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1. Main results

Just under 14,400 (14,373) school-age children live in households with a shielded person. These children live in 8,310 households in Wales. 

Of these children living in a household with a shielded person, 90% have their ethnicity in the Pupil Level Annual School Census (PLASC) recorded as White British; 49% are female and 51% male.

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Chart 1: Number of children living in shielded households in Wales, June 2020: Just under 14,400 (14,373) school-age children live in households with a shielded person.  The highest number of children is in Cardiff (1524) and the lowest in Ceredigion (263).

Number of children living in shielded households in Wales, June 2020 (MS Excel) 

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Chart 2: Number of shielded households that have children living in them Wales, June 2020: These children live in 8,310 households in Wales.

Number of shielded households that have children living in them, Wales, June 2020 (MS Excel)

2. Children who are shielding

To test the matching, we matched those children flagged as under 16 on the Shielded Patient List with PLASC. We expect the vast majority of children who are under 16 on the shielded patient list to be found within PLASC. A low match rate between these two datasets would suggest our main analysis is likely to miss out a large proportion of children living in a household with a shielded person.

There were 6,561 children on the shielded patient list on 15 June. We linked 5,805 shielding children within the PLASC dataset. We were able to link 88% of children on the shielded list to their details in PLASC. A match rate of 88% indicates the matching quality of the two datasets is good, albeit not perfect. It suggests our analysis may under estimate the number of children living in households with a shielded person. However, given that the shielded patient list is predominantly older adults, this is unlikely to be a big under-estimate.

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Chart 3: Children who are shielding and linked with details in PLASC 2020, June 2020: There were 6,561 children on the shielded patient list on 15 June. We linked 5,805 shielding children within the PLASC dataset. We were able to link 88% of children on the shielded list to their details in PLASC.

Children who are shielding and linked with details in PLASC 2020, June 2020 (MS Excel)

3. Dataset information

The Shielded Patient List (SPL) is a list of clinically extremely vulnerable people. They are deemed most likely to become unwell if they catch coronavirus. Shielded people should have received a letter or been told by their GP that they are in this group. The Shielded Patient List is derived using a variety of data sources drawn from the Health Service. More information on the sources and methodology can be accessed on the NHS Wales Informatics Service.

PLASC 2020 is a list of children enrolled in schools during the 2019/2020 academic year and the census date was January 14 2020. Children who are home-schooled or attend independent schools are not in PLASC. PLASC 2020 contains 469,177 records of children aged 3 to 19.

4. Quality and methodology information

The Administrative Data Research Unit (ADRU) in Welsh Government undertakes research projects for the public good using established administrative datasets. During the coronavirus (COVID-19) pandemic, ADRU has undertaken a number of data linking projects. One of these projects involved linking the Shielded Patient List and Pupil Level Annual School Census 2020 to estimate the number of children living in shielded households and provide demographic information about them. This analysis uses the SPL as of 15 June 2020 when there were 127,095 unique NHS numbers on the list and PLASC 2020 received on 30 April 2020. 

To estimate the number of children living in households with shielded people, we reduced the SPL to include only those aged from 19 to 59 years old. The age range is based on distribution of births by age group in Wales. This also excludes under-16s who are themselves shielded. This reduced the error rate and false matches due to no unique matching field in both datasets. Data linking was done by matching name and address information from the two datasets. 

Our results do not pick up all children because PLASC is limited to school-age children and excludes children who are home-schooled or attend independent schools. Data on Children Educated Other Than At School (EOTAS) are also not included in this analysis. Additionally, inconsistencies between health and education data can affect matching.

The data manipulation was done in Spyder using Python 3.7, on the Welsh Government UKSeRP (UK Secure Research Platform). Below is our data linking process.

Shielded patient list

  • Spaces removed from postcodes.
  • For the main analysis: List reduced to include shielded people aged 19 to 59 only.
  • For shielding children analysis : List included only children flagged as Under 16 in the dataset.
  • Created linking field called 'concatS' which combines Surname and Postcode in the shielded list (e.g., JONESCF113AT).

PLASC 2020

  • Spaces removed from postcodes for uniformity across datasets.
  • Date of Birth, forename, and surnames edited to match formatting in Shielded list.
  • Created linking field called 'concatP' which combines Surname and Postcode in PLASC (e.g., JONESCF113AT).

Merged dataset and tables

  • Merged Shielded list and PLASC using concatS and concatP fields.
  • The two datasets appear side-by-side. Each row contains data from a shielded person who is matched with a child from PLASC. For example, a shielded person with concatS as JONESCF113AT is matched with a child with concatP as JONESCF113AT.
  • Tables are produced by using filters (pandas) in Spyder to consolidate specific characteristics from the dataset (e.g., child's gender).

This research has been carried out as part of the ADR Wales programme of work. The ADR Wales programme of work is aligned to the priority themes as identified in the Welsh Government’s national strategy: Prosperity for All. ADR Wales brings together data science experts at Swansea University Medical School, staff from the Wales Institute of Social and Economic Research, Data and Methods (WISERD) at Cardiff University and specialist teams within the Welsh Government to develop new evidence which supports Prosperity for All by using the SAIL Databank at Swansea University, to link and analyse anonymised data. ADR Wales is part of the Economic and Social Research Council (part of UK Research and Innovation) funded ADR UK (grant ES/S007393/1).

5. Contact details

Kathryn Helliwell
Telephone: 0300 062 8349
Email: ADRUWales@gov.wales

Media: 0300 025 8099

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ADR Wales

 

SFR 102/2020

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