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These initiatives were driven by Lord Taylor of Goss Moor, and are more likely to reflect personal policy preferences.
Lord Taylor of Goss Moor has not introduced any legislation before Parliament
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The information requested falls under the remit of the UK Statistics Authority.
Please see the letter attached from the National Statistician and Chief Executive of the UK Statistics Authority.
Lord Taylor of Goss Moor
House of Lords
London
SW1A 0PW
27 November 2023
Dear Lord Taylor,
As National Statistician and Chief Executive of the UK Statistics Authority, I am responding to your Parliamentary Question asking a) how many babies were born in England each year since 1945 (HL435) and b) how many babies were registered in Cornwall in each year since 1945 (HL436).
The Office for National Statistics (ONS) publishes statistics on births registered in England. Birth statistics are based on year of registration, rather than date of birth.
Table 1 of the attached dataset provides numbers of live births registered in England from 1945 to 2022, and stillbirths registered from 1981 to 2023. Data on stillbirths registered in England prior to 1981 are not available.
Table 2 of the attached dataset provides numbers of live births and stillbirths registered in Cornwall from 1981 to 2022. Figures for Cornwall are based on the mother’s usual residence. Data on the mother’s usual residence prior to 1981 is not available.
Yours sincerely,
Professor Sir Ian Diamond
The information requested falls under the remit of the UK Statistics Authority.
Please see the letter attached from the National Statistician and Chief Executive of the UK Statistics Authority.
Lord Taylor of Goss Moor
House of Lords
London
SW1A 0PW
27 November 2023
Dear Lord Taylor,
As National Statistician and Chief Executive of the UK Statistics Authority, I am responding to your Parliamentary Question asking a) how many babies were born in England each year since 1945 (HL435) and b) how many babies were registered in Cornwall in each year since 1945 (HL436).
The Office for National Statistics (ONS) publishes statistics on births registered in England. Birth statistics are based on year of registration, rather than date of birth.
Table 1 of the attached dataset provides numbers of live births registered in England from 1945 to 2022, and stillbirths registered from 1981 to 2023. Data on stillbirths registered in England prior to 1981 are not available.
Table 2 of the attached dataset provides numbers of live births and stillbirths registered in Cornwall from 1981 to 2022. Figures for Cornwall are based on the mother’s usual residence. Data on the mother’s usual residence prior to 1981 is not available.
Yours sincerely,
Professor Sir Ian Diamond
The information requested falls under the remit of the UK Statistics Authority.
Please see the letter attached from the National Statistician and Chief Executive of the UK Statistics Authority.
The Lord Taylor of Goss Moor
House of Lords
London
SW1A 0PW
28 November 2023
Dear Lord Taylor,
As National Statistician and Chief Executive of the UK Statistics Authority, I am responding to your Parliamentary Questions asking about the number of (1) over 65-year-olds (HL437), and (2) over 80-year-olds in each year since 1945 for both the UK as a whole and those living in Cornwall (HL438).
The Office for National Statistics (ONS) is responsible for publishing population estimates for the United Kingdom. The attached Excel file provides estimates for the United Kingdom from 1953 to 2021 and for England and Wales from 1945 to 2022. United Kingdom age group estimates are not available from before 1953. Estimates for the United Kingdom for 2022 are not yet available due to synchronisation issues caused by the latest census being held in 2021 in England, Wales, and Northern Ireland and in 2022 in Scotland.
The file also contains estimates for Cornwall from 1971 to 2022. Age group estimates prior to 1991 are not available for Cornwall as local authority reorganisation in the early 1970s prevents comparisons prior to 1971.
When accessing any of our files please read the 'notes, terms and conditions' contained within them.
Yours sincerely,
Professor Sir Ian Diamond
The information requested falls under the remit of the UK Statistics Authority.
Please see the letter attached from the National Statistician and Chief Executive of the UK Statistics Authority.
The Lord Taylor of Goss Moor
House of Lords
London
SW1A 0PW
28 November 2023
Dear Lord Taylor,
As National Statistician and Chief Executive of the UK Statistics Authority, I am responding to your Parliamentary Questions asking about the number of (1) over 65-year-olds (HL437), and (2) over 80-year-olds in each year since 1945 for both the UK as a whole and those living in Cornwall (HL438).
The Office for National Statistics (ONS) is responsible for publishing population estimates for the United Kingdom. The attached Excel file provides estimates for the United Kingdom from 1953 to 2021 and for England and Wales from 1945 to 2022. United Kingdom age group estimates are not available from before 1953. Estimates for the United Kingdom for 2022 are not yet available due to synchronisation issues caused by the latest census being held in 2021 in England, Wales, and Northern Ireland and in 2022 in Scotland.
The file also contains estimates for Cornwall from 1971 to 2022. Age group estimates prior to 1991 are not available for Cornwall as local authority reorganisation in the early 1970s prevents comparisons prior to 1971.
When accessing any of our files please read the 'notes, terms and conditions' contained within them.
Yours sincerely,
Professor Sir Ian Diamond
Throughout the pandemic, the Government has used a broad range of health, social and economic evidence to inform decision making. The Scientific Advisory Group for Emergency (SAGE) is responsible for providing coordinated scientific advice to support decisions made by the Government. The SAGE subgroup, the Scientific Pandemic Influenza Group on Modelling (SPI-M), uses estimates across a range of metrics to support this advice, including short term modelling including on cases & hospitalisations. These models include a range of projections based on the observed rates of infection and hospitalisations. The assumptions underpinning these models develop as our understanding of the virus changes.
At the end of October, it was clear that rising infections had the potential to exceed NHS regular and surge capacity within weeks. Case projections showed increases in every region, and that national intervention was therefore necessary.
In December, the SAGE subgroup on New and Emerging Respiratory Virus Threats (NERVTAG), estimated that the B.1.1.7 variant may be up to 70% more transmissible. This informed the rapid escalation of areas and regions through the tier system in late December and a creation of Tier 4. Further analysis across a number of infection metrics, along with SPI-M modelled projections, helped inform the decision that national restrictions were again required on 5 January.
