AndreaBozzo/ceres-open-data-index huggingface dataset:
Vaccination coverage: MMR for one dose (2 years old) - Birmingham Wards

All children for whom the local authority is responsible who received one dose of MMR on or after their first birthday and at any time up to their second birthday as a percentage of all children whose second birthday falls within the time period. ## Note on ward level data This data is GP practice level data taken from Fingertips and converted to wards using our [Fingertips GP to Ward Lookup Matrix for Birmingham and Solihull dataset]. This dataset uses the GP census to allocate an approximate percentage of their patients to each ward based on the citizens home address. ## Rationale MMR is the combined vaccine that protects against measles, mumps and rubella. Measles, mumps and rubella are highly infectious, common conditions that can have serious complications, including meningitis, swelling of the brain (encephalitis) and deafness. They can also lead to complications in pregnancy that affect the unborn baby and can lead to miscarriage. Vaccination coverage is the best indicator of the level of protection a population will have against vaccine preventable communicable diseases. Coverage is closely correlated with levels of disease. Monitoring coverage identifies possible drops in immunity before levels of disease rise. The first MMR vaccine is given to children as part of the routine vaccination schedule, usually within a month of their first birthday. They'll then have a booster dose before starting school, which is usually between three and five years of age. Previous evidence shows that highlighting vaccination programmes encourages improvements in uptake levels.May also have relevance for NICE guidance PH21: Reducing differences in the uptake of immunisations (The guidance aims to increase immunisation uptake among those aged under 19 years from groups where uptake is low). ## Definition of numerator Total number of children whose second birthday falls within the time period who received one dose of MMR on or after their first birthday and at any time before their second birthday. Data for 2013 to 2014 are available at source at LA level. Data prior to 2013 to 2014 were collected at PCT level and converted to LA level using the criteria as described in the notes section below. ## Definition of denominator Total number of children whose second birthday falls within the time period. Data from 2013to 2014 are available at source at LA level. Data prior to 2013 to 2014 were collected at PCT level and converted to LA level using the criteria as described in the notes section below. ## Caveats Full GP postcodes are used to aggregate data to ICB. The GP-level coverage data is collected by NHS Digital Strategic Data Collection Service (SDCS) and published by the UK Health Security Agency (UKHSA) COVER team. ICB data is experimental data and should be treated with caution. It is not an official statistic.
Overcrowded households (Percentage) - Birmingham Wards

This metric provides a measure of whether a household's accommodation is overcrowded or under occupied. It is calculated by summing households with one room too few and households with two or more rooms too few, as a percentage of all households. The ages of the household members and their relationships to each other are used to derive the number of rooms/bedrooms they require, based on a standard formula. The number of rooms/bedrooms required is subtracted from the number of rooms/bedrooms in the household's accommodation to obtain the occupancy rating. An occupancy rating of -1 implies that a household has one fewer room/bedroom than required, whereas +1 implies that they have one more room/bedroom than the standard requirement. Statistical Disclosure Control: In order to protect against disclosure of personal information from the Census, there has been swapping of records in the Census database between different geographic areas, and so some counts will be affected. In the main, the greatest effects will be at the lowest geographies, since the record swapping is targeted towards those households with unusual characteristics in small areas. Data is [Powered by LG Inform Plus] .
Emergency admissions for diabetes (under 19yrs) - ICP Outcomes Framework - Birmingham and Solihull

This dataset presents the crude rate of emergency hospital admissions for insulin-dependent diabetes mellitus (Type 1 diabetes) among children and young people aged under 19. It provides insight into the burden of acute diabetic complications requiring urgent care and supports the evaluation of diabetes management in paediatric populations. ## Rationale Reducing emergency admissions for diabetes in children is a key public health objective. High admission rates may indicate challenges in managing the condition, such as poor glycaemic control, lack of access to specialist care, or gaps in education and support for families. Monitoring this indicator helps inform strategies to improve diabetes care and reduce preventable hospitalisations. ## Numerator The numerator is the number of emergency hospital admissions for individuals aged under 19 with a primary diagnosis of insulin-dependent diabetes mellitus, identified using ICD-10 code E10. Data are sourced from NHS England’s Secondary Uses Service (SUS). ## Denominator The denominator is the total resident population aged under 19, based on the 2021 Census. ## Caveats No specific caveats were noted for this dataset. However, as with all hospital admission indicators, local variations in clinical coding, referral practices, and healthcare access may influence the results. ## External References [Fingertips Public Health Profiles – Diabetes Admissions (Under 19)] [Click here] to explore more from the Birmingham and Solihull Integrated Care Partnerships Outcome Framework.
Boundaries - Wards (2024) - East Birmingham and North Solihull

