bolton 177 237.9 34% 60.9
Hartlepool 131.3 226.3 72% 95
Rossendale 144.1 223.8 55% 79.7
West Lancashire 137.4 217 58% 79.6
Trafford 126 215.3 71% 89.3
Wigan 134.2 214.5 60% 80.3
Middlesbrough 110.7 213.5 93% 102.8
Wirral 150.9 209.6 39% 58.7
Tameside 138.2 209.3 51% 71.1
Blackburn with Darwen 142.3 207.1 46% 64.8
Ribble Valley 106.8 202 89% 95.2
Warrington 151.4 199.5 32% 48.1
Gateshead 115.8 195.5 69% 79.7
North Tyneside 118.8 192.9 62% 74.1
Stockton-on-Tees 103.4 182.4 76% 79
Stockport 96.1 181.6 89% 85.5
South Ribble 108.3 172.4 59% 64.1
Darlington 109.5 172.3 57% 62.8
Northumberland 123.4 171.2 39% 47.8
Rotherham 88.9 162.4 83% 73.5
Kirklees 96.6 162.1 68% 65.5
County Durham 88.9 160.5 81% 71.6
Barrow-in-Furness 111.9 156.6 40% 44.7
Blackpool 86.8 154.2 78% 67.4
Craven 108.5 150.5 39% 42
York 66 143.9 118% 77.9
Birmingham 109.6 143.6 31% 34
Lancaster 66.4 143.1 116% 76.7
Rushcliffe 50.3 141 180% 90.7
Redcar and Cleveland 60.5 135.6 124% 75.1
Calderdale 83.7 132.4 58% 48.7
Broxtowe 46.5 130.7 181% 84.2
Leicester 80.7 130.1 61% 49.4
Chorley 72.7 126.9 75% 54.2
Wakefield 72.6 126.6 74% 54
Barnsley 65.6 124 89% 58.4
Fylde 106.5 121.3 14% 14.8
Oadby and Wigston 63.1 121 92% 57.9
Cheshire West and Chester 69.1 118.3 71% 49.2
Richmondshire 72.6 115.4 59% 42.8
Sandwell 85.2 114.5 34% 29.3
Cheshire East 56 113 102% 57
Doncaster 54.2 110.6 104% 56.4
Gedling 45 106 136% 61
High Peak 61.5 104.7 70% 43.2
Walsall 65.5 103.7 58% 38.2
Harrogate 52.9 103.2 95% 50.3
Solihull 78.6 102.6 31% 24
Wyre 71.4 101.7 42% 30.3
Stafford 55.4 101.3 83% 45.9
Oxford 60.3 99 64% 38.7
Newark and Sherwood 84.1 98.8 17% 14.7
Hambleton 48 97.2 103% 49.2
Redbridge 62.2 93.7 51% 31.5
Coventry 61.4 92.6 51% 31.2
Great Yarmouth 59.4 91.6 54% 32.2
Charnwood 35 90.9 160% 55.9
East Riding of Yorkshire 51.3 90.3 76% 39
Newcastle-under-Lyme 52.5 89.6 71% 37.1
Richmond upon Thames 36.9 86.4 134% 49.5
Scarborough 43.2 86.4 100% 43.2
North East Derbyshire 37.5 85.7 129% 48.2
South Lakeland 29.5 84.7 187% 55.2
Hackney and City of London 44 84.6 92% 40.6
Bromsgrove 34 84.1 147% 50.1
Selby 49.7 82.8 67% 33.1
West Lindsey 28.2 82.6 193% 54.4
Blaby 48.3 81.8 69% 33.5
South Staffordshire 52.5 80 52% 27.5
Ashfield 43 79.7 85% 36.7
Hertsmere 27.6 78.2 183% 50.6
Erewash 38.1 78 105% 39.9