The Reasonable Worst Case Scenario is an operational contingency planning tool. The Government has used a broad range of health, social and economic evidence to inform decision making, including modelled projections. The evidence used to introduce measures on 5 January 2021 included amended assumptions based on the increased transmissibility of the B.1.1.7 variant.
The Government is working to publish a full technical consultation later this year on the Future Homes and Building Standards. As part of the consultation, we will explore how we can continue to drive onsite renewable electricity generation, such as solar panels, where appropriate in new homes and buildings.
I refer the Noble Lord to my answer of 24 November 2023 to Question HL257.
Since the 2020/21 academic year, the department has made significant increases in funding per student for 16–19 year-old education. The 2021 Spending Review made available an extra £1.6 billion for 16-19 education in the 2024/25 financial year compared with 2021/22.
In July 2023, the department announced that it will be investing £185 million in 2023/24 and £285 million in 2024/25 to drive forward skills delivery in the further education sector. This funding will help colleges and other providers to continue to deliver high-value technical, vocational, and academic provision needed to power economic growth and prosperity. This investment will be delivered via core 16-19 year-old funding, including through boosting programme cost weightings for higher-cost subject areas, as well as increasing the per-student funding rate. This investment is on top of £125 million the department announced in January 2023 for 16-19 education in the 2023/24 financial year.
In October 2023, the government announced that, in the future, students retaking English and mathematics GCSE while studying at Level 2 or below will attract the same funding that those studying at Level 3 already receive.
The department does not record the real terms changes to funding as requested and therefore does not hold this information.
The table below uses the published 16-19 funding allocations to derive the average funding per student, in both England and Cornwall from 2014/15 and the subsequent nine academic years, in cash terms. This includes all 16-19 funded students, including those in further education colleges, school sixth forms, and other types of provider. The figures are not available for 2005/06 to 2013/14.
Average total programme funding per student[1] England | Cornwall | |
2014/2015 | £4,432 | £4,200 |
2015/2016 | £4,489 | £4,326 |
2016/2017 | £4,488 | £4,396 |
2017/2018 | £4,514 | £4,393 |
2018/2019 | £4,504 | £4,410 |
2019/2020 | £4,516 | £4,447 |
2020/2021 | £4,958 | £4,783 |
2021/2022 | £4,994 | £4,878 |
2022/2023 | £5,469 | £5,321 |
2023/2024 | £5,923 | £5,779 |
[1] This calculation only includes institutions that have students receiving total programme funding. Some institutions receive only high needs funding – their students are not included in this calculation.
The department is continuing to invest in education and skills training for adults through the Adult Education Budget (AEB). This resulted in £1.34 billion of investment in the 2023/24 Funding Year.
In 2023/24, the government has devolved approximately 60% of the AEB to 9 Mayoral Combined Authorities (MCAs) and the Greater London Authority (GLA). These authorities are now responsible for the provision of AEB-funded adult education for their residents, allocation of the AEB to providers, and for reporting funding in devolved areas. The Education and Skills Funding Agency (ESFA) is responsible for the remaining AEB in non-devolved areas. In ESFA AEB areas the department applied a 2.2% increase to the final earnings for all AEB formula-funded provision (excluding associated learner and learning support) in the 2022/23 and 2023/24 academic years. In addition, the department also applied a 20% boost on top of earnings for all AEB formula-funded provision in 6 sector subject areas: Engineering, Manufacturing Technologies, Transport Operations and Maintenance, Building and Construction, ICT for Practitioners, and Mathematics and Statistics.
Spend by the department on further education is reported through publication of the Annual Report and Accounts, which is available at: https://www.gov.uk/government/collections/dfe-annual-reports. The department is unable to provide average funding per learner as funding is determined by a combination of factors including funding rates, funding formulas, earnings method and support funding.
The table below provides per pupil funding units from 2013/14 to 2023/24, which represent the funding provided by the government for schools in Cornwall each year.
The school funding system changed significantly between 2012/13 and 2013/14, which is when the schools block was first introduced. The department does not have comparable data for primary schools from 2005 to 2012/13.
From 2013/14, the department has supplied data on the “schools block per-pupil unit of funding”. This covers both primary and secondary schools together. The department does not have separate data for primary pupils for this period.
The funding system changed again in 2018/19 when the National Funding Formula (NFF) was introduced. With the introduction of the NFF, funding was provided by reference to primary and secondary schools separately. The table below shows both per primary and per secondary pupil funding amounts.
The scope of the per pupil figures pre and post-2018 in the table below are not directly comparable. In particular, the central services provided by local authorities was split out from the schools block funding in 2018/19, and instead funded separately through the central school services block from that year onwards.
The figures in the table below are provided on a cash basis. The department also published real-terms statistics on schools funding at the national level which does not distinguish by phase. The department used the GDP deflator to calculate real-terms funding levels. Further information can be found at: https://explore-education-statistics.service.gov.uk/find-statistics/school-funding-statistics, and the GDP deflator can be found online at: https://explore-education-statistics.service.gov.uk/methodology/school-funding-statistics-methodology.
Year | DSG | England | Cornwall |
2013-14 | Schools Block per-pupil Unit of Funding | £4,550.54 | £4,396.58 |
2014-15 | Schools block per-pupil unit of funding | £4,555.02 | £4,396.58 |
2015-16 | Schools block unit of funding | £4,612.11 | £4,464.04 |
2016-17 | Schools block unit of funding (SBUF) | £4,636.43 | £4,467.43 |
2017-18 | Schools block unit of funding (SBUF) | £4,618.63 | £4,428.26 |
2018-19 | Schools block primary unit of funding | £4,057.87 | £3,957.13 |
Schools block secondary unit of funding | £5,228.74 | £4,992.96 | |
2019-20 | Schools block primary unit of funding | £4,098.82 | £3,989.71 |
Schools block secondary unit of funding | £5,294.78 | £5,030.28 | |
2020-21 | Schools block primary unit of funding | £4278.92 | £4,218.40 |
Schools block secondary unit of funding | £5495.88 | £5,187.28 | |
2021-22 | Schools block primary unit of funding | £4,610.68 | £4,573.43 |
Schools block secondary unit of funding | £5,934.86 | £5,623.44 | |
2022-23 | Schools block primary unit of funding | £4,731.72 | £4,751.53 |
Schools block secondary unit of funding | £6,100.01 | £5,784.42 | |
2023-24 | Schools block primary unit of funding | £4,954.27 | £4,988.31 |
Schools block secondary unit of funding | £6,421.94 | £6,117.31 |
The NFF takes account of a wide range of factors that affect the costs schools face, including the particular challenges faced by small schools in rural areas through the sparsity factor. This recognises that some schools are necessarily small because they are remote and do not have the same opportunities to grow or make efficiency savings as other schools, and that such schools often play a significant role in the rural communities they serve.