This file contains the digital vector boundaries for Wards in East Birmingham and North Solihull. The boundaries available are: Generalised Clipped (BGC) - Generalised to 20m and clipped to the coastline (Mean High Water mark) and more generalised than the BFE boundaries. Contains both Ordnance Survey and ONS Intellectual Property Rights. ## TopoJSON Shapefile for Power BI On the Export tab you will find a file under the Alternative exports. This file is in TopoJSON format and is ready for use in compatible visualisation tools such as Power BI or Mapbox.
Emergency admissions for falls (over 65yrs) - ICP Outcomes Framework - Resident Locality

This dataset presents the age-standardised rate of emergency hospital admissions due to falls in individuals aged 65 and over. It serves as a key indicator of frailty, injury risk, and the effectiveness of fall prevention strategies in older populations. ## Rationale Reducing emergency admissions due to falls in older adults is a major public health priority. Falls are a leading cause of injury, loss of independence, and mortality in this age group. Monitoring this indicator supports the development of targeted interventions, community support services, and healthcare planning to reduce fall-related harm. ## Numerator The numerator is the number of emergency hospital admissions for individuals aged 65 and over with a primary diagnosis of injury (ICD-10 codes S00 to T98) and an external cause of a fall (ICD-10 codes W00 to W19). Admissions are included if they are emergency admissions (episode order = 1, admission method starts with '2'). Data are sourced from the Secondary Uses Service (SUS). ## Denominator The denominator is the resident population aged 65 and over, based on the 2021 Census. ## Caveats In 2023, NHS England introduced a methodological change requiring Trusts to report Same Day Emergency Care (SDEC) to the Emergency Care Data Set (ECDS) by July 2024. Early adopter sites began reporting from 2021/22, with others following in 2022/23 and 2023/24. Some Trusts previously reported this activity under Admitted Patient Care, and the shift to ECDS may reduce the number of admissions captured by this indicator. NHSE has advised that SDEC activity cannot currently be accurately identified in existing data flows, and the impact of this change is expected to vary by diagnosis, particularly for injuries and external causes. ## External References [Fingertips Public Health Profiles – Emergency Admissions for Falls (65+)] ## Localities Explained This dataset contains data based on either the resident locality or registered locality of the patient, a distinction is made between resident locality and registered locality populations: * Resident Locality refers to individuals who live within the defined geographic boundaries of the locality. These boundaries are aligned with official administrative areas such as wards and Lower Layer Super Output Areas (LSOAs). * Registered Locality refers to individuals who are registered with GP practices that are assigned to a locality based on the Primary Care Network (PCN) they belong to. These assignments are approximate—PCNs are mapped to a locality based on the location of most of their GP surgeries. As a result, locality-registered patients may live outside the locality, sometimes even in different towns or cities. This distinction is important because some health indicators are only available at GP practice level, without information on where patients actually reside. In such cases, data is attributed to the locality based on GP registration, not residential address. [Click here] to explore more from the Birmingham and Solihull Integrated Care Partnerships Outcome Framework.
Emergency admissions for falls (over 65yrs) - ICP Outcomes Framework - Birmingham and Solihull

This dataset presents the age-standardised rate of emergency hospital admissions due to falls in individuals aged 65 and over. It serves as a key indicator of frailty, injury risk, and the effectiveness of fall prevention strategies in older populations. ## Rationale Reducing emergency admissions due to falls in older adults is a major public health priority. Falls are a leading cause of injury, loss of independence, and mortality in this age group. Monitoring this indicator supports the development of targeted interventions, community support services, and healthcare planning to reduce fall-related harm. ## Numerator The numerator is the number of emergency hospital admissions for individuals aged 65 and over with a primary diagnosis of injury (ICD-10 codes S00 to T98) and an external cause of a fall (ICD-10 codes W00 to W19). Admissions are included if they are emergency admissions (episode order = 1, admission method starts with '2'). Data are sourced from the Secondary Uses Service (SUS). ## Denominator The denominator is the resident population aged 65 and over, based on the 2021 Census. ## Caveats In 2023, NHS England introduced a methodological change requiring Trusts to report Same Day Emergency Care (SDEC) to the Emergency Care Data Set (ECDS) by July 2024. Early adopter sites began reporting from 2021/22, with others following in 2022/23 and 2023/24. Some Trusts previously reported this activity under Admitted Patient Care, and the shift to ECDS may reduce the number of admissions captured by this indicator. NHSE has advised that SDEC activity cannot currently be accurately identified in existing data flows, and the impact of this change is expected to vary by diagnosis, particularly for injuries and external causes. ## External References [Fingertips Public Health Profiles – Emergency Admissions for Falls (65+)] [Click here] to explore more from the Birmingham and Solihull Integrated Care Partnerships Outcome Framework.
Travel to work by bicycle (Percentage of pop. aged 16-74) - WMCA Wards (2025)