Hull 28.1 75.8 170% 47.7
Harrow 34.2 75.8 122% 41.6
Ryedale 34.3 75.8 121% 41.5
Haringey 34.6 75.2 117% 40.6
Rugby 42.2 74.4 76% 32.2
Ealing 47.1 74.3 58% 27.2
Slough 62.2 74.2 19% 12
North Lincolnshire 38.9 73.1 88% 34.2
Elmbridge 23.4 72.4 209% 49
Bassetlaw 35.8 71.5 100% 35.7
Tower Hamlets 40.3 70.5 75% 30.2
Barnet 33.3 70 110% 36.7
Lincoln 54.4 69.5 28% 15.1
Wolverhampton 56.2 69.5 24% 13.3
East Staffordshire 34.2 69.3 103% 35.1
Hounslow 50.8 68.5 35% 17.7
Dudley 48.5 66.9 38% 18.4
Worcester 37.5 66.2 77% 28.7
Derby 32.6 66.1 103% 33.5
Newham 53.8 65.1 21% 11.3
Brent 39.7 64.6 63% 24.9
Melton 21.5 64.4 200% 42.9
Amber Valley 38.2 64 68% 25.8
East Northamptonshire 27.5 63.5 131% 36
Islington 35.5 63.5 79% 28
Lichfield 31.5 63 100% 31.5
Harborough 30.9 62.9 104% 32
Hammersmith and Fulham 38.3 62.7 64% 24.4
Waltham Forest 33.2 62.5 88% 29.3
Stoke-on-Trent 41.7 61.2 47% 19.5
Wychavon 28.6 61 113% 32.4
Hinckley and Bosworth 37.1 61 64% 23.9
Havering 48.5 60.9 26% 12.4
Windsor and Maidenhead 26.4 60.1 128% 33.7
Brentwood 27.3 60.1 120% 32.8
Nuneaton and Bedworth 37 60.1 62% 23.1
St Albans 34.4 59.3 72% 24.9
Enfield 37.4 59.3 59% 21.9
Stratford-on-Avon 22.3 59.2 165% 36.9
Hillingdon 42 59 40% 17
Allerdale 31.7 58.3 84% 26.6
Bedford 39.8 58.3 46% 18.5
Watford 29 58 100% 29
Croydon 25.9 57.4 122% 31.5
Shropshire 34 57.3 69% 23.3
South Bucks 42.8 57.1 33% 14.3
Wandsworth 27.3 57 109% 29.7
Lambeth 27.3 57 109% 29.7
Uttlesford 39.4 57 45% 17.6
South Derbyshire 34.5 56.9 65% 22.4
East Hertfordshire 28 56.8 103% 28.8
Telford and Wrekin 37.8 56.7 50% 18.9
Luton 52.1 56.3 8% 4.2
Bolsover 32.3 55.9 73% 23.6
Kingston upon Thames 29.3 55.8 90% 26.5
Lewisham 24.2 55.6 130% 31.4
Barking and Dagenham 48.4 55 14% 6.6
North East Lincolnshire 25.7 54.5 112% 28.8
Southwark 31.7 53.9 70% 22.2
Woking 27.8 53.6 93% 25.8
Chesterfield 21 53.4 154% 32.4
Epping Forest 38.7 53.2 37% 14.5
Rutland 30.1 52.6 75% 22.5
Guildford 22.8 52.3 129% 29.5
Copeland 30.8 51.3 67% 20.5
Dacorum 32.3 51 58% 18.7
Malvern Hills 29.2 50.8 74% 21.6
Westminster 24.9 50.5 103% 25.6
Spelthorne 28 50.1 79% 22.1
Daventry 20.9 50 139% 29.1
South Kesteven 21.8 49.1 125% 27.3
Peterborough 23.2 48.9 111% 25.7
Bath and North East Somerset 26.4 48.1 82% 21.7
Rushmoor 14.8 47.6 222% 32.8