In recent years, the government has made changes to the sparsity factor which have seen the total amount allocated, nationally, increase from £26 million in 2020/21 to £97 million in 2023/24. In 2023/24, 108 of Cornwall’s 268 schools (40.3%) are in receipt of this funding. The change in Cornwall’s schools’ sparsity funding over time is illustrated in the table below:
Financial Year | Total Sparsity Funding Allocated to Cornwall Through the NFF |
2018/19 | £1,094,868 |
2019/20 | £1,144,828 |
2020/21 | £1,161,341 |
2021/22 | £1,884,761 |
2022/23 | £4,196,307 |
2023/24 | £4,265,424 |
Note: In financial year 2022/23 the sparsity calculation was changed
The table summarises maintenance expenditure by road class, adjusted for inflation, in England, from April 2005 onwards.
Road class | Financial Year Ending (FYE) | Structural Treatment [Note 1, 2] | Routine and other Treatment [Note 1, 2] | Highways Maintenance Policy, Planning and Strategy [Note 2] | Total [Note 2] |
Trunk motorway and trunk 'A' roads [Note 3] | FYE 2006 | 728 | 457 | [z] | 1,185 |
Trunk motorway and trunk 'A' roads [Note 3] | FYE 2007 | 681 | 466 | [z] | 1,148 |
Trunk motorway and trunk 'A' roads [Note 3] | FYE 2008 | 646 | 513 | [z] | 1,159 |
Trunk motorway and trunk 'A' roads [Note 3] | FYE 2009 | 633 | 530 | [z] | 1,164 |
Trunk motorway and trunk 'A' roads [Note 3] | FYE 2010 [Note 4] | 1,166 | 477 | [z] | 1,643 |
Trunk motorway and trunk 'A' roads [Note 3] | FYE 2011 | 579 | 375 | [z] | 954 |
Trunk motorway and trunk 'A' roads [Note 3] | FYE 2012 | 595 | 387 | [z] | 982 |
Trunk motorway and trunk 'A' roads [Note 3] | FYE 2013 | 513 | 332 | [z] | 845 |
Trunk motorway and trunk 'A' roads [Note 3] | FYE 2014 | 620 | 306 | [z] | 926 |
Trunk motorway and trunk 'A' roads [Note 3] | FYE 2015 | 864 | 270 | [z] | 1,135 |
Trunk motorway and trunk 'A' roads [Note 3] | FYE 2016 | 790 | 305 | [z] | 1,095 |
Trunk motorway and trunk 'A' roads [Note 3] | FYE 2017 | 716 | 292 | [z] | 1,007 |
Trunk motorway and trunk 'A' roads [Note 3] | FYE 2018 | 870 | 287 | [z] | 1,157 |
Trunk motorway and trunk 'A' roads [Note 3] | FYE 2019 | 744 | 299 | [z] | 1,043 |
Trunk motorway and trunk 'A' roads [Note 3] | FYE 2020 | 777 | 283 | [z] | 1,060 |
Trunk motorway and trunk 'A' roads [Note 3] | FYE 2021 | 763 | 297 | [z] | 1,059 |
Trunk motorway and trunk 'A' roads [Note 3] | FYE 2022 | 887 | 285 | [z] | 1,172 |
Local authority roads [Note 6, 7, 8] | FYE 2006 | 2,439 | 1,664 | 389 | 4,492 |
Local authority roads [Note 6, 7, 8] | FYE 2007 | 2,315 | 1,596 | 428 | 4,338 |
Local authority roads [Note 6, 7, 8] | FYE 2008 | 2,265 | 1,721 | 419 | 4,406 |
Local authority roads [Note 6, 7, 8] | FYE 2009 | 2,213 | 1,315 | 390 | 3,918 |
Local authority roads [Note 6, 7, 8] | FYE 2010 [Note 4] | 2,502 | 1,774 | 421 | 4,696 |
Local authority roads [Note 6, 7, 8] | FYE 2011 | 2,386 | 1,673 | 390 | 4,449 |
Local authority roads [Note 6, 7, 8] | FYE 2012 | 2,313 | 1,573 | 345 | 4,231 |
Local authority roads [Note 6, 7, 8] | FYE 2013 | 2,022 | 1,528 | 339 | 3,888 |
Local authority roads [Note 6, 7, 8] | FYE 2014 | 2,119 | 1,496 | 358 | 3,973 |
Local authority roads [Note 6, 7, 8] | FYE 2015 | 2,539 | 1,315 | 323 | 4,178 |
Local authority roads [Note 6, 7, 8] | FYE 2016 | 2,489 | 1,246 | 369 | 4,103 |
Local authority roads [Note 6, 7, 8] | FYE 2017 | 2,507 | 1,198 | 380 | 4,085 |
Local authority roads [Note 6, 7, 8] | FYE 2018 | 2,442 | 1,243 | 363 | 4,047 |
Local authority roads [Note 6, 7, 8] | FYE 2019 | 2,792 | 1,116 | 351 | 4,259 |
Local authority roads [Note 6, 7, 8] | FYE 2020 | 2,661 | 1,103 | 403 | 4,167 |
Local authority roads [Note 6, 7, 8] | FYE 2021 | 2,650 | 1,092 | 399 | 4,141 |
Local authority roads [Note 6, 7, 8] | FYE 2022 | 2,484 | 1,153 | 532 | 4,168 |
Of which: Local authority motorway and 'A' roads | FYE 2006 | 745 | 552 | [z] | 1,297 |
Of which: Local authority motorway and 'A' roads | FYE 2007 | 690 | 487 | [z] | 1,177 |
Of which: Local authority motorway and 'A' roads | FYE 2008 | 616 | 608 | [z] | 1,224 |
Of which: Local authority motorway and 'A' roads | FYE 2009 | 601 | 370 | [z] | 971 |
Of which: Local authority motorway and 'A' roads | FYE 2010 [Note 4] | 779 | 686 | [z] | 1,464 |
Of which: Local authority motorway and 'A' roads | FYE 2011 | 774 | 565 | [z] | 1,339 |
