DEFRA PUBLIC SERVICE AGREEMENT TECHNICAL NOTE PSA 1 – Sustainable Development PSA target 1: "To promote sustainable development across Government and in the UK and internationally, as measured by: • • the achievement of positive trends in the Government’s headline indicators of sustainable development; the UK’s progress towards delivering the World Summit on Sustainable Development commitments, notably in the areas of sustainable consumption and production, chemicals, biodiversity, oceans, fisheries and agriculture; progress towards internationally agreed commitments to tackle climate change”. • Definition 1.1 Sustainable Development is about ensuring a better quality of life for everyone, now and for generations to come. It means meeting four broad objectives at the same time: • Social progress which recognises the needs of everyone; • Effective protection of the environment; • Prudent use of natural resources; and • Maintenance of high and stable levels of economic growth and employment. Methodology Domestic 1.2 In addition to its responsibilities for incorporating sustainable development into its own operations and policies, Defra has the lead role in promoting sustainable development across government and other sectors of society, by working with other stakeholders to review the 1999 UK Sustainable Development Strategy1, raising awareness and understanding of the principles and practices of sustainable development and promote the use of integrated policy appraisal tools. PSA1 covers promotion of sustainable development internationally as well as the UK. Work on domestic issues will be designed to enhance existing work streams and will also focus on engaging the key areas of government policy that have, or are likely to have, significant impacts 1.3 A better quality of life – A strategy for sustainable development in the UK, DETR, 1999. (www.sustainable-development.gov.uk/uk_strategy/content.htm) 1 on delivery of the sustainable development agenda, examples of which are policies relating to: • • • • Climate change and energy; Sustainable consumption, production and use of natural resources; Environment and social justice, and; Helping communities help themselves. 1.4 The measures necessary to take this forward and the criteria used to judge their success will be considered as part of the review of the UK Sustainable Development Strategy which is due to report in Spring 2005. A detailed delivery plan for the target will then be produced. Progress in promoting sustainable development will continue to be measured by achievement of positive trends in the Government’s headline indicators. A revised set of indicators will be produced as part of the review of the UK Sustainable Development Strategy that will be designed to relate closely to the important themes which will move forward the sustainable development agenda (highlighted above). However, the current set (set out below) will continue to provide a context for progress until the revised indicators can be fully implemented. We will keep this technical note updated as appropriate. 1.5 World Summit on Sustainable Development (WSSD) 1.6 Progress in meeting the commitments made by the Government at WSSD will require close collaboration between departments. However, specific commitments have been formally assigned to individual departments. Revised PSA 1 covers the six WSSD commitments on which Defra formally leads. Other Government Departments (DTI, DFID, FCO) own the commitments on which they lead. Measurement in the area of international sustainable development is extremely complex. There is no agreed methodology for assessing the UK’s impacts on sustainable development overseas. Although a certain amount of information on global trends is collected by, for example, the UN Development Programme and UN Environment Programme, it is difficult to obtain reliable quantitative data in many of the WSSD policy areas. Where data is available, indicators tend to measure long-term changes, and are rarely able to show the impact of UK policy within the period between spending reviews. Any success measures will therefore need to be indicators of direction of travel overall. In many cases, success measurements are likely to be more process based. A number of the WSSD commitments, either directly or indirectly, are linked to the targeted introduction of policies and measures, e.g. marine protected areas or an internationally agreed system to measure biodiversity loss. These are proxies for real world changes but nonetheless reflect agreement on necessary policy 1.7 1.8 1.9 changes and implementation. It is right, therefore, to also see success in terms of influencing or carrying about such changes. 1.10 The current international indicators in the UK Sustainable Development Strategy – in conjunction with Defra’s six interim WSSD delivery plans – will be used as contextual indicators for measuring aspects of the overall movement towards more sustainable international development, although they are not sufficient in coverage or responsiveness to be used to measure Defra’s own contribution to that progress. The consultation on, and subsequent elaboration of, the new UK Sustainable Development Strategy may result in some new improved indicators that could provide a basis of our international monitoring. Securing International Climate Change commitments 1.11 The Government's activities on international climate change have long benefited from close collaboration between departments. While Defra formally leads, other Government Departments, particularly DTI, DFID, and FCO, play a vital role in delivering the Government's objectives. As with international sustainable development, measurement of progress on international climate change is very complex, particularly during the current phase, in which the majority of countries have no specific commitments to action. Long term, the climate change problem will need to be solved through a much broader (in terms of countries included) and deeper (in terms of commitment to action) framework that focuses on the ultimate objective of stabilising greenhouse gases at safe levels. Our objective as a global leader in the field is therefore to secure greater commitment from our European neighbours and other developed countries, and to draw in the most significant greenhouse gas emitters from the developing world, though not necessarily to bind them into the same sort of action as developed countries will be committed to. A significant step along the way will be to ensure that the EU is able to show demonstrable progress towards its Kyoto Protocol commitments by the end of 2005. We will have been successful if, by December 2005: • • the EU has shown that it has made demonstrable progress towards its Kyoto commitments; negotiations on a framework for international action on climate change after 2012 have begun; 1.12 1.13 and we have negotiated a framework by 2008, that: • • • has buy in from the United States; secures binding commitments for emissions reductions by industrialised countries consistent with putting the world on a path to a 60% cut in greenhouse gas emissions by 2050; secures the engagement of key developing countries in actions to avoid or limit greenhouse gases. A separate Technical Note detailing PSA1 measurement can be found at http://www.defra.gov.uk/corporate/busplan/tnpsa1-2005.pdf PSA 2 – Climate Change and Energy PSA Target 2: “To reduce greenhouse gas emissions by 12.5% from 1990 levels in line with our Kyoto commitment and move towards a 20% reduction in carbon dioxide emissions below 1990 levels by 2010, through measures including energy efficiency and renewables (joint with DTI and DfT)” Greenhouse Gas Emissions Data 2.1 The National Environmental Technology Centre (NETCEN) publishes an annual inventory on behalf of Defra of the UK’s historic greenhouse gas emissions usually within 15 months of the end of the calendar year in question. Data is available on an annual basis back to 19902. Provisional data on carbon dioxide emissions are estimated from energy data and published annually by DTI in Energy Trends3 in the March following the end of the calendar year in question. 2.2 Quality Controls 2.3 2 3 Data will be subject to the requirements of National Statistics. See http://www.airquality.co.uk/archive/reports/cat07/aeat-env-r-1702.doc See http://www.dti.gov.uk/energy/inform/energy_trends/index.shtml Definitions 2.4 The UK’s target under the Kyoto Protocol is to reduce its greenhouse gas emissions (carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O), hydrofluorocarbons (HFCs), perfluorocarbons (PFCs), and sulphur hexafluoride (SF6)) to 12.5% below 1990 levels by 2008-12 (for the purposes of this PSA target, emissions will be calculated as an average over these five years). The baseline for the UK’s greenhouse gas emissions is 1990 although, as allowed by the Kyoto Protocol, 1995 is used for emissions of hydrofluorocarbons, perfluorocarbons and sulphur hexafluoride. The Government has a domestic goal to reduce emissions of CO2 by 20% from 1990 levels by 2010. The UK Climate Change Programme4, which sets out how the UK will meet its Kyoto target and move towards the domestic goal, will be reviewed in 2004. The Government has also accepted, in the Energy White Paper published in February 2003, the Royal Commission on Environmental Pollution’s recommendation that the UK should put itself on a path to a reduction in carbon dioxide emissions of some 60% from current levels by about 2050. 2.5 2.6 Timing 2.7 Data on greenhouse gas emissions are available annually with lags of just over a year. Territorial Scope 2.8 Emissions data relate to the UK. Success Criteria 2.9 UK greenhouse gas emissions should be below the level of the Kyoto target, and thus the UK should be moving towards the goal of a 20% reduction in carbon dioxide emissions below 1990 levels by 2010, by 2008. In addition, that we have, by 2008, put the UK on a path to cut carbon dioxide emissions by some 60% by about 2050, with real progress by 2020. 2.10 Energy Efficiency Data 2.11 Energy intensity has traditionally been used as a proxy for energy efficiency. However, intensity changes include changes in energy service demand or to structural changes in business. Defra is 4 See http://www.defra.gov.uk/environment/climatechange/cm4913/index.htm undertaking work to develop improved indicators for energy efficiency to take account of these changes. The available data will continue to be published annually in indicators to support the Energy White Paper annual report. Quality Controls 2.12 Data will be subject to the requirements of National Statistics. Definitions 2.13 Energy efficiency improvements are calculated for individual technical measures, and the overall improvement for a sector such as Households is the sum of the improvements for all of the installations of each of the measures. Timing 2.14 Energy efficiency data are available annually with a lag of about a year. Territorial Scope 2.15 Carbon savings from energy efficiency are for the UK. Success Criteria 2.16 The Government set out in the Energy Efficiency Action Plan a formal aim to achieve savings of 4.2MtC per annum by 2010 (3.5 MtC for England) through energy efficiency in the household sector, in fulfilment of the requirements of the Sustainable Energy Act 2003. The Action Plan also projected savings of 7.9 MtC from business and the public sector, giving total savings of 12.1 MtC. Renewable Energy Data 2.17 Data on the supply of electricity from renewable sources is available annually in the Digest of UK Energy Statistics5. Quality Controls 2.18 Data will be subject to the requirements of National Statistics. Definitions 2.19 Renewable energy is defined here as all sources of renewable energy that are eligible for the Renewables Obligation (RO) in England and Wales and