Enzyme-linked Immunosorbent Assay (IELISA) Dataset#
1. Summary#
This dataset is also known as the Covid-19 UK Non-hospital Antibody Testing Results dataset.
| Dataset descriptor | Dataset-specific information |
|---|---|
| Name of dataset in TRE | IELISA |
| Other name | Covid-19 UK Non-hospital Antibody Testing Results |
| Temporal coverage | 01/09/2020 onwards |
| TRE temporal coverage | 01/09/2020 to 2022 |
| Short description | Dataset of results across the UK from Pillar 3 serology (antibody) testing for people who have had COVID-19. A record represents one serology test. |
| Owner | Department of Health and Social Care |
| Frequency of update | Annually |
| Key link | None |
| Keywords | COVID-19, Testing, Immunity |
| Geographical coverage | UK |
| Data resolution | Serology test |
| Specific restrictions to data use | Research must be related to COVID-19. For examples of research purposes acceptable to NHS England see the COVID-19 Public Health Directions 2020: https://digital.nhs.uk/about-nhs-digital/corporate-information-and-documents/directions-and-data-provision-notices/secretary-of-state-directions/covid-19-public-health-directions-2020 |
| Number of variables | 35 |
| Number of observations | 11159 |
| Participant count | 8840 |
| Date of last extract | 2024-04-26 |
2. Metrics#
The tables below summarise the IELISA dataset in the UK LLC TRE.
Table 1 The number of participants from each LPS that are represented in the IELISA dataset in the UK LLC TRE
(Note: numbers relate to the most recent extract of NHS England data)
| LPS | Participant count |
|---|---|
| ALSPAC | 108 |
| BCS70 | 184 |
| BIB | 276 |
| ELSA | 88 |
| EPICN | 39 |
| EXCEED | 279 |
| FENLAND | 300 |
| GLAD | 3923 |
| MCS | 342 |
| NCDS58 | 120 |
| NEXTSTEP | 92 |
| NIHRBIO_COPING | 1038 |
| NSHD46 | 11 |
| TEDS | 192 |
| TRACKC19 | 1177 |
| TWINSUK | 482 |
| UKHLS | 189 |
| TOTAL | 8840 |
3. Helpful syntax#
Below we will include syntax that may be helpful to other researchers in the UK LLC TRE. For longer scripts, we will include a snippet of the code plus a link to Git where you can find the full script.