Of which: Local authority motorway and 'A' roads | FYE 2012 | 874 | 601 | [z] | 1,474 |
Of which: Local authority motorway and 'A' roads | FYE 2013 | 688 | 581 | [z] | 1,270 |
Of which: Local authority motorway and 'A' roads | FYE 2014 | 750 | 608 | [z] | 1,358 |
Of which: Local authority motorway and 'A' roads | FYE 2015 | 976 | 426 | [z] | 1,401 |
Of which: Local authority motorway and 'A' roads | FYE 2016 | 927 | 464 | [z] | 1,391 |
Of which: Local authority motorway and 'A' roads | FYE 2017 | 1,192 | 415 | [z] | 1,607 |
Of which: Local authority motorway and 'A' roads | FYE 2018 | 1,047 | 477 | [z] | 1,524 |
Of which: Local authority motorway and 'A' roads | FYE 2019 | 1,069 | 359 | [z] | 1,428 |
Of which: Local authority motorway and 'A' roads | FYE 2020 | 1,021 | 326 | [z] | 1,347 |
Of which: Local authority motorway and 'A' roads | FYE 2021 | 973 | 321 | [z] | 1,295 |
Of which: Local authority motorway and 'A' roads | FYE 2022 | 852 | 360 | [z] | 1,212 |
Of which: Local authority minor roads ('B', 'C' and 'U') | FYE 2006 | 1,694 | 1,112 | [z] | 2,806 |
Of which: Local authority minor roads ('B', 'C' and 'U') | FYE 2007 | 1,625 | 1,108 | [z] | 2,733 |
Of which: Local authority minor roads ('B', 'C' and 'U') | FYE 2008 | 1,649 | 1,114 | [z] | 2,763 |
Of which: Local authority minor roads ('B', 'C' and 'U') | FYE 2009 | 1,612 | 945 | [z] | 2,557 |
Of which: Local authority minor roads ('B', 'C' and 'U') | FYE 2010 [Note 4] | 1,723 | 1,088 | [z] | 2,811 |
Of which: Local authority minor roads ('B', 'C' and 'U') | FYE 2011 | 1,612 | 1,108 | [z] | 2,720 |
Of which: Local authority minor roads ('B', 'C' and 'U') | FYE 2012 | 1,439 | 973 | [z] | 2,412 |
Of which: Local authority minor roads ('B', 'C' and 'U') | FYE 2013 | 1,333 | 946 | [z] | 2,280 |
Of which: Local authority minor roads ('B', 'C' and 'U') | FYE 2014 | 1,369 | 889 | [z] | 2,258 |
Of which: Local authority minor roads ('B', 'C' and 'U') | FYE 2015 | 1,564 | 890 | [z] | 2,453 |
Of which: Local authority minor roads ('B', 'C' and 'U') | FYE 2016 | 1,561 | 782 | [z] | 2,343 |
Of which: Local authority minor roads ('B', 'C' and 'U') | FYE 2017 | 1,315 | 783 | [z] | 2,098 |
Of which: Local authority minor roads ('B', 'C' and 'U') | FYE 2018 | 1,394 | 766 | [z] | 2,160 |
Of which: Local authority minor roads ('B', 'C' and 'U') | FYE 2019 | 1,723 | 758 | [z] | 2,480 |
Of which: Local authority minor roads ('B', 'C' and 'U') | FYE 2020 | 1,640 | 777 | [z] | 2,417 |
Of which: Local authority minor roads ('B', 'C' and 'U') | FYE 2021 | 1,676 | 771 | [z] | 2,447 |
Of which: Local authority minor roads ('B', 'C' and 'U') | FYE 2022 | 1,632 | 793 | [z] | 2,42 |
Information about the value in real terms of vehicle excise duty (VED) receipts is not held. The table below provides the VED figures reported in the published Annual Report & Accounts between years 2005-06 and 2022-23. Net Revenue stated as VED in the Statement of revenue & expenditure published Accounts.
Year | £m |
|
2022-23 | 7,325 | |
2021-22 | 7,133 | |
2020-21 | 6,898 | |
2019-20 | 6,775 | |
2018-19 | 6,390 | |
2017-18 | 6,001 | |
2016-17 | 5,876 | |
2015-16 | 5,930 | |
2014-15 | 6,023 | |
2013-14 | 6,052 | |
2012-13 | 6,013 | |
2011-12 | 5,932 | |
2010-11 | 5,782 | |
2009-10 | 5,742 | |
2008-09 | 5,543 | |
2007-08 | 5,269 | |
2006-07 | 4,984 | |
2005-06 | 4,953 |
Ambulance response time standards were reformed following the recommendations of the Ambulance Response Programme in 2017, including the publication of average response times.
We recognise the pressures the ambulance service is facing which is why we published our Recovery Plan for Urgent and Emergency Care Services. The ambition is to deliver one of the fastest and longest sustained improvements in emergency waiting times in the National Health Service's history. We aim to reduce average Category 2 response times to 30 minutes this year with further improvements towards pre-pandemic levels next year.
Ambulance response times are recorded at an ambulance trust level. Royal Cornwall Hospitals NHS Trust is served by South West Ambulance Service. The following table shows the South West Ambulance Service average response time since the introduction of the standards in August 2017.