the analogous Renewables (Scotland) Obligation. This includes solar power, wind, hydropower, wave and tide, geothermal, 5 See http://www.dti.gov.uk/energy/inform/energy_stats/renewables/index.shtml biomass, landfill gas, sewage treatment plant gas and biogases. Specific exclusions from eligibility for the RO include existing hydro plant over 20 MW; all plant using renewable sources built before 1990 (unless re-furbished); and energy from mixed waste combustion unless the waste is first converted to fuel using advanced conversion technology. Only the biodegradable fraction of any waste is eligible. Timing 2.20 Data on renewable energy supplies are available annually with a lag of about 6 months. Carbon savings from renewable energy supplies are for the UK. The percentage of electricity supplies from renewable energy is also for the UK. 2.21 Success Criteria 2.22 We are on course for renewable energy to supply 10% of the UK’s electricity needs by 2010. PSA 3 –Birds/SSSIs PSA target 3 (i): “Care for our natural heritage, make the countryside attractive and enjoyable for all, and preserve biological diversity by … reversing the long-term decline in the number of farmland birds by 2020, as measured annually against underlying trends” Scope 3.1 In previous years the target has been based on data from the Common Bird Census for the whole of the UK. Because the data are now derived form the more statistically powerful Breeding Bird Survey, the target can now be based on BBS data for England only. Since Defra’s policies relate to England, this makes the PSA a more relevant measure of Defra performance. Methodology and measurement 3.2 Twenty species of birds were originally identified as being representative of the overall population of farmland birds. The selected species were approved by the Joint Nature Conservation Committee (JNCC) and the Royal Society for the Protection of Birds (RSPB), and are a mixture of farmland specialists and farmland generalists. The data used to calculate the long-term trend in farmland bird populations are taken from the Breeding Bird Survey, carried out by the British Trust for Ornithology (BTO), the JNCC and the RSPB. This survey has now replaced the Common Bird Census, on which the indicator was previously based. The index of farmland bird populations 3.3 is calculated annually on the breeding populations of 18 species. (This excluded two of the original twenty species, Rook and Barn Owl, because they are not counted every year and trends had previously been extrapolated). 3.4 Research completed in 2001 by the BTO and RSPB produced an agreed methodology to measure the annual underlying trend in populations (see Annex A). The methodology enables the production of a smoothed indicator showing the long-term trend by combining the 18 individual species’ indices. In this way the effects of any short-term fluctuations due to the weather or special factors affecting one or two species are reduced. The PSA target will have been achieved when the long-term trend in the index and the associated upper and lower confidence limits (using a 95% confidence interval) are all positive. The data series from the Common Bird Census began in the 1960s and its last year was 2000. The Breeding Bird Survey began in 1994 and overlapped with the CBC until 2000 but is now the only survey. Detailed work was carried out (see Annex A) on the statistical techniques for combining data across the two surveys in order to ensure continuity and check that the resulting index was not significantly different. Further work was also done to check that the indicator based only on English data was not significantly different from the one based on all UK data. As this was shown to be the case, the decision was taken to switch to an England basis from the current report onwards. 3.5 3.6 3.7 PSA target 3 (ii): “Care for our natural heritage, make the countryside attractive and enjoyable for all and preserve biological diversity by…bringing into favourable condition by 2010 95 per cent of all nationally important wildlife sites” Scope 3.8 Monitoring will be for England only and will be carried out by English Nature. Monitoring is governed by common standards (agreed at UK level through the Joint Nature Conservation Committee (JNCC)) and is carried out in England by English Nature staff. Further detailed standards for assessing the condition of individual habitats and species are being prepared through the JNCC, drawing upon the work of the national conservation agencies. Notified features are assessed at least once every six years (on a rolling programme) and more frequently where sites are perceived to be more vulnerable. English Nature completed the first assessment of 3.9 3.10 all Sites of Special Scientific Interest (SSSI) land in March 2003, and published a comprehensive report on the results from this assessment in December 2003 England’s best wildlife and geological sites- the condition of Sites of Special Scientific Interest. 3.11 Through the English Nature Site Information System (ENSIS), English Nature collates information on the condition of the notified biological and geological features that constitute the special interest of the SSSIs. National summaries are reported on annually through English Nature's Annual report which can be ordered or viewed at: http//www.englishnature.org.uk. The latest overall position is also reported on English Nature’s website and updated regularly, along with information by site and at the regional level. 3.12 Definitions 3.13 ‘Nationally important wildlife site’ – means land which is notified as a Site of Special Scientific Interest under section 28 of the Wildlife and Countryside Act 1981 (as amended by the Countryside and Rights of Way Act 2000). ‘Favourable condition’ - means that the features for which SSSIs are notified are in satisfactory condition; or are recovering, with the necessary management measures in place, such that English Nature predicts, using expert judgement, that the land will reach favourable condition. The target comprises the sum of the JNCC Common Standards conditions ‘Favourable maintained’, ‘Favourable recovered’ and ‘Unfavourable recovering’. ‘95%’ – means 95% of SSSI land, measured by area. The total area of SSSI land in England is 1,055,390 hectares. This target is linked to Core indicator S6 of sustainable development: Extent and management of Sites of Special Scientific Interest. 3.14 3.15 3.16 PSA 4 – Rural Productivity/Services PSA 4 (Productivity): “Reduce the gap in productivity between the least well performing quartile of rural areas and the English median by 2008, demonstrating progress by 2006” 4.1 Productivity is a measure of economic success. Used in the rural context of this Public Service Agreement, it is a means to gauge whether economic conditions in rural areas with relatively poor economic performance are improving. In technical terms, the objective is to reduce the gap in productivity between the least well performing quartile of rural areas and the 4.2 English median. This objective will be met if the absolute gap between the growth rate of the indicator districts and the growth rate of the English median is reduced or if the growth rate on the indicators districts is greater than that for the English median, as demonstrated by the trend up to 2008. Section 1: The Measure of Productivity. Productivity is typically measured using value added by the workforce, expressed as Gross Value Added. This can be described in aggregate (i.e. for all workers per region or nationally) or in various permutations such as per hour worked or per worker. A complete measure of rural productivity has to take into account employment levels because the productivity of an area will be influenced by the level of unemployment or under employment. Gross Value Added as a measure is only available down to NUTS 3 level (this EU classification broadly equates to an English county). This is too large to effectively describe rural productivity differences. A close proxy is currently unavailable below district level so a district level proxy measure is applied as follows: (1) the aggregate earnings of taxpayers of working age divided by (2) the number of people of working age who are either economically active or economically inactive and not in education The intention was to establish a baseline using the average for both 1999/2000 and 2000/2001. However, the 1999/2000 earnings data have been withdrawn by the Inland Revenue following the identification of errors. The current baseline therefore uses only 2000/2001 data. The average for 1999/2000 and 2000/2001 will be used once the revised 1999/2000 figures are released. The districts used to measure performance in the bottom quartile are listed in Annex B. These indicator districts are selected from those with a predominantly rural population. The list of indicator districts will be reviewed in 2005 in the light of the new rural definition (see below) and its application to relevant data sets (3). The average productivity of the indicator districts is calculated by weighting the productivity figure for each district by the population in that district. The weights are based on the number of people of working age (4) in rural output areas (5) in each district. The median is calculated for all districts in England. The target will be met if the absolute gap between the growth rate of the indicator districts and the growth rate of the English median is reduced or the growth rate in indicator districts is greater than that for the English median, as demonstrated by the trend in productivity, as defined above, up to 2008. Section 2: Data (1). Aggregate earnings of taxpayers of working age. This comes from the Inland Revenue Survey of Personal Sources and Incomes. It is measured over the tax year, includes Definitions. earnings of employees and the self-employed and is based on the district of residence for tax purposes. It excludes members of the armed forces. (2). The number of people of working age who are either economically active or economically inactive and not in education. This comes from the Office for National Statistics Annual Local Area Labour Force Survey. Interviews are conducted over the period March to February. Students are recorded at their vacation address. Members of their foreign armed forces are included if they live off-base and stay in the country for at least six months. (3). Ideally the measure would be based on people living in just the rural parts of particular areas, so that those in the rural parts of predominantly urban areas do not fall out of scope. We are investigating the possibility of producing such figures – but at present data is unavailable below district level. In their absence, it has been necessary to use district level information. The indicator districts were therefore selected from those whose productivity estimate is determined by a predominantly rural population. This helps to avoid situations where low district productivity hides a relatively productive rural population and conversely where higher overall district productivity hides less productive rural communities, and where change in district productivity does not reflect change in rural productivity. The indicator districts were selected from those districts where at least 50% of the population live outside settlements with a population of 25,000 or more and where at least 25% of the population live outside settlements with a population of 10,000 or more. These percentages were estimated using the 1991 ODPM urban settlement boundaries, the associated 1991 Census population figures and the 1991 district population figures. The implication is that the selected indicator districts are not an exclusive identification of low rural productivity nor are they intended to be a sole focus for action to raise