North Warwickshire 30.6 47.5 55% 16.9
Epsom and Ewell 17.4 47.1 171% 29.7
Waverley 23 46.7 103% 23.7
Staffordshire Moorlands 24.4 46.7 91% 22.3
Basildon 30.4 46.5 53% 16.1
Wellingborough 25.1 46.4 85% 21.3
South Gloucestershire 23.5 46.3 97% 22.8
Kensington and Chelsea 25.6 46.1 80% 20.5
Three Rivers 37.5 46.1 23% 8.6
Bristol 19.4 45.5 135% 26.1
Wyre Forest 40.5 45.4 12% 4.9
Northampton 15.6 45 188% 29.4
Bexley 19.3 44.7 132% 25.4
Runnymede 20.1 44.7 122% 24.6
Cannock Chase 22.8 44.7 96% 21.9
Redditch 32.8 44.6 36% 11.8
Huntingdonshire 19.7 44.4 125% 24.7
Mansfield 23.8 43.9 84% 20.1
Warwick 27.8 43.8 58% 16
Brighton and Hove 21.7 43.7 101% 22
South Cambridgeshire 20.1 42.7 112% 22.6
Tandridge 21.6 42 94% 20.4
Derbyshire Dales 11.1 41.5 274% 30.4
Camden 20.4 41.5 103% 21.1
North West Leicestershire 23.2 41.5 79% 18.3
Carlisle 28.5 41.4 45% 12.9
North Kesteven 21.4 41.1 92% 19.7
Greenwich 27.8 41 47% 13.2
Bournemouth, Christchurch and Poole 25.3 40.5 60% 15.2
Vale of White Horse 14.7 40.4 175% 25.7
Surrey Heath 23.5 40.3 71% 16.8
Bromley 21.1 39.4 87% 18.3
Castle Point 24.3 38.7 59% 14.4
Winchester 19.2 38.4 100% 19.2
Broxbourne 31.9 38 19% 6.1
Tamworth 14.3 37.8 164% 23.5
Cheltenham 21.5 37.8 76% 16.3
Chiltern 21.9 37.5 71% 15.6
Torbay 25 37.4 50% 12.4
Sevenoaks 16.6 37.3 125% 20.7
Gloucester 16.3 37.2 128% 20.9
Southampton 17 37.2 119% 20.2
Mole Valley 14.9 36.7 146% 21.8
Kettering 20.6 36.4 77% 15.8
Chelmsford 24.1 35.9 49% 11.8
Merton 22.8 35.3 55% 12.5
Wokingham 21.6 35.1 63% 13.5
Test Valley 12.7 34.9 175% 22.2
Somerset West and Taunton 16.1 34.8 116% 18.7
Cherwell 14.6 34.6 137% 20
Corby 31.8 34.6 9% 2.8
Cambridge 21.6 34.5 60% 12.9
Wycombe 16.6 34.4 107% 17.8
West Berkshire 20.2 34.1 69% 13.9
Portsmouth 25.1 34 35% 8.9
Milton Keynes 19.7 33.8 72% 14.1
Eden 24.4 33.8 39% 9.4
North Hertfordshire 15.7 33.7 115% 18
Hastings 16.2 33.5 107% 17.3
Fenland 7.9 33.4 323% 25.5
Welwyn Hatfield 17.1 33.3 95% 16.2
Thurrock 21.8 32.1 47% 10.3
Norwich 11.4 32 181% 20.6
Tunbridge Wells 16.8 32 90% 15.2
Hart 13.4 31.9 138% 18.5
Gravesham 9.4 31.8 238% 22.4
West Oxfordshire 19 31.6 66% 12.6
Canterbury 16.3 31.4 93% 15.1
East Hampshire 14.7 31.1 112% 16.4
South Northamptonshire 13.8 30.7 122% 16.9
Horsham 13.2 30.6 132% 17.4
Plymouth 15.3 30.5 99% 15.2