South West Ambulance Service average response times (hh:mm:ss)
Year | Category 1 mean | Category 2 mean | Category 3 mean | Category 4 mean |
2017/18 (August-March) | 00:09:42 | 00:33:22 | 01:15:30 | 02:00:33 |
2018/19 | 00:07:18 | 00:27:26 | 01:12:09 | 02:06:25 |
2019/20 | 00:07:03 | 00:28:38 | 01:17:17 | 01:33:56 |
2020/21 | 00:07:35 | 00:23:30 | 01:00:03 | 01:23:46 |
2021/22 | 00:10:20 | 1:01:57 | 02:44:01 | 02:53:39 |
2022/23 | 00:11:05 | 1:09:04 | 02:41:37 | 02:45:25 |
2023/24 (so far) | 00:09:27 | 00:40:40 | 01:46:15 | 02:02:26 |
The following table shows the National average ambulance response time since the introduction of the standards in August 2017.
Year | Category 1 mean | Category 2 mean | Category 3 mean | Category 4 mean |
2017/18 (August-March) | 00:08:23 | 00:25:51 | 01:04:36 | 01:30:32 |
2018/19 | 00:07:18 | 00:21:47 | 01:01:46 | 01:25:42 |
2019/20 | 00:07:18 | 00:23:50 | 01:11:04 | 01:26:09 |
2020/21 | 00:07:03 | 00:20:57 | 00:54:41 | 01:22:51 |
2021/22 | 00:08:39 | 00:41:18 | 02:13:39 | 03:07:10 |
2022/23 | 00:09:18 | 00:50:01 | 02:35:19 | 03:07:43 |
2023/24 (so far) | 00:08:25 | 00:34:25 | 01:57:07 | 02:24:33 |
Official data on accident and emergency waiting times is collected and published by NHS England including the number and proportion of patient attendances that meet the national four-hour accident and emergency access standard and is published monthly. The latest published data from NHS England shows that the Royal Cornwall NHS Trust achieved 78.5% of patient attendances within the four-hour standard in October 2023.
Some information on median waiting time data is collected by NHS England, however this remains experimental data subject to quality issues and is not intended for official performance monitoring use.
Spending on general practice (GP) services rose by just over a fifth in real terms between 2017/18 and the most recent data in 2021/22. More specifically it rose from £11.3 billion in 2017/18 to £13.5 billion in 2021/22, representing a 19% increase in real terms.
Payments to general practices are published by NHS Digital. The attached tables show the requested real-terms, per-patient GP funding figures from from 2014/15, which is the first year for which cilinical commissioning group summary figures are available; there is no data prior to 2013/14.
The tables summarise payments to GPs both in cash terms and adjusted for inflation. From 2020/21, payments are also made for primary care network-related activities. The final annual figures for inflation have been adjusted using the GDP deflator published by HM Treasury.
The figures attached are presented for payments per registered patient, as well as payments per weighted patient, where the weighting adjusts for differences in workload associated with age/sex, additional health needs, care home residents, list turnover, as well as areas costs and costs related to rurality. The figures include dispensing doctors related payments and the number of dispensing doctors in each area will therefore impact payment figures.
We have reported the health geography most closely fitting the request, with data availability changing over the years; for example, the data for 2022/23 is available at integrated care board (ICB) level but not at a sub-ICB level, while previous years’ data is available for NHS Kernow Clinical Commissioning Group.
The Scientific Advisory Group for Emergency’s (SAGE) subgroup, Scientific Pandemic Influenza Group on Modelling, Operational, do not have a single estimate for asymptomatic case proportions, infection hospitalisation rates, case hospitalisation rates, infection fatality rates, or case fatality rates. Individual modelling groups use their own estimates of these metrics, which are based on a wide range of data sources, including testing data, hospital admission, intensive care unit admissions, and deaths. Their models are regularly updated to fit to the observed transmission of the disease and further details are publicly available.
The Office for National Statistics COVID-19 Infection Study has estimated that approximately 55% of those individuals who test positive do not record evidence of symptoms at or around the time of the test. This does not mean these individuals will not go on to develop symptoms or had symptoms previously.
Other SAGE evidence has shown that there is wide variation in the estimated proportion of infections that are truly asymptomatic across different studies with the rapid review providing a pooled estimate, based on 22 studies, of 28% but with very wide confidence intervals.
NHS England use data from their daily COVID-19 situation report collection from individual hospital trusts to estimate current average length of stay and the proportion who require mechanical ventilation. In the run up to the national restrictions this gave an average length of stay of 7.7 days, of which 5.5% of those would be with mechanical ventilation.
The decision to re-introduce greater restrictions from 5 November until 2 December 2020 was based on a wide range of data, not just modelling estimates. These included analysis from the National Health Service on hospital capacity, the rapidly rising hospital admissions, and deaths, and the similar second waves seen across Europe.
SAGE papers from its meetings are published in an online only format on GOV.UK.
The Scientific Advisory Group for Emergency (SAGE) is responsible for ensuring that timely and coordinated scientific advice is made available to support decisions by the Government. The SAGE subgroup, Scientific Pandemic Influenza Group on Modelling, Operational use their own estimates of metrics such as asymptomatic case proportions, infection hospitalisation rates, or infection fatality rates. These are based on a wide range of available data sources, including testing data, hospital admission, intensive care unit admissions, and deaths. Their models are regularly updated to fit to the observed transmission of the disease.
In the reasonable worst-case planning scenario from late March, SAGE’s best estimate of the infection fatality ratio was approximately 1%, however this was highly age-dependent. Precise estimates of the case fatality ratio – the proportion of people with clinical symptoms who die – are much harder, as the proportion of cases who are asymptomatic is difficult to estimate. Due to the difficulty with ascertaining the proportion of infections that are truly asymptomatic, modelling is based on estimates of the total number of infections in a population. At the time, the best estimate of the proportion of cases that were asymptomatic was 33%.
Estimates of mortality rates for those hospitalised were around 12%. However, again this was highly age-dependent, with 50% mortality in those hospitalised who require invasive ventilation.
