Publications by authors named "Gary W Davies"
Background: Hybrid SARS-CoV-2 immunity may provide longer duration protection against severe SARS-CoV-2 infection and hospitalisation than purely vaccine-derived immunity. Older adults represent a high-risk group for severe disease, yet available data is skewed towards younger adults.
Methods: A prospective longitudinal study at a large London long-term care facility (LTCF) was conducted from March 2020 to April 2022 to assess the effect of hybrid versus vaccine-only immunity on SARS-CoV-2 infection in older adults during Omicron variant dominance.
Background: Older adults, particularly in long-term care facilities (LTCF), remain at considerable risk from SARS-CoV-2. Data on the protective effect and mechanisms of hybrid immunity are skewed towards young adults precluding targeted vaccination strategies.
Methods: A single-centre longitudinal seroprevalence vaccine response study was conducted with 280 LCTF participants (median 82 yrs, IQR 76-88 yrs; 95.
Monoclonal antibody therapy has been approved for prophylaxis and treatment of severe COVID-19 infection. Greatest benefit appears limited to those yet to mount an effective immune response from natural infection or vaccination, but concern exists around ability to make timely assessment of immune status of community-based patients where laboratory-based serodiagnostics predominate. Participants were invited to undergo paired laboratory-based (Abbott Architect SARS-CoV-2 IgG Quant II chemiluminescent microparticle immunoassay) and lateral flow assays (LFA; a split SARS-CoV-2 IgM/IgG and total antibody test) able to detect SARS-CoV-2 anti-spike antibodies.
View Article and Find Full Text PDFIntroductionImmunoassays targeting different SARS-CoV-2-specific antibodies are employed for seroprevalence studies. The degree of variability between immunoassays targeting anti-nucleocapsid (anti-NP; the majority) vs the potentially neutralising anti-spike antibodies (including anti-receptor-binding domain; anti-RBD), particularly in mild or asymptomatic disease, remains unclear.AimsWe aimed to explore variability in anti-NP and anti-RBD antibody detectability following mild symptomatic or asymptomatic SARS-CoV-2 infection and analyse antibody response for correlation with symptomatology.
View Article and Find Full Text PDFArticle Synopsis
- The study evaluated the effectiveness of the Innova lateral flow immunoassay device for COVID-19 testing among 5,076 healthcare staff in a London NHS Trust from November 2020 to January 2021.* -
- A high positive predictive value (PPV) of 94.21% was found, with 244 out of 259 individuals testing positive via PCR following a positive LFD result, indicating a reliable test performance in this environment.* -
- The results highlighted that many symptomatic staff members were tested, rather than using the LFD solely for asymptomatic screening, suggesting a need for better implementation of testing strategies in hospitals.*
Background: Patient-facing (frontline) health-care workers (HCWs) are at high risk of repeated exposure to SARS-CoV-2.
Aim: We sought to determine the association between levels of frontline exposure and likelihood of SARS-CoV-2 seropositivity amongst HCW.
Methods: A cross-sectional study was undertaken using purposefully collected data from HCWs at two hospitals in London, United Kingdom (UK) over eight weeks in May-June 2020.
Background: As SARS-CoV-2 testing expands, particularly to widespread asymptomatic testing, high sensitivity point-of-care PCR platforms may optimise potential benefits from pooling multiple patients' samples.
Method: We tested patients and asymptomatic citizens for SARS-CoV-2, exploring the efficiency and utility of CovidNudge (i) for detection in individuals' sputum (compared to nasopharyngeal swabs), (ii) for detection in pooled sputum samples, and (iii) by modelling roll out scenarios for pooled sputum testing.
Results: Across 295 paired samples, we find no difference (p = 0.
Background: The artificial neural network (ANN) is an increasingly important tool in the context of solving complex medical classification problems. However, one of the principal challenges in leveraging artificial intelligence technology in the health care setting has been the relative inability to translate models into clinician workflow.
Objective: Here we demonstrate the development of a COVID-19 outcome prediction app that utilizes an ANN and assesses its usability in the clinical setting.
Background: Accurately predicting patient outcomes in Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) could aid patient management and allocation of healthcare resources. There are a variety of methods which can be used to develop prognostic models, ranging from logistic regression and survival analysis to more complex machine learning algorithms and deep learning. Despite several models having been created for SARS-CoV-2, most of these have been found to be highly susceptible to bias.
View Article and Find Full Text PDFBackground: Black, Asian and minority ethnic (BAME) populations are emerging as a vulnerable group in the severe acute respiratory syndrome coronavirus disease (SARS-CoV-2) pandemic. We investigated the relationship between ethnicity and health outcomes in SARS-CoV-2.
Methods And Findings: We conducted a retrospective, observational analysis of SARS-CoV-2 patients across two London teaching hospitals during March 1 -April 30, 2020.
Background: Health-care workers constitute a high-risk population for acquisition of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Capacity for acute diagnosis via PCR testing was limited for individuals with mild to moderate SARS-CoV-2 infection in the early phase of the COVID-19 pandemic and a substantial proportion of health-care workers with suspected infection were not tested. We aimed to investigate the performance of point-of-care and laboratory serology assays and their utility in late case identification, and to estimate SARS-CoV-2 seroprevalence.
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