Respiratory virology dashboards for primary care and public health insight in England
Background Effective community surveillance of respiratory diseases relies on the timely collection and analysis of high quality clinical and virology data. The aim was to develop interactive dashboards for general practice, public health, and researcher groups. This would improve the visualisation, utilisation, and quality of virology data from an English sentinel network, support disease trend monitoring, early outbreak response, and thereby reduce poor health outcomes and their societal impact. Methods The study was conducted in the Oxford-Royal College of General Practitioners (RCGP), Research and Surveillance Centre (RSC) sentinel network sponsored by the UK Health Security Agency (UKHSA). A collaborative user-centred design (UCD) approach was used to identify three use cases for general practices, national public health collaborators, and researchers in the internal team. Reference laboratory virology data, and electronic primary care health records were processed, cleaned, linked, and aggregated in a secure Trusted Research Environment (TRE). Dashboards were developed using Microsoft Power BI (Business Intelligence). The effectiveness, usability, and user satisfaction of the dashboards were not formally evaluated. Results Interactive dashboards were co-designed to present spatiotemporal trends of circulating respiratory viruses in the community, in near real-time, with weekly updates on a Wednesday until the previous week ending on Sunday. The dashboard allowed primary care users to filter data to their own results, and it presented key metrics such as virus positivity rates, with benchmarked targets for team incentives. The dashboard also supported public health planning, and research and surveillance activities of the internal RSC team. Conclusion The user-centred dashboards created a data feedback loop. Future work requires formal evaluation of usage metrics, user impact and satisfaction, data quality, and the quality of virology samples.
Authors
- Simon de Lusignan (ORCID: https://orcid.org/0000-0002-8553-2641)
- Uy Hoang (ORCID: https://orcid.org/0000-0002-8428-5140)
- Jessica Smylie (ORCID: https://orcid.org/0000-0001-5036-9197)
- Anika Singanayagam (ORCID: https://orcid.org/0000-0002-2572-0173)
- Katja Höschler (ORCID: https://orcid.org/0000-0003-4837-0433)
- Gavin Jamie (ORCID: https://orcid.org/0000-0001-9147-7784)
- Cecilia Okusi (ORCID: https://orcid.org/0000-0002-5575-8527)
- Harshana Liyanage (ORCID: https://orcid.org/0000-0001-9738-6349)
- Pushpa Kumarapeli (ORCID: https://orcid.org/0000-0002-9552-6835)
- Maria Zambon (ORCID: https://orcid.org/0000-0002-8897-7881)
- Beatrix Kele (ORCID: https://orcid.org/0000-0003-1273-7299)
- Timea Suli (ORCID: https://orcid.org/0009-0009-6982-3180)
- José M. Ordóñez-Mena
- Praveen SebastianPillai
Institutions
- University of Oxford (GB)
- Kingston University (US)
- UK Health Security Agency (GB)
- Royal College of General Practitioners (GB)
Publication Details
- Journal
- PLoS ONE
- Published
- 2026-09-16
- DOI
- https://doi.org/10.1371/journal.pone.0357287
- Primary Topic
- Data-Driven Disease Surveillance
- Type
- article
- Field-Weighted Citation Impact
- 0.00