SAGE’s estimate of the proportion of infections that required hospitalisation was 5% overall, but that this was also highly dependent on age. This reasonable worse-case planning scenario used an estimate for the number of patients requiring ventilation, mechanical or otherwise, of 30%. A copy of the SAGE paper Reasonable Worst-Case Planning Scenario – 29/03/2020 is attached.
The Scientific Advisory Group for Emergency (SAGE) is responsible for ensuring that timely and coordinated scientific advice is made available to support decisions by the Government. The SAGE subgroup, Scientific Pandemic Influenza Group on Modelling, Operational use their own estimates of metrics such as asymptomatic case proportions, infection hospitalisation rates, or infection fatality rates. These are based on a wide range of available data sources, including testing data, hospital admission, intensive care unit admissions, and deaths. Their models are regularly updated to fit to the observed transmission of the disease.
In the reasonable worst-case planning scenario from late March, SAGE’s best estimate of the infection fatality ratio was approximately 1%, however this was highly age-dependent. Precise estimates of the case fatality ratio – the proportion of people with clinical symptoms who die – are much harder, as the proportion of cases who are asymptomatic is difficult to estimate. Due to the difficulty with ascertaining the proportion of infections that are truly asymptomatic, modelling is based on estimates of the total number of infections in a population. At the time, the best estimate of the proportion of cases that were asymptomatic was 33%.
Estimates of mortality rates for those hospitalised were around 12%. However, again this was highly age-dependent, with 50% mortality in those hospitalised who require invasive ventilation.
SAGE’s estimate of the proportion of infections that required hospitalisation was 5% overall, but that this was also highly dependent on age. This reasonable worse-case planning scenario used an estimate for the number of patients requiring ventilation, mechanical or otherwise, of 30%. A copy of the SAGE paper Reasonable Worst-Case Planning Scenario – 29/03/2020 is attached.
The Scientific Advisory Group for Emergency’s (SAGE) subgroup, Scientific Pandemic Influenza Group on Modelling, Operational, do not have a single estimate for asymptomatic case proportions, infection hospitalisation rates, case hospitalisation rates, infection fatality rates, or case fatality rates. Individual modelling groups use their own estimates of these metrics, which are based on a wide range of data sources, including testing data, hospital admission, intensive care unit admissions, and deaths. Their models are regularly updated to fit to the observed transmission of the disease and further details are publicly available.
The Office for National Statistics COVID-19 Infection Study has estimated that approximately 55% of those individuals who test positive do not record evidence of symptoms at or around the time of the test. This does not mean these individuals will not go on to develop symptoms or had symptoms previously.
Other SAGE evidence has shown that there is wide variation in the estimated proportion of infections that are truly asymptomatic across different studies with the rapid review providing a pooled estimate, based on 22 studies, of 28% but with very wide confidence intervals.
NHS England use data from their daily COVID-19 situation report collection from individual hospital trusts to estimate current average length of stay and the proportion who require mechanical ventilation. In the run up to the national restrictions this gave an average length of stay of 7.7 days, of which 5.5% of those would be with mechanical ventilation.
The decision to re-introduce greater restrictions from 5 November until 2 December 2020 was based on a wide range of data, not just modelling estimates. These included analysis from the National Health Service on hospital capacity, the rapidly rising hospital admissions, and deaths, and the similar second waves seen across Europe.
SAGE papers from its meetings are published in an online only format on GOV.UK.
The Scientific Advisory Group for Emergency (SAGE) is responsible for ensuring that timely and coordinated scientific advice is made available to support decisions by the Government. The SAGE subgroup, Scientific Pandemic Influenza Group on Modelling, Operational use their own estimates of metrics such as asymptomatic case proportions, infection hospitalisation rates, or infection fatality rates. These are based on a wide range of available data sources, including testing data, hospital admission, intensive care unit admissions, and deaths. Their models are regularly updated to fit to the observed transmission of the disease.
In the reasonable worst-case planning scenario from late March, SAGE’s best estimate of the infection fatality ratio was approximately 1%, however this was highly age-dependent. Precise estimates of the case fatality ratio – the proportion of people with clinical symptoms who die – are much harder, as the proportion of cases who are asymptomatic is difficult to estimate. Due to the difficulty with ascertaining the proportion of infections that are truly asymptomatic, modelling is based on estimates of the total number of infections in a population. At the time, the best estimate of the proportion of cases that were asymptomatic was 33%.
Estimates of mortality rates for those hospitalised were around 12%. However, again this was highly age-dependent, with 50% mortality in those hospitalised who require invasive ventilation.
SAGE’s estimate of the proportion of infections that required hospitalisation was 5% overall, but that this was also highly dependent on age. This reasonable worse-case planning scenario used an estimate for the number of patients requiring ventilation, mechanical or otherwise, of 30%. A copy of the SAGE paper Reasonable Worst-Case Planning Scenario – 29/03/2020 is attached.
The Scientific Advisory Group for Emergency’s (SAGE) subgroup, Scientific Pandemic Influenza Group on Modelling, Operational, do not have a single estimate for asymptomatic case proportions, infection hospitalisation rates, case hospitalisation rates, infection fatality rates, or case fatality rates. Individual modelling groups use their own estimates of these metrics, which are based on a wide range of data sources, including testing data, hospital admission, intensive care unit admissions, and deaths. Their models are regularly updated to fit to the observed transmission of the disease and further details are publicly available.
The Office for National Statistics COVID-19 Infection Study has estimated that approximately 55% of those individuals who test positive do not record evidence of symptoms at or around the time of the test. This does not mean these individuals will not go on to develop symptoms or had symptoms previously.
Other SAGE evidence has shown that there is wide variation in the estimated proportion of infections that are truly asymptomatic across different studies with the rapid review providing a pooled estimate, based on 22 studies, of 28% but with very wide confidence intervals.
NHS England use data from their daily COVID-19 situation report collection from individual hospital trusts to estimate current average length of stay and the proportion who require mechanical ventilation. In the run up to the national restrictions this gave an average length of stay of 7.7 days, of which 5.5% of those would be with mechanical ventilation.
The decision to re-introduce greater restrictions from 5 November until 2 December 2020 was based on a wide range of data, not just modelling estimates. These included analysis from the National Health Service on hospital capacity, the rapidly rising hospital admissions, and deaths, and the similar second waves seen across Europe.
