Outputs (13)

The Challenges and Lessons Learned Building a New UK Infrastructure for Finding and Accessing Population-Wide COVID-19 Data for Research and Public Health Analysis: The CO-CONNECT Project (2024)
Journal Article
Jefferson, E., Milligan, G., Johnston, J., Mumtaz, S., Cole, C., Best, J., Giles, T. C., Cox, S., Masood, E., Horban, S., Urwin, E., Beggs, J., Chuter, A., Reilly, G., Morris, A., Seymour, D., Hopkins, S., Sheikh, A., & Quinlan, P. (2024). The Challenges and Lessons Learned Building a New UK Infrastructure for Finding and Accessing Population-Wide COVID-19 Data for Research and Public Health Analysis: The CO-CONNECT Project. Journal of Medical Internet Research, 26, Article e50235. https://doi.org/10.2196/50235

The COVID-19-Curated and Open Analysis and Research Platform (CO-CONNECT) project worked with 22 organizations across the United Kingdom to build a federated platform, enabling researchers to instantaneously and dynamically query federated datasets t... Read More about The Challenges and Lessons Learned Building a New UK Infrastructure for Finding and Accessing Population-Wide COVID-19 Data for Research and Public Health Analysis: The CO-CONNECT Project.

Lessons from the PROTECT-CH COVID-19 platform trial in care homes (2024)
Journal Article
Bath, P. M., Ball, J., Boyd, M., Gage, H., Glover, M., Godfrey, M., Guthrie, B., Hewitt, J., Howard, R., Jaki, T., Juszczak, E., Lasserson, D., Leighton, P., Leyland, V., Shen Lim, W., Logan, P., Meakin, G., Montgomery, A., Ogollah, R., Passmore, P., …Gordon, A. L. (in press). Lessons from the PROTECT-CH COVID-19 platform trial in care homes. Health Technology Assessment,

The association between drugs and vaccines commonly prescribed to older people and bullous pemphigoid: a case-control study (2024)
Journal Article
Swiderski, M., Vinogradova, Y., Knaggs, R. D., Harman, K., Harwood, R. H., Prasad, V., Persson, M. S. M., Figueredo, G., Layfield, C., & Gran, S. (2024). The association between drugs and vaccines commonly prescribed to older people and bullous pemphigoid: a case-control study. British Journal of Dermatology, Article ljae416. https://doi.org/10.1093/bjd/ljae416

Background
Bullous pemphigoid (BP) is an autoimmune skin disease that affects mainly older people. Numerous drugs have been previously associated with BP based on case series and small hospital-based studies. More reliable and precise estimates of a... Read More about The association between drugs and vaccines commonly prescribed to older people and bullous pemphigoid: a case-control study.

The association between drugs and vaccines commonly prescribed to older people and bullous pemphigoid: a UK population-based case-control study (2024)
Journal Article
Swiderski, M., Vinogradova, Y., Knaggs, R., Harman, K., Harwood, R., Prasad, V., Persson, M., Figueredo, G., Layfield, C., & Gran, S. (2024). The association between drugs and vaccines commonly prescribed to older people and bullous pemphigoid: a UK population-based case-control study. British Journal of Dermatology, https://doi.org/10.1093/bjd/ljae416

Background
Bullous pemphigoid (BP) is an autoimmune skin disease that affects mainly older people. Numerous drugs have been previously associated with BP based on case series and small hospital-based studies. More reliable and precise estimates of a... Read More about The association between drugs and vaccines commonly prescribed to older people and bullous pemphigoid: a UK population-based case-control study.

Monitoring university student response to social distancing policy during the SARS-CoV-2 pandemic using Bluetooth: the RADAR study (2024)
Journal Article
Bolton, K. J., Mendez-Villalon, A., Nanji, H., Jia, R., Ayling, K., Figueredo, G., & Vedhara, K. (in press). Monitoring university student response to social distancing policy during the SARS-CoV-2 pandemic using Bluetooth: the RADAR study. Mathematics in Medical and Life Sciences,

Aim: We use the Remote Assessment of Disease and Relapses platform (RADAR) to collect Bluetooth contact and location data from university students. We test the ability of this technology to objectively capture social interaction, explore the propensi... Read More about Monitoring university student response to social distancing policy during the SARS-CoV-2 pandemic using Bluetooth: the RADAR study.