rural productivity. (4). Output Area working age population. This comes from the 2001 Population Census. (5). Rural Output Areas. These are from the provisional new National Statistics urban/rural definition. Section 3. Data (1) Inland Revenue Survey of Personal Incomes: data is available free of charge on request to the Inland Revenue Availability approximately 18 months after the end of the tax year. That is, data for the 2002/03 tax year are expected to be available in October 2004. (2). Office for National Statistics Labour Force Survey: data is available from the Office for National Statistics Labour Market Enquiries Service approximately eight months after the year in question (e.g. figures for 2003/04 are expected to be available in October 2004). (3). The 1991 urban settlement boundaries and population data are available from ODPM. The 1991 Census district populations are available free of charge from the Office for National Statistics. (4). Output Area working age population: data is available free of charge from the ONS Census Customer Services (http://www.statistics.gov.uk/census2001/customerservices. asp) (5). Rural Output Area classification. This will shortly be available from http://www.statistics.gov.uk/geography and further information can be found at http://www.ruralurban.org.uk). Productivity figures for 2001/2 are expected to become available in June 2004, with 2002/3 data expected in October 2004. England Section 4:Time Period of Measurement Section 5: Territorial scope Section 6: Validation Arrangements There are two stages to the validation process: 1. The data providers undertake validation of source data. 2. Validation of the selected indicator districts listed in Annex B: a. These were checked for instances where low district productivity hid a relatively productive rural population. b. Conversely, a check was made to control for instances where a poor performing district was excluded because it was hidden by better performing urban areas. Checks a & b also offer some control against the misselection of indicator districts due sampling or estimation error in the productivity measure. The data used consist of ward-level data on incomes and employment. Rural wards were those used under the Countryside Agency definition. Section 7: Data We want to use productivity indicators that are based on people living in just the rural parts of particular areas. We Development are investigating the possibility of producing such estimates with the Inland Revenue and ONS. We also plan to discuss the possibility of producing a better proxy for rural productivity with the ONS. This, along with the new urban/rural definition, will inform the review of indicator areas for 2005. Whilst the measure described in this Technical Note will be used to assess progress, we are also working with stakeholders to establish a set of complementary indicators that permit more comprehensive analysis and reporting on delivery, for example in relation to business performance and workforce qualifications. PSA 4 – Access to Services: “Improve the accessibility of services for people in England’s rural areas…” Indicators 4.3 Defra does not deliver rural services. Our action on this PSA thus contains a range of activities aimed at influencing the delivery of rural services by others. Because Defra does not deliver services itself, work on this PSA is inevitably focused on processes. However it is important to have an over-arching indicator which will measure the long term success of Defra’s influence in terms of outcomes for people living in rural areas. The proposed indicator is that the improvement achieved in the delivery of selected services should be as good in rural areas as it is in urban areas, except for indicator 7 on accessibility where a rural- 4.4 4.5 urban comparison is not appropriate for accessibility. We will judge our influence to have been successful if the indicators listed have risen for rural areas by April 2008. What combination of the 11 accessibility indicators will have to have risen for this to be considered a success will be a matter of judgement. 4.6 Our target is that this indicator is achieved in at least 7 of the 9 selected services. 4.7 The 9 PSAs included in this basket for our PSA indicator are chosen from the group of ‘shared priorities’ 6. 4.8 It should be emphasised that these are not the only PSAs important to rural people. Our aim is to influence all service delivery in rural areas. PSA target wording The improvement achieved in the delivery of selected services should be as good in rural areas as it is in urban areas How will the target be judged as met, partly met, or not Success Criteria met? It will be met if Defra succeeds in influencing the relevant departments to achieve the target in at least 7 out of the 9 service areas identified. What indicators will be used to make this judgement? 1. Mental health. Access to (i) crisis services and (ii) child and adolescent mental health services. 2. Drug rehabilitation and treatment. (i) Participation of problem drug users in drug treatment programmes. (ii) Proportion of users successfully sustaining or completing treatment programmes. 3. Children’s services. Increase in the stock of Ofsted recognised childcare places. 4. NEETs. Proportion of young people not in education, employment or training. 5. Employment rates of disadvantaged groups. Combined employment rate of (i) lone parents, (ii) minority ethnic groups, (iii) people aged between 50 and state retirement age, (iv) least qualified members of the working age population and (v) those living in the wards with the poorest initial labour market position. 6. Pensions. Number of (i) pensioner households being paid Pension Credit and (ii) disadvantaged pensioner households in receipt of the Guarantee Credit. 7. Accessibility. priorities for action which Defra shares with other Government departments which are specially important for rural people. We work with the Department concerned to agree what action is needed by that department and by Defra to ensure they are well delivered in rural areas. 6 • % of a) pupils of compulsory school age ; b) pupils of compulsory school age in receipt of free school meals within 15 and 30 minutes of a primary school and 20 and 40 minutes of a secondary school by public transport % of 16-19 year olds within 30 and 60 minutes of a further education establishment by public transport % of a) people of working age; b) people in receipt of Jobseekers' allowance within 20 and 40 minutes of work by public transport % of a) households b) households without access to a car within 30 and 60 minutes of a hospital with an outpatients' facility by public transport % of a) households b) households without access to a car within 15 and 30 minutes of a GP by public transport % of a) households; b) households without access to a car within 15 and 30 minutes of a major centre by public transport • • • • • 8. Road traffic accidents. (i) Number of people killed or seriously injured in road accidents. (ii) Number of children killed or seriously injured in road accidents. 9. Affordable housing. Ratio of lower quartile house prices to lower quartile earnings. What level of change (e.g. %) needs to be observed by which date? The percentage improvement in rural areas in England should not be statistically significantly less than the improvement in urban areas over the period from 2005 to 2008. One exception to this is indicator 6 on pensions. In this case, the performance in rural England is likely to be compared against the performance across the UK as a whole. Another exception is indicator 7 on accessibility. This is not a DfT PSA, although improvements in the accessibility of services, especially for the socially excluded, is a Government policy priority. A ruralurban comparison is not appropriate for accessibility. We will judge our influence to have been successful if the indicators listed have risen for rural areas by April 2008. What combination of the 11 accessibility indicators will have to have risen for this to be considered a success will be a matter of judgement. Baseline What is the baseline for performance? (if applicable) Except for indicators 6 and 7, the baseline for performance is the percentage change in urban areas during the period 2005 to 2008. In the case of indicator 6 on pensions, the baseline is the performance in the UK during the period 2005 to 2008. In the case of indicator 7 on accessibility, the baseline is the performance in rural areas at October 2004. Data Sources Which statistics or surveys will be used? 1. Mental health. (i) Crisis services: These data come from Primary Care Trusts via the Local Delivery Plan Return. (ii) CAMHS: CAMHS mapping data. 2. Drug rehabilitation and treatment. National Drug Treatment Monitoring System (NDTMS). 3. Children’s services. OFSTED Register of Childcare Providers. 4. NEETs. Annual Local Area Labour Force Survey. 5. Employment rates of disadvantaged groups. Annual Local Area or Quarterly Labour Force Survey. 6. Pensions. Pension administration system. 7. Accessibility. DfT accessibility indicators. 8. Road traffic accidents. National road casualty database (constructed using information recorded by the police on the STATS19 forms). 9. Affordable housing. (i) Land Registry and (ii) New Earnings Survey. Data Limitations What level of confidence do we have in the data? How established is the data? Is it a National Statistic? Has it been developed yet? In addition to the quality of the source information itself, there is the issue of whether good quality rural figures can be derived from that information. 1. Mental Health. Crisis services: The data are based on a complete enumeration and are therefore not subject to sampling error. Rural figures will be derived using the forthcoming urban/rural classification of Primary Care Trusts. This classification will be available by April 2005. CAMHS: The data are based on a complete enumeration and are therefore not subject to sampling error. Rural figures will be derived using the forthcoming urban/rural classification of Primary Care Trusts. This classification will be available by April 2005. This is a relatively new data set. Improvements have been made for the 2004 collection exercise. The choice of indicators that will be used to measure performance has not yet been made. It is possible that some estimation will be needed to produce figures for PCTs. 2. Drug rehabilitation and treatment. A census of participants was conducted in 2003/4. The data are therefore not subject to sampling error. Information on residence is patchy: postcodes are generally only collected at district level and the primary care trust field has a high proportion of blanks. Information is collected on the Drug Action Team, the areas of which correspond with unitary and upper tier local authorities. These areas are too large to be used to construct meaningful rural figures. The production of rural figures would therefore need to be based on a classification of postcode districts. These areas are sufficiently small to be used to construct rural figures. However, further investigation is needed to confirm the feasibility of this method. 3. Children’s services. The data are based on a complete enumeration and are therefore not subject to sampling error. Rural figures will be derived using the urban-rural classification of wards. 4. NEETs. The Labour Force Survey is a National Statistic. The Annual Local Area Labour Force Survey covers 128 thousand people of working age in England. However, the rural NEET target would relate just to 1618 year olds in rural areas. There are 342 thousand such people. This would give a sample size for this group of around 1200 (assuming an average sampling/response rate). The 90% confidence interval association with a NEET figure of, for example, 10% would be +/- 1.5 percentage points. We feel that this would be an acceptable level of precision. Until we obtain Labour Force Survey figures based on one of the sub-district level classifications in 2005, we will need to construct the indicator using the urban/rural classification of districts that is currently under development. This will be available by April 2005. 