SAGE papers from its meetings are published in an online only format on GOV.UK.
The Scientific Advisory Group for Emergency (SAGE) is responsible for ensuring that timely and coordinated scientific advice is made available to support decisions by the Government. The SAGE subgroup, Scientific Pandemic Influenza Group on Modelling, Operational use their own estimates of metrics such as asymptomatic case proportions, infection hospitalisation rates, or infection fatality rates. These are based on a wide range of available data sources, including testing data, hospital admission, intensive care unit admissions, and deaths. Their models are regularly updated to fit to the observed transmission of the disease.
In the reasonable worst-case planning scenario from late March, SAGE’s best estimate of the infection fatality ratio was approximately 1%, however this was highly age-dependent. Precise estimates of the case fatality ratio – the proportion of people with clinical symptoms who die – are much harder, as the proportion of cases who are asymptomatic is difficult to estimate. Due to the difficulty with ascertaining the proportion of infections that are truly asymptomatic, modelling is based on estimates of the total number of infections in a population. At the time, the best estimate of the proportion of cases that were asymptomatic was 33%.
Estimates of mortality rates for those hospitalised were around 12%. However, again this was highly age-dependent, with 50% mortality in those hospitalised who require invasive ventilation.
SAGE’s estimate of the proportion of infections that required hospitalisation was 5% overall, but that this was also highly dependent on age. This reasonable worse-case planning scenario used an estimate for the number of patients requiring ventilation, mechanical or otherwise, of 30%. A copy of the SAGE paper Reasonable Worst-Case Planning Scenario – 29/03/2020 is attached.
The Home Office collects and publishes data on fixed penalty notices (FPNs) and other outcomes for motoring offences in England and Wales on an annual basis. The most recent data, up to 2021, is available here:
https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/1118166/fixed-penalty-notices-and-other-motoring-offences-statistics-police-powers-and-procedures-year-ending-31-december-2021.ods
Table 1 below shows the number of speeding offences recorded by police between 2011 and 2021, and how many resulted in a fine being paid.
Table 1 Number of speeding offences recorded by police in England and Wales, and how many resulted in a fine being paid, 2011 to 2021
Calendar Year | Number of speeding offences | ..of which a fine was paid |
2011 | 1,494,183 | 705,444 |
2012 | 1,590,384 | 731,329 |
2013 | 1,659,846 | 722,503 |
2014 | 1,863,317 | 745,576 |
2015 | 1,944,978 | 787,092 |
2016 | 1,970,207 | 784,654 |
2017 | 2,013,830 | 778,486 |
2018 | 2,101,647 | 807,273 |
2019 | 2,253,948 | 820,308 |
2020 | 2,006,382 | 758,418 |
2021 | 2,378,373 | 853,811 |
Excludes ‘cancelled’ and ‘incomplete’ offences.
These figures may be an underestimation, as Durham, North Wales, South Wales, Gwent, North Yorkshire, Nottinghamshire and Derbyshire forces do not record all outcomes on the PentiP system.
Equivalent information for years prior to 2011 is not available.
The Home Office collects and publishes data on fixed penalty notices (FPNs) and other outcomes for motoring offences, including speed limit offences, in England and Wales on an annual basis. The most recent data, up to 2021, is available here: https://assets.publishing.service.gov.uk/government/uploads/system/uploads/attachment_data/file/1118166/fixed-penalty-notices-and-other-motoring-offences-statistics-police-powers-and-procedures-year-ending-31-december-2021.ods
These statistics include the number of speed limit offences recorded by police forces in England and Wales and the subsequent outcomes, such as whether a fine was paid or a driver retraining course was attended.
However, the Home Office does not centrally collect data on mile-per-hour excess over the speed limit, or any information regarding the speed of the vehicle, for speeding penalties issued.
HM Passport Office is unable to provide the information requested as it is not held in a reportable format.
The information requested could not be obtained without disproportionate cost.
An Impact Assessment for the Leasehold and Freehold Reform Bill was published on 11 December 2023 and is available on the Parliament website at: Leasehold and Freehold Reform Bill publications - Parliamentary Bills - UK Parliament. The Impact Assessment considers the non-monetised impact of increasing the non-residential for collective enfranchisement claims including the potential impact on freeholders, high streets, and businesses.
An Impact Assessment for the Leasehold and Freehold Reform Bill was published on 11 December 2023 and is available on the Parliament website at: Leasehold and Freehold Reform Bill publications - Parliamentary Bills - UK Parliament. The Impact Assessment considers the non-monetised impact of increasing the non-residential for collective enfranchisement claims including the potential impact on freeholders, high streets, and businesses.
An Impact Assessment for the Leasehold and Freehold Reform Bill was published on 11 December 2023 and is available on the Parliament website at: Leasehold and Freehold Reform Bill publications - Parliamentary Bills - UK Parliament. The Impact Assessment considers the non-monetised impact of increasing the non-residential for collective enfranchisement claims including the potential impact on freeholders, high streets, and businesses.
An Impact Assessment for the Leasehold and Freehold Reform Bill was published on 11 December 2023 and is available on the Parliament website (attached) at: Leasehold and Freehold ReformBill publications - Parliamentary Bills - UK Parliament. This includes an estimate of the impact of removing marriage value on different groups and regions.
An Impact Assessment for the Leasehold and Freehold Reform Bill was published on 11 December 2023 and is available on the Parliament website (attached) at: Leasehold and Freehold ReformBill publications - Parliamentary Bills - UK Parliament. This includes an estimate of the impact of removing marriage value on different groups and regions.
The last time the provisions of the New Towns Act 1946 were used in England was in 1964 with the designation of Washington, Tyne and Wear New Town. The New Towns Act 1946 was subsequently consolidated into the New Towns Act 1965 and the Central Lancashire New Town in 1970 was the last new town in England designated under that Act. There have been no new towns designated in England since then.