This is the proportion of residents that travel to work by bicycle. This dataset provides estimates that classify usual residents aged 16 to 74 by the method of travel used for the longest part, by distance, of the usual journey to work. This topic is only applicable to people who were in employment in the week before the census and estimates are as at census day. Travel to work estimates from the 2001 Census, for example in UV39, are not compatible with this estimates in this dataset because of the differences in the way that people who indicated that they work from home but also have a method of travel to work have been handled. Estimates that are compatible with 2001 are available in dataset CT0015. Information on travel to work informs both national and local transport services and policies. It provides a basis for transport planning, for example, whether new bus routes or changes to existing bus routes are needed. Statistical Disclosure Control: In order to protect against disclosure of personal information from the Census, there has been swapping of records in the Census database between different geographic areas, and so some counts will be affected. In the main, the greatest effects will be at the lowest geographies, since the record swapping is targeted towards those households with unusual characteristics in small areas. Data is [Powered by LG Inform Plus] and automatically checked for new data on the 4th of each month.
Census 2021 Ethnicity and Religion by Age

This dataset provides Census 2021 estimates that classify usual residents in Birmingham by ethnic group, by religion, and by age. Ethnic Group: The ethnic group that the person completing the census feels they belong to. This could be based on their culture, family background, identity or physical appearance. Religion: The religion people connect or identify with (their religious affiliation), whether or not they practise or have belief in it. Age: A person's age on Census Day, 21 March 2021 in England and Wales. ## Coverage This dataset is focused on the data for Birmingham at city level. ## About the 2021 Census The Census takes place every 10 years and gives us a picture of all the people and households in England and Wales. ## Protecting personal data The ONS sometimes need to make changes to data if it is possible to identify individuals. This is known as statistical disclosure control. In Census 2021, they: * Swapped records (targeted record swapping), for example, if a household was likely to be identified in datasets because it has unusual characteristics, they swapped the record with a similar one from a nearby small area. Very unusual households could be swapped with one in a nearby local authority. * Added small changes to some counts (cell key perturbation), for example, we might change a count of four to a three or a five. This might make small differences between tables depending on how the data are broken down when they applied perturbation. For more geographies, aggregations or topics see the link in the Reference below. Or, to create a custom dataset with multiple variables use the ONS [Create a custom dataset tool].
Emergency admissions for falls (over 65yrs) - ICP Outcomes Framework - Birmingham and Solihull Wards

This dataset presents the age-standardised rate of emergency hospital admissions due to falls in individuals aged 65 and over. It serves as a key indicator of frailty, injury risk, and the effectiveness of fall prevention strategies in older populations. ## Rationale Reducing emergency admissions due to falls in older adults is a major public health priority. Falls are a leading cause of injury, loss of independence, and mortality in this age group. Monitoring this indicator supports the development of targeted interventions, community support services, and healthcare planning to reduce fall-related harm. ## Numerator The numerator is the number of emergency hospital admissions for individuals aged 65 and over with a primary diagnosis of injury (ICD-10 codes S00 to T98) and an external cause of a fall (ICD-10 codes W00 to W19). Admissions are included if they are emergency admissions (episode order = 1, admission method starts with '2'). Data are sourced from the Secondary Uses Service (SUS). ## Denominator The denominator is the resident population aged 65 and over, based on the 2021 Census. ## Caveats In 2023, NHS England introduced a methodological change requiring Trusts to report Same Day Emergency Care (SDEC) to the Emergency Care Data Set (ECDS) by July 2024. Early adopter sites began reporting from 2021/22, with others following in 2022/23 and 2023/24. Some Trusts previously reported this activity under Admitted Patient Care, and the shift to ECDS may reduce the number of admissions captured by this indicator. NHSE has advised that SDEC activity cannot currently be accurately identified in existing data flows, and the impact of this change is expected to vary by diagnosis, particularly for injuries and external causes. ## External References [Fingertips Public Health Profiles – Emergency Admissions for Falls (65+)] [Click here] to explore more from the Birmingham and Solihull Integrated Care Partnerships Outcome Framework.
Insight Factsheets