Association between Nutritional Status Assessed by Body Mass Index and Crohn’s Disease Phenotype: A Nation-Wide Analysis (2024)
Journal Article
Ndzo, J., Vuyyuru, S. K., Trimble, T., Yan, K., Figueredo, G., & Moran, G. W. (in press). Association between Nutritional Status Assessed by Body Mass Index and Crohn’s Disease Phenotype: A Nation-Wide Analysis. Journal of Crohn's and Colitis,

Background & Aims:

Incidence of obesity and Crohn’s disease (CD) is increasing globally. Therefore, understanding any associations between adiposity and disease phenotype is crucial. We aimed explore the relationship between nutritional status me... Read More about Association between Nutritional Status Assessed by Body Mass Index and Crohn’s Disease Phenotype: A Nation-Wide Analysis.

A SARS-CoV-2 minimum data standard to support national serology reporting (2024)
Journal Article
Urwin, E. N., Martin, J., Sebire, N., Harris, A., Johnson, J., Masood, E., …Jefferson, E. (2024). A SARS-CoV-2 minimum data standard to support national serology reporting. Annals of Clinical Biochemistry, https://doi.org/10.1177/00045632241261274

Background: Healthcare laboratory systems produce and capture a vast array of information, yet do not always report all of this to the national infrastructure within the United Kingdom. The global COVID-19 pandemic brought about a much greater need f... Read More about A SARS-CoV-2 minimum data standard to support national serology reporting.

A machine learning-driven approach to predicting thermo-elasto-hydrodynamic lubrication in journal bearings (2024)
Journal Article
Cartwright, S., Rothwell, B. C., Figueredo, G., Medina, H., Eastwick, C., Layton, J., & Ambrose, S. (2024). A machine learning-driven approach to predicting thermo-elasto-hydrodynamic lubrication in journal bearings. Tribology International, 196, Article 109670. https://doi.org/10.1016/j.triboint.2024.109670

Traditional methods of evaluating the performance of journal bearings, for example thermal-elastic-hydrodynamic- lubrication theory, are limited to simplified conditions that often fail to accurately model real-world components. Numerical models that... Read More about A machine learning-driven approach to predicting thermo-elasto-hydrodynamic lubrication in journal bearings.

An empirical critique of the low income low energy efficiency approach to measuring fuel poverty (2024)
Journal Article
Semple, T., Rodrigues, L., Harvey, J., Figueredo, G., Nica-Avram, G., Gillott, M., …Goulding, J. (2024). An empirical critique of the low income low energy efficiency approach to measuring fuel poverty. Energy Policy, 186, Article 114014. https://doi.org/10.1016/j.enpol.2024.114014

Fuel poverty is a complex socioenvironmental issue of increasing global significance. In England, fuel poverty is assessed via the Low Income Low Energy Efficiency (LILEE) indicator, yet concerns exist regarding the efficacy of this metric given its... Read More about An empirical critique of the low income low energy efficiency approach to measuring fuel poverty.

Active learning-driven uncertainty reduction for in-flight particle characteristics of atmospheric plasma spraying of silicon (2023)
Journal Article
Memon, H., Gjerde, E., Lynam, A., Chowdhury, A., De Maere, G., Figueredo, G., & Hussain, T. (2024). Active learning-driven uncertainty reduction for in-flight particle characteristics of atmospheric plasma spraying of silicon. Engineering Applications of Artificial Intelligence, 128, Article 107465. https://doi.org/10.1016/j.engappai.2023.107465

The first-of-its-kind use of the active learning (AL) framework in thermal spray is adapted to enhance the prediction accuracy of the in-flight particle characteristics. The successful AL framework implementation via Bayesian Optimisation is benefici... Read More about Active learning-driven uncertainty reduction for in-flight particle characteristics of atmospheric plasma spraying of silicon.