5. Employment rates of disadvantaged groups. The Labour Force Survey is a National Statistic. As the number of people in some of the five disadvantaged groups in rural areas would be small, it will be necessary to use a combined indicator for all five groups to obtain a sufficiently precise estimate. Until we obtain Labour Force Survey figures based on one of the sub-district level classifications in 2005, we will need to construct the indicator using the urban/rural classification of districts that is currently under development. This will be available by April 2005. 6. Pensions. Data on the numbers receiving Pension Credit and the Guarantee Credit are based on a complete enumeration and are therefore not subject to sampling error. Rural figures will be derived using the urban/rural classification of Output Areas or wards. A greater challenge is in estimating the number of people who are eligible and therefore the percentage take up. This would need to be based on the Family Resources Survey. Any estimate would be based on quite a small sample and therefore subject to not insignificant sampling error. This has not yet been quantified. 7. Accessibility. The indicators are not yet National Statistics, but there are plans to obtain National Statistics status in 2005. Journey times are measured at a number of times during the day. The data do not take account of flexible route and demand responsive services or of special school buses. Also, there are no transport data for London. In the case of the secondary school indicator, it is assumed that anyone can go to any school and that every school has a sixth form. These indicators will be produced for wards and possibly Super Ouput Areas (SOAs). Rural figures will be constructed using the existing ward classification or, if the data are produced for SOAs, the forthcoming SOA classification. The SOA classification will be available by April 2005. 8. Road traffic accidents. These are National Statistics. The database contains a field for the grid reference of the accident. This is used to determine whether the accident occurred in a rural or urban area. 9. Affordable housing. The data are readily available at unitary / lower tier local authority level. Rural figures will therefore need to be constructed using the urban/rural classification of districts that is currently under development. This classification will be available by April 2005. In the longer term, we will be seeking the production of rural figures using one of the subdistrict classifications. The data on house prices are a complete enumeration of sales during the period. It is therefore affected by variation in the quality of housing sold. This effect is reduced by the use of the lower quartile price. PSA 5 – Sustainable Farming and Food PSA Target 5: “To deliver more customer-focused, competitive and sustainable farming and food industries; and to secure further progress via CAP and WTO negotiations in reducing CAP production-linked support” Assessing success 5.1 Progress in delivering a more customer-focused, competitive and sustainable farming and food industries will be assessed by measuring agriculture’s gross value added per person excluding support payments; productivity of the food industry; farming’s impact on river water quality; and soil organic matter content. Progress in respect of CAP reform is to be measured by reductions in EU export subsidies, reductions in EU production linked domestic support, and reductions in barriers to access to EU markets. The food industry productivity, river water quality and soil organic content indicators are not yet ready to go ‘live’. Indicators will be deemed to be ‘live’ when the methodology, data sources, targets and trajectories for the indicator are agreed by exchange of letter between the Chief Secretary to the Treasury and the Secretary of State for Environment, Food and Rural Affairs. Overall success for PSA 5 will require meeting the targets for CAP reform and agricultural gross value added, and the targets for all bar one of the remaining ‘live’ indicators. PSA 5 (together with a number of other PSAs) is to be achieved through the implementation of the Government’s Sustainable Farming and Food Strategy. The note now considers each of the individual measures within PSA 5. 5.2 5.3 5.4 5.5 To deliver more customer-focused, competitive and sustainable farming and food industries A. Agriculture’s gross value added per person excluding support payments 5.6 This measure has been chosen to measure the economic sustainability of the agriculture sector. It will provide a measure of the competitiveness of the sector. It will capture the effects of a more market orientated approach, as farming responds to market signals for new and different products, higher quality products and different farming methods (e.g. organic) to obtain a greater market value for its outputs. The measure will also capture increases in value-added activities such as further on-farm processing and retailing at farmer’s markets, as farmers’ seek to obtain a greater proportion of the value added across the whole food chain. The gross value added measure will also reflect improvements in both labour and total factor productivity of the industry which will reduce input costs and hence raise gross value added. 5.7 5.8 5.9 It will be ensured that the methodology for the calculation of gross value added will fully reflect the increased value added resulting from higher quality farm produce. However, the normal published measure of gross value added will also be greatly influenced by a variety of external factors. In particular developments in world commodity prices (and changes in policies which influence EU prices) and the sterling exchange rate will have a significant impact on the measurement of output used to compile the gross value added measure. Comparison with the EU14 (i.e. EU15 less UK) average gross value added will be made to largely remove the impact of changes in world commodity prices (which will impact broadly equally across the EU15) upon the measurement of output and allow a clearer measurement of the industry’s response to price changes. The comparison with the EU14 will also have the advantage of allow the UK to be benchmarked against its main international competitors. Comparison will be restricted to the rest of the EU15 rather than extended to the EU25, as the new 10 Member States will likely show very different trends over the coming years to the existing EU reflecting the different phase in the development of agriculture within these economies. As the UK is outside of the Euro-zone, the UK agriculture industry will be affected by the £/Euro exchange rate when compared to other EU countries. The tradable nature of agricultural commodities means that changes in the exchange rate have a significant effect on UK market prices of outputs. These are only partly offset by a similar, but smaller, effect on the price of inputs. Adjustments will be made to the gross value added measure to remove the direct effects of exchange rate movements so that the underlying trend and the industry’s response to those changes in exchange rates can be assessed. The methodology to achieve this has been developed by assessing the relationship between the Agricultural Price Index for outputs and inputs and the £/Euro exchange rate to derive adjustments factors. The methodology will be reviewed at appropriate points in time (in particular following significant shifts in the £/Euro exchange rate to ensure that there are no structural breaks occurring). The target for this measure is for the ratio of the UK exchange rate adjusted GVA to the EU14 GVA measure to increase back to the 19901992 average level by 2010. Achievement of this target will require recovery of the ground lost to other MS during the 1990’s (when UK productivity growth fell behind that of the EU14) whilst keeping pace with further advances in productivity across the rest of the EU. 5.10 5.11 5.12 5.13 Ratio of UK to EU14 GVA per head 1.80 1.60 1.40 1.20 1.00 0.80 0.60 0.40 0.20 0.00 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 Ratio of UK (adjusted) to EU14 GVA per head B. 5.14 C. 5.15 D. 5.16 Productivity of the food industry This indicator is not yet ready to go ‘live’. Farming’s impact on river water quality This indicator is not yet ready to go ‘live’. Soil organic matter content This indicator is not yet ready to go ‘live’. Secure further progress via CAP and WTO negotiations in reducing CAP trade-distorting support 5.17 The effects of agricultural support on agricultural production and trade depend on the nature of the policies adopted: different policies which give rise to similar levels of gross transfers may generate significantly different impacts on trade. To assess the impact of EU agricultural policy on trade we have adopted the WTO framework which identifies three categories of support: export subsidies, domestic support, and restrictions in the access third countries have to domestic markets (‘market access’). We have specified targets for each of these three components and all three will have to be met for the overall target to be deemed achieved. Where the target states that we must be on “an agreed track” towards our objective we will assess success by examining the agreements in place governing future commitments under that measure. 5.18 5.19 The same measures form part of the technical note to the PSA target on trade shared by the Department for Trade and Industry and the Department for International Development. (i) Reductions in EU export subsidies 5.20 Measure: EU expenditure on export subsidies as recorded in the annual ‘Depenses’ document. Baseline: 2003 budget expenditure (€3,721 million) Target: By 2010, export subsidies to have reached or be on an agreed track to reaching zero. 5.21 5.22 (ii) Reductions in EU production-linked domestic support 5.23 Measure: The sum of EU notifications to the WTO of support under the Amber and Blue boxes representing EU 15 support Baseline: 2000/01 marketing year Notification (Amber Box €43,654 million, Blue Box, €22,223 million). Our current estimates for 2008/09, when reforms agreed up to May 2004 are fully implemented, are that the Amber Box will be around €25.2 billion, and the Blue Box €5.5 billion7. Target: By 2008/09, to be on an agreed track to reaching reductions, beyond those agreed up to May 2004, of 10 per cent of the total. Domestic agricultural support is classified under the Uruguay Round Agreement on Agriculture8 to three ‘boxes’ of differing impacts on trade. The most distorting support is classified to the Amber Box, and includes market price support, or subsidies directly related to the quantity produced. Support which is classified as ‘production-limiting’ and is paid on fixed areas and yields or paid on a fixed number of livestock is allocated to the Blue Box. Support which has “no, or at most minimal, trade-distorting effects or effects on production” is classified to the Green Box. The objective of the measure is to identify the impact of changes in EU agricultural policy on trade-distorting domestic support beyond those already agreed. The extension of the CAP to the new EU member states will create a discontinuity in the series notified to the WTO. In order account for this extraneous effect we will continue to calculate estimates for the EU 15. To calculate market price support for the EU 15 we will multiply the price gap by production in EU 15 (source: Eurostat); to identify direct payments in EU 15 we will use budgetary expenditure estimates by member state (source: ‘Depenses’ document). In both cases we will follow the WTO methodology. 