Insight Factsheets The following factsheets can be found here: Birmingham Community Safety This factsheet provides key insights from the Birmingham Community Safety Dashboard which supports the Serious Violence Strategic Needs Assessment. It provides a comprehensive understanding of crimes reported in Birmingham, including breakdowns by crime categories and demographics of suspects, victims and vulnerable groups who may be subject to violence or harm. Climate Change Briefing Book The Climate Change Briefing Book dashboard provides a wealth of data regarding key topics such as emissions, homes and energy performance, transportation, refuse, recycling and waste disposal and environmental justice. The dashboard provides an insight into climate-related topics within Birmingham and how as a city, it compares to other geographical areas such as the English Core Cities. Economy briefing for Leader This factsheet provides information on the latest economic statistics in Birmingham. Housing Briefing Book for publishing The Housing Briefing Book brings together data that is internally held, as well as external sources to provide a rich understanding of the housing stock in Birmingham. The dashboard provides information on all dwellings in Birmingham, council owned housing stock, social housing lettings, rooms, tenure, housing supply, affordability and benefits, and Help to Buy. Inequality in Birmingham Headline Statistics This document provides a comprehensive statistical overview of various socio-economic factors affecting Birmingham, highlighting the disparities in education, income, health, and housing among different demographics. Post 16 Employment and Skills for publishing The Post-16 Employment & Skills dashboard brings together data that is internally held by the council, as well as external sources, to provide information on the following themes: 1) Young People: Population composition and projections of young people in the city 2) Supply: The destinations of young people in terms of education, employment and/or training 3) Demand: Labour market trends, and 4) Provider: Distance travelled by young people in Birmingham to a learning provider. SEND Briefing Book The SEND Briefing Book dashboard provides an overview of people with special educational needs and disabilities (SEND) in Birmingham. In order to learn and have the same opportunities as all children, those with SEND require educational provision that is additional to, or different from, that made generally for others of the same age. ## Viewing and downloading This dataset contains unstructured files such as documents, PDF's and images. To view and download the files click on the Table tab at the top and select the desired file in the File name column. You may use the filters to further refine your selection. ℹ️ Note The Export and API will only download the table of contents.
Boundaries - GB DNO Licence Areas

This dataset contains approximate GIS (geographic information system) geospatial boundaries for each of the DNO Licence Areas in Great Britain. There are 14 licensed Distribution Network Operators (DNOs) in Britain and each is responsible for a regional distribution services area. DNO Licence Areas are sometimes referred to as GSP Groups and historically have also been known as Public Electricity Supplier (PES) regions, though the latter name is no longer widely used. The DNO Licence Area boundaries are unusual because they are only well defined when tested. The boundaries tend to run through rural areas and change over time whenever a new connection is added close to a boundary. For example, a new connection close to an existing boundary can approach the DNO responsible for both neighbouring Licence Areas to ask for a connection, and is free to choose either depending on how much they will charge - once the new connection is made the boundary is, theoretically, re-drawn to ensure that the new connection falls into the correct Licence Area. The boundaries in this dataset were originally shared by Western Power Distribution, now National Grid Electricity Distribution (the DNO responsible for 4 of the 14 Licence Areas) and come with the disclaimer that they are probably a little outdated and not 100% accurate. That said, they are a good indication of the geography of DNO Licence Areas. DNO Licence Areas are widely used as an aggregation entity when reporting electricity network data, for example, in Elexon's publication of electricity settlement data. As such, they are also useful for regional modelling of the GB electricity transmission network, for example to aggregate distributed embedded generator energy flows onto the transmission network. A good example of this is the Regional PV_Live outturn estimates published by The University of Sheffield (https://www.solar.sheffield.ac.uk/pvlive/regional/). Note: DNO Regions do not align with standard geographic regions and should not be used for mapping beyond that related to DNO and Power Networks. ## TopoJSON Shapefile for Power BI On the Export tab you will find a file under the Alternative exports. This file is in TopoJSON format and is ready for use in compatible visualisation tools such as Power BI or Mapbox.