Sutton 16 30.5 91% 14.5
South Oxfordshire 11.3 30.3 168% 19
Southend-on-Sea 27.8 30 8% 2.2
Eastbourne 14.5 29.9 106% 15.4
Swale 10.7 29.3 174% 18.6
Teignbridge 11.9 29.1 145% 17.2
South Norfolk 19.9 29.1 46% 9.2
Chichester 17.3 28.1 62% 10.8
East Suffolk 13.6 27.7 104% 14.1
Central Bedfordshire 17.3 27.7 60% 10.4
South Holland 10.5 27.4 161% 16.9
West Suffolk 11.7 27.4 134% 15.7
Reading 21.6 27.2 26% 5.6
Bracknell Forest 14.7 26.9 83% 12.2
Dartford 20.4 26.6 30% 6.2
Mendip 12.1 26 115% 13.9
Wiltshire 13.6 26 91% 12.4
Mid Sussex 13.9 25.8 86% 11.9
KingÕs Lynn and West Norfolk 13.9 25.8 86% 11.9
Forest of Dean 19.6 25.3 29% 5.7
Stroud 10 25 150% 15
Aylesbury Vale 13 24.6 89% 11.6
North Somerset 14 24.6 76% 10.6
Cotswold 6.7 24.5 266% 17.8
Arun 18 24.3 35% 6.3
Reigate and Banstead 10.8 24.2 124% 13.4
Lewes 11.6 24.2 109% 12.6
Tewkesbury 12.6 24.2 92% 11.6
East Devon 7.5 23.9 219% 16.4
Havant 17.4 23.8 37% 6.4
Braintree 13.1 22.9 75% 9.8
East Lindsey 16.9 22.6 34% 5.7
Wealden 6.2 22.3 260% 16.1
Mid Devon 8.5 21.9 158% 13.4
Medway 12.2 21.9 80% 9.7
Harlow 20.7 21.8 5% 1.1
New Forest 13.9 21.7 56% 7.8
Breckland 10 21.4 114% 11.4
Boston 18.5 21.4 16% 2.9
Cornwall and Isles of Scilly 24.8 21.3 -14% -3.5
Tonbridge and Malling 9.8 21.2 116% 11.4
Broadland 8.4 20.6 145% 12.2
Rochford 10.3 20.6 100% 10.3
Thanet 7 19.7 181% 12.7
Babergh 2.2 19.6 791% 17.4
South Somerset 11.3 19.6 73% 8.3
North Devon 13.4 19.6 46% 6.2
Crawley 21.4 19.6 -8% -1.8
Dorset 10.8 18.8 74% 8
Adur 7.8 18.7 140% 10.9
Colchester 10.8 18.5 71% 7.7
Herefordshire 11.4 18.2 60% 6.8
Basingstoke and Deane 9.6 18.1 89% 8.5
Swindon 11.7 18 54% 6.3
Rother 8.3 17.7 113% 9.4
Maidstone 9.9 17.5 77% 7.6
Mid Suffolk 8.7 17.3 99% 8.6
South Hams 10.3 17.2 67% 6.9
Worthing 15.4 17.2 12% 1.8
Stevenage 8 17.1 114% 9.1
Tendring 12.3 17.1 39% 4.8
Sedgemoor 13 17 31% 4
Ashford 6.9 16.9 145% 10
Maldon 18.5 15.4 -17% -3.1
Gosport 14.1 15.3 9% 1.2
West Devon 7.2 14.3 99% 7.1
Folkestone and Hythe 8.8 14.2 61% 5.4
Eastleigh 4.5 13.5 200% 9
East Cambridgeshire 12.2 13.4 10% 1.2
Ipswich 9.5 13.1 38% 3.6
Dover 6.8 11.9 75% 5.1
North Norfolk 4.8 11.4 138% 6.6
Fareham 8.6 11.2 30% 2.6
Torridge 5.9 8.8 49% 2.9
Isle of Wight 6.3 6.3 0% 0

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