5.24 5.25 5.26 5.27 These estimates will be revised as further details on the implementation of the reforms in other member states become available. 8 Available from the WTO website at http://www.wto.org/wto/english/docs_e/legal_e/14-ag.pdf 7 5.28 As there is a significant delay before WTO notifications become available we will supplement that series with our own estimates, produced using the WTO methodology. This will enable us to have a current assessment of the impact of reforms. (iii) Reductions in barriers to access to EU markets 5.29 Measure: An average tariff calculated for a range of important agricultural commodities. Baseline: 2004 Target: By 2008, to be on an agreed track to achieving a fall of at least 36 per cent in the calculated average tariff. Agricultural tariffs tend to be complex and notoriously difficult to measure accurately. To provide a transparent indicator of the level of tariff barriers facing foreign agricultural products we will focus on a limited number of key agricultural tariffs. Specifically we will calculate an estimate of the simple (unweighted) average ad-valorem tariff equivalent, for the Most Favoured Nation (MFN) tariff in specific tariff lines, for a range of important agricultural commodities. The specific commodities which will be included in the calculation are: wheat, maize, barley, beef, sheepmeat, pigmeat, poultry meat, sugar, butter, skimmed milk powder, cocoa paste, tomatoes and apples. One or two tariff lines will be chosen for each commodity to cover a representative primary and first-stage processed product where appropriate. For specific and compound tariffs we will calculate the ad-valorem equivalent using a fixed world reference price based on the average for the years 2000-02. Details of the tariff codes, prices and data sources will be published on the Defra web site. 5.30 5.31 5.32 5.33 5.34 PSA 6 – Waste PSA Target 6: “To enable at least 25% of household waste to be recycled or composted by 2005-06, with further improvement by 2008” Scope 6.1 This target relates to England only as waste management is a devolved matter. Success will be measured through achievement of at least 25% recycling or composting of household waste for the financial year 200506, with a further increase by 2008. 6.2 6.3 Progress will be measured at the end of each financial year. In 2002/03 14.5 per cent of household waste was recycled or composted. Data Sources 6.4 Data from the Defra Municipal Waste Management Survey will be used to measure success against this PSA target. The Municipal Waste Management Survey is an annual (financial year) survey undertaken by Defra of all local authorities in England and is used widely for reporting, monitoring and policy analysis. It collects detailed information about local authority household and municipal waste collection and management, which will allow us to identify how the target is being met. Results from the survey are published on the Defra website at: http://www.defra.gov.uk/environment/statistics/wastats/index.htm For data from 2004/5 the department will be using a new web-based data collection system, WasteDataFlow, which will provide equivalent information but on a more frequent, timely basis. Data will be collected quarterly and then aggregated to the financial year. An initial indication of the annual recycling and composting rate will be produced by combining individual local authority Best Value Performance Indicators (BVPIs) – BV82a percentage of household waste sent for recycling and BV82b percentage of household waste sent for composting. These data are validated by the Audit Commission. However, the more detailed information, including tonnage, from the Municipal Waste Management Survey is required to reliably measure success against target. Information on BVPIs can be found at: http://www.bvpi.gov.uk/pages/Index.asp The survey data are subject to a range of validation checks at different stages of processing. Any identified errors are checked and clarified where necessary with local authorities. 6.5 6.6 6.7 Timing 6.8 The results of each annual Municipal Waste Survey are currently published between a year (provisional results) and fifteen months (full analytical report) after the end of the period. These periods will be reduced by three months for 2003/04 results. An initial estimate based on BVPI data will available around 6 months after the end of the financial year. When fully operational the new quarterly system of data collection will aim to provide final annual data within six months of the end of the year. It is planned to produce indicative quarterly results in a similar timescale. Quality constraints 6.9 Completion of the survey is voluntary but the response rate is in excess of 95%. Where appropriate missing data are estimated on the basis of past performance. The new collection system is expected to achieve a similar level of quality when fully operational. An indication of the variability or uncertainty of the data will be included. 6.10 The survey is classified as a National Statistic and as such is produced to high professional standards set out in the National Statistics code of Practice. Definitions 6.11 The indicator is calculated as the amount of household waste that is sent for recycling or composting divided by the total amount of household waste collected by local authorities "Household waste" means all waste from households collected on the regular local authority refuse collection round, through special bulky waste collections, through separate recycling collections and banks and at Civic Amenity sites. Some other waste, such as that from street sweeping, also counts as household waste. Waste collected for recycling or composting by community groups is also included. The target is based on the total amount of household waste produced less that sent for recycling or composting, i.e. the amount sent to other forms of recovery such as incineration with energy recovery or disposal such as landfill. Fuller definitions of household waste and recycling/composting etc. are given in Annex A of “Guidance on Municipal Waste Management Strategies” http://www.defra.gov.uk/environment/waste/management/guidance/mw ms/10.htm This target is linked to the Sustainable Development indicator (A5) on household waste and recycling which forms part of the waste Headline indicator H15 (waste arisings and waste management). http://www.sustainabledevelopment.gov.uk/indicators/headline/h15.htm 6.12 6.13 6.14 6.15 PSA 7 – Fuel Poverty PSA target 7: “Eliminate fuel poverty in vulnerable households in England by 2010 in line with the Government’s fuel poverty strategy objective” Data 7.1 Fuel poverty data is provided by the English House Condition Survey data which is now conducted on an annual ‘rolling’ basis (from 2002). Quality Controls 7.2 Data will be subject to the requirements of National Statistics. Definitions 7.3 A household is fuel poor if, in order to maintain a satisfactory heating regime, it would be required to spend more than 10% of its income (including Housing Benefit or ISMI) on all household fuel use. Vulnerable households are those who have been identified as being particularly vulnerable to the effects of ill health due to a cold home, including older householders, families with children and householders who are disabled or have long term illness. The strategy target includes reference to delivery ‘As far as reasonably practicable’. This takes account of those households where assistance is refused or where households cannot be helped. The experience of programmes to date is that this may be around 20% of all those approached. 7.4 Timing 7.5 Fuel poverty data is available annually with a lag of just over one year. Territorial Scope 7.6 Fuel poverty is a devolved matter and this target applies only to England Success Criteria 7.7 Success will be measured through monitoring the number of households taken out of fuel poverty against a trajectory required to meet the statutory target for the eradication of fuel poverty, as far as reasonably practicable, for vulnerable households in England by 2010. PSA 8 – Air Quality PSA Target 8: “Improve air quality by meeting our National Air Quality Strategy targets for carbon monoxide, lead, nitrogen dioxide, particles, sulphur dioxide, benzene and 1-3 butadiene (Joint target with the Department for Transport)” 8.1 The Air Quality Strategy, which covers England, sets different dates for achieving health-based targets for each air pollutant between 2003 and 2010. The targets are expressed in terms of the desired concentrations of individual pollutants in air (generally measured as the number of microgrammes of each pollutant per cubic metre of ambient air) to be achieved by a fixed date. A summary of what the targets the Air Quality PSA commits the Government to meeting is set out in the table below: PSA Air Quality Objectives and Target Dates Pollutant PSA Air Quality Strategy objectives in England for protection of public health Concentration Measured as 16.25 µg/m3 5 µg/m3 2.25 µg/m3 10 mg/m3 running annual mean annual mean running annual mean daily maximum running 8-hour mean annual mean annual mean 1 hour mean Date to be achieved by 31.12.2003 31.12.2010 31.12.2003 31.12.2003 Benzene Benzene 1,3 -butadiene Carbon monoxide Lead Nitrogen dioxide* 0.5 µg/m3 0.25 µg/m3 200 µg/m3 not to be exceeded more than 18 times a year 40 µg/m3 50 µg/m3 not to be exceeded more than 35 times a year 40 µg/m3 50µg/m3 not to be exceeded more than 7 times a year 20 µg/m3 31.12.2004 31.12.2008 31.12.2005 annual mean 24 hour mean annual mean 24 hour mean 31.12.2005 31.12.2004 31.12.2004 31.12.2010 Particles (PM10) (gravimetric) all of England Particles (PM10) * (gravimetric) all of England except London Particles (PM10) * (gravimetric) London only 50µg/m not to be exceeded more than 10 times a year 23 µg/m3 3 annual mean 24 hour mean 31.12.2010 31.12.2010 Sulphur dioxide 350 µg/m not to be exceeded more than 24 times a year 125 µg/m3 not to be exceeded more than 3 times a year 266 µg/m3 not to be exceeded more than 3 annual mean 1 hour mean 31.12.2010 31.12.2004 24 hour mean 31.12.2004 15 minute mean 31.12.2005 PSA Air Quality Strategy objectives in Date to be England for protection of public health achieved by Concentration Measured as 35 times a year * Provisional objectives that might need to be revised following the review of corresponding EU Directive limit values in 2004/5 by the European Commission. 