| EPSRC Reference: |
EP/V053922/1 |
| Title: |
The CIVIC Project: A Sustainable Platform for COVID-19 syndromic-surveillance via Health, Deprivation and Mass Loyalty-Card Datasets |
| Principal Investigator: |
Goulding, Dr JO |
| Other Investigators: |
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| Project Partners: |
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| Department: |
Nottingham University Business School |
| Organisation: |
University of Nottingham |
| Scheme: |
Standard Research |
| Starts: |
01 February 2021 |
Ends: |
31 January 2022 |
Value (£): |
233,965
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Summary on Grant Application Form |
In light of ongoing COVID-19 infections, and approaching second waves, there is urgent need to:
N1. Vastly improve estimation of UK-wide unrecorded cases.
N2. Identify key antecedents of COVID in mass, UK-wide behavioural data, that can power urgently needed early-warning systems at scale; sustainably; and without reliance on self-reporting apps.
N3. Model impact to hidden, vulnerable communities (e.g. food poverty, BAME), to help long-term intervention strategies.
CIVIC is ideally placed to address these needs via unparalleled granularity of access to mass behavioural data; A unique partnership: private-sector data-providers (e.g. Boots, OLIO, Fareshare), academic expertise (Epidemiology, Behavioural Science, AI/Statistics), and public-sector impact partners (ONS, JBC, NHS-X) building an unprecedented platform via 3 interlinked work-packages:
WP1. Partnership with Boots/NHS to generate first-ever, sustainable models of untested COVID-19 cases through interrogation of mass, line-item health/pharmacy transaction data (validated against 111-call-data).
WP2. Identification of behavioural and clinical antecedents of COVID-19 outbreak; processing mass retail loyalty-card/point-of-sale logs via AI/machine-learning techniques, generating near-future forecasts, underpinning early-warning systems.
WP3. Modelling of hidden social/economic impacts to key vulnerable communities, identified in actual behavioural patterns not simple demographic projections.
Each WP has 2 stages. Stage-1 focuses on strictly-anonymized, aggregated data derived from >1.5 billion transactional records, providing crucial deliverables and revolutionizing insights for each of the UK's 32,884 neighbourhoods (LSOAs) within just 4 months. Stage-2 increases fidelity, via individual-level modelling via a ground-breaking "Data Donation" framework.
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Key Findings |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Potential use in non-academic contexts |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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Impacts |
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| Description |
This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk |
| Summary |
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| Date Materialised |
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Sectors submitted by the Researcher |
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This information can now be found on Gateway to Research (GtR) http://gtr.rcuk.ac.uk
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| Project URL: |
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| Further Information: |
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| Organisation Website: |
http://www.nottingham.ac.uk |