Well planned, well-designed, locally led garden communities will play a vital role in helping to meet this country’s housing need well into the future, providing a pipeline of new homes. We are supporting 47 locally led Garden Community projects across the country, with the capacity to deliver around 300,000 homes by 2050.
The department publishes an annual release entitled ‘Housing supply: net additional dwellings, England’, which is the primary and most comprehensive measure of housing supply, with estimates of new homes delivered, in each financial year shown in Table 1 below.
Table 1. Housing Supply Net Additional Dwellings, England, 2004-05 to 2021-221.
2004-05 | 185553 |
2005-06 | 202653 |
2006-07 | 214936 |
2007-08 | 223534 |
2008-09 | 182767 |
2009-10 | 144870 |
2010-11 | 137394 |
2011-12 | 134896 |
2012-13 | 124722 |
2013-14 | 136605 |
2014-15 | 170693 |
2015-16 | 189645 |
2016-17 | 217345 |
2017-18 | 222281 |
2018-19 | 241877 |
2019-20 | 242702 |
2020-21 | 211865 |
2021-22 | 232816 |
Source: Live Table 122,123 https://www.gov.uk/government/statistical-data-sets/live-tables-on-net-supply-of-housing
1 Net additional dwellings includes new builds but also dwellings supplied through conversions of existing buildings, change of existing buildings use, other gains/losses, offset by demolitions. The detail, with each component, is published in Live Table 123.
Estimates of the number of new homes delivered, broken down by flats or houses, are not centrally collected.
Estimates of the proportion of building control reported new build dwelling completions by flats or houses for England, in each financial year, are shown in Table 2 below. These cover new build dwellings only and should be regarded as a leading indicator of overall housing supply.
Table 2. Housebuilding: Percentage of permanent dwellings completed, by house and flats, England, 2004-05 to 2021-222.
| House | Flats |
2004-05 | 59 | 41 |
2005-06 | 54 | 46 |
2006-07 | 53 | 47 |
2007-08 | 52 | 48 |
2008-09 | 50 | 50 |
2009-10 | 55 | 45 |
2010-11 | 65 | 35 |
2011-12 | 64 | 36 |
2012-13 | 67 | 33 |
2013-14 | 71 | 29 |
2014-15 | 75 | 25 |
2015-16 | 77 | 23 |
2016-17 | 75 | 25 |
2017-18 | 77 | 23 |
2018-19 | 78 | 22 |
2019-20 | 80 | 20 |
2020-21 | 81 | 19 |
2021-22 | 83 | 17 |
2022-23 | 82 | 18 |
Source: Live Table 254 https://www.gov.uk/government/statistical-data-sets/live-tables-on-house-building
2. Approximately half of the data used to produce the house building statistics are supplied by the National House-Building Council. These data contain additional detail on the size and type of new homes being completed and can be used to provide annual estimates of the proportion of new build dwellings that are houses as opposed to flats. The caveat is that these estimates are indicative only, as based on just 1 of the 3 sources of building control data (Local Authority Building Control, Independent Approved Inspectors and National House Building Council Data).
The department publishes an annual release entitled ‘Housing supply: net additional dwellings, England’, which is the primary and most comprehensive measure of housing supply, with estimates of new homes delivered, in each financial year shown in Table 1 below.
Table 1. Housing Supply Net Additional Dwellings, England, 2004-05 to 2021-221.
2004-05 | 185553 |
2005-06 | 202653 |
2006-07 | 214936 |
2007-08 | 223534 |
2008-09 | 182767 |
2009-10 | 144870 |
2010-11 | 137394 |
2011-12 | 134896 |
2012-13 | 124722 |
2013-14 | 136605 |
2014-15 | 170693 |
2015-16 | 189645 |
2016-17 | 217345 |
2017-18 | 222281 |
2018-19 | 241877 |
2019-20 | 242702 |
2020-21 | 211865 |
2021-22 | 232816 |
Source: Live Table 122,123 https://www.gov.uk/government/statistical-data-sets/live-tables-on-net-supply-of-housing
1 Net additional dwellings includes new builds but also dwellings supplied through conversions of existing buildings, change of existing buildings use, other gains/losses, offset by demolitions. The detail, with each component, is published in Live Table 123.
Estimates of the number of new homes delivered, broken down by flats or houses, are not centrally collected.
Estimates of the proportion of building control reported new build dwelling completions by flats or houses for England, in each financial year, are shown in Table 2 below. These cover new build dwellings only and should be regarded as a leading indicator of overall housing supply.
Table 2. Housebuilding: Percentage of permanent dwellings completed, by house and flats, England, 2004-05 to 2021-222.
| House | Flats |
2004-05 | 59 | 41 |
2005-06 | 54 | 46 |
2006-07 | 53 | 47 |
2007-08 | 52 | 48 |
2008-09 | 50 | 50 |
2009-10 | 55 | 45 |
2010-11 | 65 | 35 |
2011-12 | 64 | 36 |
2012-13 | 67 | 33 |
2013-14 | 71 | 29 |
2014-15 | 75 | 25 |
2015-16 | 77 | 23 |
2016-17 | 75 | 25 |
2017-18 | 77 | 23 |
2018-19 | 78 | 22 |
2019-20 | 80 | 20 |
2020-21 | 81 | 19 |
2021-22 | 83 | 17 |
2022-23 | 82 | 18 |
Source: Live Table 254 https://www.gov.uk/government/statistical-data-sets/live-tables-on-house-building
2. Approximately half of the data used to produce the house building statistics are supplied by the National House-Building Council. These data contain additional detail on the size and type of new homes being completed and can be used to provide annual estimates of the proportion of new build dwellings that are houses as opposed to flats. The caveat is that these estimates are indicative only, as based on just 1 of the 3 sources of building control data (Local Authority Building Control, Independent Approved Inspectors and National House Building Council Data).
The Building Regulations continue to set a performance-based approach. This means that our approach to achieving higher standards remains technology-neutral, to provide developers with the flexibility to choose the most appropriate and cost-effective solutions for their site.
We recently consulted on proposals for a new permitted development right which would enable the construction of solar canopies in ground-level off-street car parks in non-domestic settings without a planning application. Further announcements will be made in due course.