8.2 8.3 The full details at http://www.defra.gov.uk/environment/airquality/strategy/ Performance, in terms of progress towards the targets, is assessed annually by means of data from the national air quality monitoring network and published in the Department’s website and the Department’s Annual Report, available on the website http://www.defra.gov.uk/environment/index.htm. Monitoring data from sites in the Government’s Automated Urban and Rural Network (AURN) is published on the Department’s website in real time. Quality Control and Quality Assurance process are then carried out every 6 month. In order to assess whether an annual objective has been met therefore, it is necessary to wait until the end of the 12 month calendar year plus the 6 month Quality Control and Quality Assurance period. Performance on an objective to be met by the end of 2010 for example, would be formally assessed by the second half of 2011. The level of accuracy sought for the data is to meet mandatory monitoring and modelling requirements in European air quality directives9. Accuracy and precision have been calculated for each pollutant in the UK national monitoring network. This gave an accuracy range of between 8% to 11% which is well within the uncertainties provided by the EU air quality directives. Data uncertainties will be recalculated in the light of guidance from the European Standards Institute (CEN) expected in the near future. In addition to the annual assessment of measured concentrations, a general assessment of progress in improving air quality is published each year against the air quality headline indicator H10 for sustainable development which records days when air pollution is moderate and higher. Details available at: www.sustainabledevelopment.gov.uk/indicators/headline/h10.htm. The public can get regularly updated information about air quality in their area and regional forecasts and health advice through the Department’s freephone service on 0800 556677, on TV ceefax and teletext and via the internet: www.airquality.co.uk. Pollutant 8.4 8.5 8.6 PSA 9 – Animal Health and Welfare 9 Directives 1996/62/EC, 1999/30 EC, 2000/69EC. PSA Target 9: “To improve the health and welfare of kept animals, and protect society from the impact of animal diseases, through sharing the management of risk with industry, including: • • • a reduction of 40% in the prevalence of scrapie infection (from 0.33% to 0.20%) by 2010. a reduction in the number of cases of BSE detected by both passive and active surveillance to less than 60 in 2006, with the disease being eradicated by 2010. a reduction in the spread of Bovine TB to new parishes to below the incremental trend of 17.5 confirmed new incidents per annum by the end of 2008” Indicator (of success towards the goal of sharing the management of risk) 9.1 90% of livestock holdings will have an auditable farm health plan by 2014. (Detailed milestones for measurement to be developed). Scrapie 9.2 Target: a reduction of 40% in the prevalence of scrapie infection (from 0.33% to 0.20%) by 2010 . Territorial coverage: 9.3 Scope 9.4 The National Scrapie Plan (NSP) was launched in 2001 and is a GB wide long-term voluntary initiative to reduce the prevalence and eventually eradicate scrapie (and BSE if it’s there and being masked by scrapie) from the national sheep flock. The plan operates on the basis of a programme of selective breeding whereby sheep which are identified as being genetically susceptible to scrapie are removed over time. In addition, recent EU legislation provides for further measures to be applied in those flocks where scrapie has been reported and confirmed. This includes either whole flock slaughter or genotyping and culling of the more scrapie susceptible animals. Under new EU requirements a compulsory genotype based breeding programme will operate in GB from April 2005. The target of a 40% reduction in scrapie prevalence is based on the conclusions of a recent epidemiological report undertaken by the VLA / Welsh Institute of Rural Studies which assessed the impacts of the application of a range of selective breeding strategies designed to remove the most scrapie susceptible genotypes from the GB national breeding flock. England, Scotland and Wales. 9.5 Measurement of qualitative target 9.6 Research is in progress to provide best estimates of the annual prevalence of scrapie infection. This will then allow the detection of significant changes in prevalence. (The current estimate of the prevalence of 0.33%, quoted above, is considered to be fairly precise with known narrow confidence limits. Future estimates will be based on different sampling though with a similar level of confidence in precision.) When these methods have been developed the results will be published in the scientific literature together with the resulting prevalence estimates. In the meantime, the prevalence will be monitored through the results of testing fallen stock and those from the abattoir survey (both requirements of Commission Regulation 999/2001) and statistical analysis of the trend over time will be possible with the accumulation of additional annual estimates. These results will continue to be available to the general public on Defra's website and will be presented at Stakeholder meetings. Data sources 9.7 Fallen stock and abattoir survey weekly statistics http://www.defra.gov.uk/animalh/bse/bse-statistics/level-4 weeklystats.html#act_shp Report and summary of scrapie surveillance in sheep in Great Britain Jan 2002-March 2003 http://www.defra.gov.uk/animalh/bse/bsepublications/reports/SheepSurveyRpt.pdf 9.8 Genotype Data 9.9 Held by the National Scrapie Plan Administration Centre data base (ARCADIA) Scrapie Notification Database 9.10 Held by VLA Background 9.11 Scrapie is a fatal brain disease of sheep (& goats), in our national flock for over 200 years. It is a Transmissible Spongiform Encephalopathy (TSE). Others include BSE and human CJD. Its significance in terms of public and animal health is that were BSE to have transmitted to sheep - as yet a theoretical risk – it might be masked by scrapie (the clinical signs are similar). Unlike BSE in cattle, sheep have variable resistance/susceptibility to scrapie affecting whether they can develop the disease after coming into contact with it. Following advances in (UK) research we can determine each sheep’s ‘scrapie genotype’ by looking at amino acid 9.12 9.13 codes at 3 specific points on its Prion Protein gene (using DNA from a blood sample). There are 5 combinations of codes: ARR, ARH, AHQ, ARQ & VRQ. Sheep receive a copy of the gene from each parent, so the genotype for a sheep can be described as ARR/ARR or ARH/ARQ etc. Of 15 possible genotypes ARR/ARR is the most scrapie resistant and VRQ/VRQ the most susceptible, others fit in a scale in between. BSE 9.14 Target: a reduction in the number of cases of BSE detected by both passive and active surveillance to less than 60 in 2006, with the disease being eradicated by 2010. Territorial coverage 9.15 Scope 9.16 Passive Surveillance: There is a statutory obligation for all BSE suspect animals to be reported. Individual cases are subject to laboratory examination by VLA staff to confirm whether the animal is suffering from BSE or not. Active Surveillance: The current active surveillance programme required by the Commission under Regulation (EC) 999/2001 requires the following categories of bovine animal to be tested for BSE at slaughter: • • • • • • • • All fallen stock aged over 24 months All casualty animals aged over 30 months All animals aged between 24 and 30 months slaughtered for human consumption and identified at ante mortem inspection as casualties All animals submitted for slaughter under the Over Thirty Months Scheme (OTMS) born between 1 August 1996 and 31 July 1997 All animals submitted for slaughter under the OTMS aged over 42 months and born after 1 August 1996 All offspring of BSE cases All animals over 30 months old slaughtered for human consumption A random sample of 10,000 animals per year born before 1 August 1996 and submitted for slaughter under the OTMS England, Scotland and Wales. 9.17 9.18 A number of new BSE cases can be expected over the next few years, but these are expected to occur at a lower and declining rate. The target will have been achieved if there are less than 60 confirmed BSE cases in Great Britain between 1 January and 31 December 2006. 9.19 Weekly statistics for passive and active surveillance are published on the internet, showing the latest incidence of BSE. http://www.defra.gov.uk/animalh/bse/bse-statistics/level-3incidence.html The data for passive and active surveillance is used to measure progress towards the target. 9.20 Timing 9.21 Calendar year, but the final figure for the year, especially for clinical cases, may not be known for some months into the next year. A good estimate of the final outcome should be known by October. Definitions 9.22 Passive Surveillance: A case is a bovine which is suspected on the basis of clinical signs to have BSE and which is subsequently confirmed to have the disease on the basis of histopathological examination of a brain section. Weekly figures, produced by the Veterinary Laboratories Agency (VLA), of the number of confirmed BSE cases. Active Surveillance: A case is a bovine which is subjected to rapid test at slaughter by biorad, without any suspicion of having BSE, and which is subsequently confirmed to have the disease on the basis of examination of a brain section, usually by immunocytochemistry or electron microscopy for scrapie assisted fibrils. Weekly figures, produced by Defra BSE Division, of the number of confirmed BSE cases. 9.23 Methodology a) The target is based on a number of laboratory tests used in the diagnosis of BSE. The basic test is an examination of a section of the brain under a microscope. Additional tests, using reagents which can detect the form of the prion protein thought to be the infective agent, are used to confirm the diagnosis. For suspects born before 1996, all samples negative or inconclusive by the initial examination are subjected to a second test. All suspects born from 1996 onwards are examined by three tests. The target is based on a VLA model which is updated as understanding of the epidemiology of the disease increases. If these changes were to be large, the basis for the target would be uncertain. The target is based on the following assumptions: • That the age structure of the adult population will remain essentially unchanged. If the dairy cow population should show an increase in mean age over the current decade, then there could be additional b) c) cases where the incubation period was exceptionally long, which would have otherwise have been slaughtered before they became identifiable as infected by the currently available tests. • That the average incubation period for the disease will remain unchanged. If the average incubation period should increase, especially for cases born after 1 August 1996, the epidemic could be prolonged beyond 2010. However there is at present no evidence to suggest that this is likely to happen. That the active surveillance programme continues at the current level. If the Commission should require testing in any additional categories (e.g. of more animals born before 1 August 1996), the number of positive cases is likely to increase. • d) The model makes no allowance for a third route of transmission (i.e. other than through feed or maternal transmission). The target does not include such cases. Were they to become apparent such cases would be monitored, recorded, and published as part of the weekly statistics. The target excludes cases arising from imported infection. The VLA model does not take account of these, but they are monitored, recorded and published as part of the weekly statistics. e) Bovine TB Target: a reduction in the spread of Bovine TB to new parishes to below the incremental trend of 17.5 confirmed new incidents per annum by the end of 2008. Territorial coverage 9.24 England. Input to the target 9.25 Some geographic spread of bovine TB is ascribed to movements of cattle, but the number of cases where there is evidence for this are limited. In many cases, it is difficult to be certain whether new outbreaks are the result of movement of cattle or spread through the medium of an increasing wildlife reservoir. It is therefore difficult to predict what impact can be expected from a measure which is directed at cattle movements without taking any account of wildlife reservoirs of disease. The input measure designed to achieve a reduction in the spread of bovine TB is the application of the proposal to impose premovement tuberculin testing for all animals moving from one and two year testing herds (including all herds in parishes designated for one or two yearly testing) to other herds. This excludes movements of calves < 6 weeks old and animals going direct to slaughter. This, along with other proposals, is currently subject to 3 months consultation (the consultation period ends early June 2004). One and two year testing parishes are those that by definition have a high incidence of tuberculosis; all herds within the parishes are subject to routine tuberculin testing at annual or biennial frequencies. Data sources and collection 9.26 We routinely gather a detailed set of statistics on disease incidence using the medium of the Vetnet database. The statistics are published monthly and can be found at: http://www.defra.gov.uk/animalh/tb/stats/stats_nov2003.htm Outcome measures 9.27 We are able, because of the careful accumulation of the epidemiological statistics for bovine TB to predict the future occurrence of disease in new areas i.e. areas that have previously not experienced disease outbreaks. We have set a standard for new areas to be a parish – the geographical unit, that has not experienced a confirmed TB incident in the past 4 years. This predictive curve is shown in Figure 1. The indicator for the new measure is: The number of confirmed new incidents (cases) in a calendar year in parishes where no confirmed new incident had commenced in the previous four calendar years. The slope of this curve i.e the number of new cases predicted from the present data set is 17.5 new cases per annum. 