Peer Review Report For: Adapting COVID-19 research infrastructure to capture influenza and respiratory syncytial virus alongside SARS-CoV-2 in UK healthcare workers winter 2022/23 and beyond: protocol for a pragmatic sub-study [version 3; peer review: 1 approved, 2 approved with reservations]
Bibliographic record
Abstract
Introduction During the COVID-19 pandemic, extensive research was conducted on SARS-CoV-2; however, important questions about other respiratory pathogens remain unanswered. A severe influenza season in 2022–2023 with simultaneous circulation of SARS-CoV2 and respiratory syncytial virus is anticipated. This sub-study aims to determine the incidence and impact of these respiratory viruses on healthcare workers, the symptoms they experienced, the effectiveness of both COVID-19 and influenza vaccination and the burden of these infections on the National Health Service (NHS) workforce. Methods and analysis This is a longitudinal prospective cohort sub-study, utilising the population and infrastructure of the SARS-CoV-2 Immunity & Reinfection Evaluation (SIREN) study, which focuses on hospital staff in the UK. Participants undergo fortnightly nucleic acid amplification testing on a multiplex assay including SARS-CoV-2, influenza A and B and RSV, regardless of symptoms. Questionnaires are completed every two weeks, capturing symptoms, sick days, exposures, and vaccination records. Serum samples are collected monthly or quarterly from participants associated with a SIREN site. This sub-study commenced on 28/11/22 to align with the predicted influenza season and participants’ influenza vaccine status. The SIREN Participant Involvement Panel shaped the aims and methods for the study, highlighting its acceptability. UK devolved administrations were supported to develop local protocols. Analysis plans include incidence of asymptomatic and symptomatic infection, comparisons of vaccination coverage, assessment of sick day burden, and effectiveness of seasonal influenza against infection and time off work. Data are also integrated into UKHSA nosocomial modelling. Ethics and dissemination The protocol was approved by the Berkshire Research Ethics Committee (IRAS ID 284460, REC Reference 20SC0230) on 14/11/2022. Participants were informed in advance. As the frequency and method of sampling remained the same, implied consent processes were approved by the committee. Participants returning to the study give informed consent. Regular reports to advisory groups and peer-reviewed publications are planned to disseminate findings and inform decision making. Clinical trial registration number: ISRCTN11041050; registration date: 12 January 2021. Sub study included in protocol version: v8.0, and amended in v9.0
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.043 | 0.202 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.358 | 0.201 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".