300 9.28 Number of confirmed new incidents (CNI) in parishes where no CNI had commenced in the previous 4 calendar years ENGLAND (all parishes) 250 ENGLAND (3 or 4 yr PTI) 200 150 100 50 0 1988 1990 1992 1994 1996 1998 2000 2002 2004 Year Figure 1. England. Annual number of confirmed new incidents in "new" parishes – all parishes and parishes with 3 or 4-year testing intervals • The slopes of the lines fitted to the respective data series were 17.5 and 7.7 confirmed incidents per year; in the year 2000 these lines passed through 237 and 99 confirmed incidents. Trajectory 9.29 The success of the new measure will be expressed as a deviation from the trend line so that numbers of incidents measured are lower than expected. This curve is shown in Fig 2. The variability of the data (excepting the points for 2001 and 2002 during and post FMD) are such that several years results will be necessary to identify success or failure in achieving the target. Delivery planning is at an early stage, but, were pre-movement testing to be introduced in the autumn of 2004 then we might expect the first statistics to be available for analysis by the end of 2005. We would expect to need at least three years worth of statistics beyond the year of introduction to be able to determine a significant departure from the predicted trend line. Thus our first confirmed judgement of success or failure of the measure cannot be safely made until the end of 2008 at the earliest. A key issue in our ability to implement the measure is acceptance of the proposal that farmers should pay for the additional testing required. Failure to agree this, or to implement the proposal in the autumn for other reasons, will delay assessment of its effectiveness. That being said we know that pre-movement testing makes logical and epidemiological sense and against the background of increasing disease, is one of the few measures that we can sensibly introduce in the short term. y 500 Trend line and prediction limits based on 1992-2000 data 400 N o. of confirm ed breakdow ns 9.30 300 200 100 0 1986 1988 1990 1992 1994 1996 Y ear 1998 2000 2002 2004 2006 Fig. 2 – Number of confirmed incidents in parishes having their first confirmed incident since the start of 1986 Risk sharing with Industry 9.31 Target: To improve the health and welfare of kept animals, and protect society from the impact of animal diseases, through sharing the management of risk with industry. Indicator: 90% of livestock holdings will have an auditable farm health plan by 2014. 9.32 Territorial coverage 9.33 Scope 9.34 This is a Defra indicator for England. It arises from a GB-wide Animal Health and Welfare Strategy: http://www.defra.gov.uk/animalh/ahws/strategy/strategy.htm England, Scotland and Wales have published separate implementation plans. Work to take forward development of farm health planning to raise standards in disease prevention is set out in a draft Action Plan which is being taken forward by Defra and WAGARAD jointly: http://www.defra.gov.uk/animalh/ahws/Positive_Animal/positive_animal .htm This is a key indicator of success towards the goal of sharing the management of risk. England only. 9.35 9.36 9.37 Timing: 9.38 This indicator has a long-term target that reflects the long-term vision that inspires the Animal Health and Welfare Strategy. More specifically, the vision for the future includes: "animal owners can see the direct benefit of actively developing and using animal health and welfare plans." The timing reflects the degree of challenge involved in meeting this target. A proportion of the livestock sector is known to be implementing farm health planning approaches to the keeping of livestock (we estimate around 5%) although more may already be implementing appropriate measures but in an informal way. 9.39 9.40 9.41 Baseline data needs to be gathered to assess current activity (see below). Definitions 9.42 A livestock holding is an enterprise or business on a specific site or registered premises, where the major commercial food livestock species are bred and reared, in particular cattle, sheep, pigs and poultry. Farm health planning should be carried out at this level because it is the smallest monitored unit of livestock keeping. This level of planning is consistent with current data collection mechanisms, for example the Defra Agricultural and Horticultural Census. Registered premises are allocated a County Parish Holding (CPH) which is used by the State Veterinary Service for disease surveillance. Some farming businesses may consist of several holdings. An Auditable Farm Health Plan is a tool by which disease prevalence on a farm is identified alongside necessary measures to improve health status and risk of disease introduction is assessed together with disease prevention measures to minimise the risk are documented. 9.43 9.44 9.45 Methodology 9.46 Farm health planning is considered the best way forward in disease control - prevention being better than cure. There is currently no "standard" farm health planning approach and many in the livestock sector need to be convinced that this is the way to go and that investment is worthwhile as it can result in improved profitability. Defra is currently developing best practice in partnership with livestock sectors and vets under a specific Animal Health and Welfare Strategy initiative. Milestones are set out in Strategy Implementation Plan: http://www.defra.gov.uk/animalh/ahws/strategy/implement_plan.htm By Summer 2006, agreed best practice will be disseminated with the assistance of stakeholders. This will enable subsequent training in farm health planning for vets and those responsible for livestock holdings to take place in a consistent way to a required standard. Two key activities will underpin this: A. Training the veterinary profession and livestock keepers in farm health planning. B. Applying necessary levers to encourage application of farm health plans. Levers include: • Cross-compliance under CAP reform will include animal health and welfare in 2007; 9.47 9.48 9.49 • Voluntary/industry lead schemes such as farm assurance scheme audits - if farmers want to secure particular markets, auditable farm health plans may be required; Legislation will be considered if other levers do not appear to be working after 2007. • Monitoring 9.50 We intend to use the following information gathering exercises to monitor progress in the early stages before other components of the AHWS come into play, for example Disease Surveillance Strategy: A. Sampling using the Farm Practices Survey for Livestock • • Until this year we do not have historical data for this measure and thus no reliable baselines; We have started collecting data through the Farm Practices Survey for Livestock, which includes specific questions about Farm Health Planning and Disease Prevention Measures. These questions were successfully piloted in 2003/04: http://www.defra.gov.uk/corporate/regulat/forms/census/surveys/css 946.htm • B. Whole Farm Approach • Disease prevention measures and farm health planning have also been incorporated as components of the Whole Farm Approach (WFA) Project, which is an integral part of the sustainable farming and food strategy (SFFS). It is a long-term project to develop an integrated solution to support the farming industry across the entire range of its activities: http://www.defra.gov.uk/farm/sustain/wfa/questions.htm • 9.51 Whole Farm Appraisal will contribute to implementation of the crosscompliance part of CAP reform, which places a number of obligations on farmers as food producers, land managers and employers that will have to be fulfilled as a requirement for receiving the single 'decoupled' farm payment. The actions necessary to fulfil these obligations will be included within the Approach. One of these obligations will be animal health and welfare requirements, which will come into force in 2007. Annex A Production of the 2002 Farmland PSA Indicators David Noble 1, Stuart Newson 1 & Richard Gregory 2 2 . British Trust for Ornithology & . Royal Society for the Protection of Birds 1 REPORT to DEFRA January 23, 2004 SUMMARY 1. The Farmland PSA Indicator was updated to 2002 using new data from the BTO/JNCC/RSPB Breeding Bird Survey (BBS), as well as the BTO/JNCC Common Bird Census (CBC). This is the first update since the hiatus caused by the absence of data in 2001 due to Foot and Mouth Disease. 2. The linking of the new BBS data to the historical CBC data was accomplished using the joint-model methods described in Noble et al (2003). This includes the special procedures for linking the population trends of a small number of species (one in the English PSA Indicator and four in the UK PSA Indicator) where the population trends generated by the two surveys cannot be reliably compared. 3. This year, for the first time, two versions were produced: one for the UK and one for England, using updated trends for the same 18 farmland species as previously reported. Each indicator is presented in two ways. The first plot shows the Farmland PSA (UK or England) annual index with calculated confidence limits. These are the smoothed trends using standard smoothing procedures. The second shows the index as a proportion of the index in the previous year. Note that because the 2001 index had to be averaged from the adjacent years, the proportional changes from 2000/2001 and 2001/2002 are necessarily equivalent. 4. The farmland indicator for the UK declines to about 51% of the 1966 value by 2002. The farmland indicator for England shows a decline to about 43% of the 1966 value by 2002. The rate of decline for both the UK and the England versions was greatest between the mid-1970s and mid 1980s, but has slowed in recent years. INTRODUCTION & METHODS Farmland Bird Indicator & PSA target In 2000, as part of the agreement on public spending, the then Ministry of Agriculture, Fisheries and Food agreed a Public Service Agreement (PSA) target. That target is to: "Care for our living heritage and preserve natural diversity by reversing the long term decline in the number of farmland birds by 2020, as measured annually against underlying trends." The target is intended to reflect the desired agri-environmental outcomes of the department's activities. Farmland birds were chosen because they are at or near the top of the terrestrial food chain and, in general, healthy populations indicate a biologically diverse agricultural landscape. The farmland bird indicator (originally produced as one of a suite of wild bird indicators for Defra’s Quality of Life Counts, is calculated on the breeding populations of 18 species, which, collectively, have declined by about 50% since the mid-1970s. The general method for producing indicators is to produce single species trends and then combine single species indices by calculating the geometric mean across species for each year. To help DEFRA in making an effective formal assessment of whether they were meeting their target, Freeman et al. (2001) carried out a study to develop statistical techniques for this purpose. In these analyses, British Trust for Ornithology (BTO) Common Bird Census (CBC) data were used to produce an indicator based on 18 common farmland species. This excluded data for two additional species included in the government’s headline indicator, Barn Owl and Rook, for which reliable annual data were not available and trends had previously been extrapolated (Gregory et al. 1999). Freeman et al. (2001) employed single-species models based on the Generalized Additive Model (GAM) family (Hastie & Tshibirani, 1990), which calculate annual indices while controlling for the fact that the various CBC sites are not visited every year and vary in the number of territories held by each species. Annual site counts are assumed to have a Poisson distribution, and the resulting time-series of estimated annual counts used as an index of abundance for the species. This index can either be calculated without any imposed degree of smoothing (which is the same as a Generalized Linear Model (GLM, in which each annual index value is separate parameter), or using a built in smoothing algorithm where the extent of smoothing is determined by the number of degree of freedom set by the user. Freeman et al. (2001) used the number of degrees of freedom n/3 (rounded to take an integer value), where n is the number of years in the survey. This choice of degrees of freedom was based on the findings of Fewster et al. (2000), who found that this procedure removed much of the noise from the time series, yet was flexible enough to accurately capture important population changes. Development of species-specific methods Although CBC data are believed to be representative of lowland farmland in England (Fuller et al. 1985), the CBC has a number of limitations as a national monitoring scheme. For this reason, the long-term aim was to replace the CBC with the Breeding Bird Survey (BBS) following a period of overlap (1994 to 2000), during which trends could be compared and calibrated. Freeman et al. (2003) compared species trends calculated from the CBC and BBS surveys in a particular region during the period of overlap to see whether they were significantly different and hence examine the potential for producing joint CBC/BBS indices. Where joint CBC/BBS trends could be produced, it was possible to combine the data across surveys, regardless of survey type, by multiplying the likelihoods of the two surveys and maximizing the joint likelihood. The analyses give equal weight to CBC and BBS sites by assigning each CBC the mean of the BBS weights. Differences in the error structure of the two datasets are accommodated by the use of bootstrapping to calculate the confidence intervals. These analyses above suggested that it would be inadvisable to produce joint CBC/BBS English trends for Stock Dove and joint UK trends for four farmland species (Stock Dove, Kestrel, Starling and Tree Sparrow). Following a presentation to Defra in early August 2003 on the impact of using joint CBCBBS trends to generate the QOL and Farmland PSA Wild Bird Indicators, it was decided to explore an alternative procedure for these species: a CBC line from 1966 to 1994, but with a BBS trend anchored to the CBC index in that year. Table 1 lists the species included in the farmland indicator and indicates whether a joint CBC/BBS or anchored trend was used. Table 1. Species included in the farmland indicator for England and the UK and whether joint CBC/BBS trends or anchored trends are produced. Species English trend UK trend Kestrel Grey Partridge Lapwing Stock Dove Woodpigeon Turtle Dove Skylark Yellow Wagtail Whitethroat Jackdaw Starling Tree Sparrow Greenfinch Goldfinch Linnet Yellowhammer Reed Bunting Corn Bunting Joint Joint Joint Anchored Joint Joint Joint Joint Joint Joint Joint Joint Joint Joint Joint Joint Joint Joint Anchored Joint Joint Anchored Joint Join Joint Joint Joint Joint Anchored Anchored Joint Joint Joint Joint Joint Joint Methodology used to update PSA target In the Freeman et al. (2001) report on developing statistical techniques for the production of farmland indicators, a Generalized Additive Modelling approach was adopted. However, the addition of more than 3000 new BBS sites (over all years of the scheme) to the c1500 in the CBC scheme greatly increases the size of the site by year matrix in the joint model, and hence the computing time. This is particularly problematic for the bootstrapping method of estimating confidence intervals. In a comparison of analytical programs for fitting joint trends of this type, Joys et al. (2003) found that GLMs fitted using the PROC GENMOD command in SAS (SAS 1996) for each species and bootstrapped 119 times, was the most efficient method of generating reliable confidence intervals. Post-hoc smoothing using the PROC TSPLINE command in SAS (SAS 1996) was then applied to the bootstraps to reduce the level of noise in the data and reveal underlying trends. This method produced trends and associated confidence intervals that were comparable with the Generalized Additive Models used in Freeman et al. (2001), but were computationally much less intensive. As in Freeman et al. (2001) the level of smoothing is determined by the degrees of freedom, set here as the number of degrees of freedom n/3, where n is the number of years in the survey. In this study, farmland indicators for England and the UK are produced for the period 1966 to 2002, using joint CBC/BBS or anchored trends as appropriate (see above). As in the production of standard farmland indicators, the geometric mean is calculated across species. Bootstrapped index values for each species and each year are then multiplied together for each of the 119 bootstrap runs, from which the 95% confidence intervals are calculated by taking the 2.5 and 97.5 percentiles. Because foot and mouth disease had a large impact on coverage of the BBS in 2001, data for 2001 were not used, but instead the mean of the index values for 2000 and 2002 calculated for each of the 119 bootstraps. Rates of change in the smoothed farmland indicator was assessed by calculating the proportional change between each pair of consecutive years. Confidence intervals were derived by bootstrap re-sampling from the individual species’ trends. RESULTS England The farmland indicator for England is shown graphically in Figure 1. The results show a curve declining in 2002 to about 43% of the 1966 value. Rates of change in the smoothed indicator are shown in Figure 2. This shows that the rate of decline was greatest from the mid 1970s to the mid-1980s, but is slowing in very recent years. Figure 1. Farmland indicator for England 1.2 1.1 1 0.9 Indicator 0.8 0.7 0.6 0.5 0.4 0.3 1966 1970 1974 1978 1982 1986 1990 1994 1998 2002 Year Figure 2. Index for England as a proportion of the previous year’s index. Index as proportion of previous year's index 1.08 Index (proportion of previous year) 1.06 1.04 1.02 1 0.98 0.96 0.94 0.92 0.9 1966 1970 1974 1978 1982 1986 1990 1994 1998 2002 Year United Kingdom Figure 3 shows the farmland indicator for the United Kingdom. This curve is similar to the one for England, but the decline is not quite as pronounced, declining by 2002 to about 51% of the 1966 value. The rate of change in the smoothed indicator is shown in Figure 4. As with England, this declined most rapidly from the mid-1970s to the mid 1980s, but is slowing in very recent years. Figure 3. Farmland indicator for the UK 1.2 1.1 1 0.9 Indicator 0.8 0.7 0.6 0.5 0.4 0.3 1966 1970 1974 1978 1982 1986 1990 1994 1998 2002 Year Figure 4. Index for UK as a proportion of the previous year’s index. Index as proportion of previous year's index 1.06 Index (proportion of previous year) 1.04 1.02 1 0.98 0.96 0.94 0.92 0.9 1966 1970 1974 1978 1982 1986 1990 1994 1998 2002 Year REFERENCES Fewster, R.M., Buckland, S.T., Siriwardena, G.M., Baillie, S.R. and Wilson, J.D. (2002). Analysis of population trends for farmland birds using generalized additive models. Ecology, 81, 1970-1984. Freeman, S.N., Baillie, S.R. & Gregory, R.D. (2001). Statistical analysis of an indicator of population trends in farmland birds. BTO Research Report No. 251. British Trust for Ornithology. Freeman, S.N., Noble, D.G., Newson, S.E. & Baillie, S.R. (2003). Modelling bird population changes using data from the Common Bird Census and the Breeding Bird Survey. BTO Research Report No. 303. British Trust for Ornithology. Fuller, R.J., Marchant, J.H. and Morgan, R.A. (1985). How representative of agricultural practice in Britain are Common Bird Census farmland plots? Bird Study, 32 56-70. Gregory, R.D., Noble, D.G., Cranswick, P.A., Campbell, L.H., Rehfisch, M.M. and Baillie, S.R. (2001). The State of the UK’s Birds 2000. RSPB, BTO and WWT, Sandy. Hastie, T.J. & Tshibirani, R.J. (1990). Generalized Additive Models. Chapman and Hall, London. Noble, D., Newson, S., Banks, A. and Gregory, R. 2003. Effect of the Transition from CBC to BBS on Wild Bird Indicators. BTO/RSPB Report to Defra, August 2003. SAS. Institute Inc. (1996) SAS/Stat Software: Changes and Enhancements through Release 6.11. SAS Institute, Inc., Cary, North Carolina. Annex B: The geography of poor economic performance in rural England This analysis is the result of establishing the nature and distribution of significant economic failure in rural England measured in terms of productivity for the Defra Rural PSA. The analysis used national statistics with validation through Government Offices and Regional Development Agencies and the Local Government Association during November / January 2002/03. Region 1. Rural Districts with consistently poor rural economic performance. 1. Shepway. 2. Isle of Wight. 3. Swale. 4. Dover. 5. Rother 1. Kerrier. 2. Penwith. 3. Carrick. 4. Caradon. 5. Restormal. 6. North Cornwall. 7. Torridge. 8. North Devon. 9. West Devon. 10. Forest of Dean. 1. North Norfolk. 2. Fenland. 3. Breckland 4. Tendring. 5. Kings Lynn & West Norfolk. 1. Oswestry. 2. Herefordshire. 2. Other urban or rural districts containing significant poor rural economic performance. 1. New Forest. 2. Wealden. Overlap with Neighbourhood Renewal Districts. 1. SE 2. SW 1. West Somerset. 2. West Dorset. 3. Sedgemoor. 4. Teignbridge. 1. Kerrier 2. Penwith 3. EoE. 1. Great Yarmouth. 2. Peterborough. 3. Forest Heath 4. Waveney 1. Staffordshire Moorlands. 2. North Warwickshire. 1. Great Yarmouth. 4. WM Region 1. Rural Districts with consistently poor rural economic performance. 3. South Shropshire. 4. North Shropshire. 1. East Lindsay. 2. West Lindsay. 3. High Peak. 4. South Holland. 5. Bolsover. 1. Copeland. 2. Allerdale. 3. Eden. 4. West Lancashire. 2. Other urban or rural districts containing significant poor rural economic performance. 3. Wychavon. Overlap with Neighbourhood Renewal Districts. 5. EM 1. Bassetlaw. 2. Newark and Sherwood. 3. Derbyshire Dales. 1. Bolsover 6. NW 7. YH. 1. Scarborough. 2. East Riding. 3. East Lincolnshire. 8. NE 1. Sedgefield 2. Wear Valley. 3. Derwentside. 4. Alnwick. 5. Berwick. 6. Teesdale. 1. Lancaster. 2. Carlisle. 3. Pendle. 4. Crewe & Nantwich. 5. South Lakeland. 6. Ribble Valley. 1. Craven. 2. Barnsley. 3. Wakefield. 4. Doncaster. 5. Harrogate. 6. Selby. 7. Hambleton. 1. Redcar and Cleveland. 2. Tynedale. 3. Castle Morpeth. 4. Darlington. 1. Allerdale. 2. Pendle. 1. Doncaster. 2. Barnsley. 3. Wakefield. 1. Sedgefield. 2. Wear Valley 3. Redcar and Cleveland. 4. Derwentside.
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