Background: Rapid identification and investigation of healthcare-associated infections (HCAIs) is important for suppression of SARS-CoV-2, but the infection source for hospital onset COVID-19 infections (HOCIs) cannot always be readily identified based only on epidemiological data. Viral sequencing data provides additional information regarding potential transmission clusters, but the low mutation rate of SARS-CoV-2 can make interpretation using standard phylogenetic methods difficult. Methods: We developed a novel statistical method and sequence reporting tool (SRT) that combines epidemiological and sequence data in order to provide a rapid assessment of the probability of HCAI among HOCI cases (defined as first positive test >48 hours following admission) and to identify infections that could plausibly constitute outbreak events. The method is designed for prospective use, but was validated using retrospective datasets from hospitals in Glasgow and Sheffield collected February-May 2020. Results: We analysed data from 326 HOCIs. Among HOCIs with time-from-admission >8 days the SRT algorithm identified close sequence matches from the same ward for 160/244 (65.6%) and in the remainder 68/84 (81.0%) had at least one similar sequence elsewhere in the hospital, resulting in high estimated probabilities of within-ward and within-hospital transmission. For HOCIs with time-from-admission 3-7 days, the SRT probability of healthcare acquisition was >0.5 in 33/82 (40.2%). Conclusions: The methodology developed can provide rapid feedback on HOCIs that could be useful for infection prevention and control teams, and warrants further prospective evaluation. The integration of epidemiological and sequence data is important given the low mutation rate of SARS-CoV-2 and its variable incubation period. Funding: COG-UK HOCI funded by COG-UK consortium, supported by funding from UK Research and Innovation, National Institute of Health Research and Wellcome Sanger Institute.

Background: Viral sequencing of SARS-CoV-2 has been used for outbreak investigation, but there is limited evidence supporting routine use for infection prevention and control (IPC) within hospital settings. Methods: We conducted a prospective non-randomised trial of sequencing at 14 acute UK hospital trusts. Sites each had a 4-week baseline data-collection period, followed by intervention periods comprising 8 weeks of 'rapid' (<48h) and 4 weeks of 'longer-turnaround' (5-10 day) sequencing using a sequence reporting tool (SRT). Data were collected on all hospital onset COVID-19 infections (HOCIs; detected ≥48h from admission). The impact of the sequencing intervention on IPC knowledge and actions, and on incidence of probable/definite hospital-acquired infections (HAIs) was evaluated. Results: A total of 2170 HOCI cases were recorded from October 2020-April 2021, corresponding to a period of extreme strain on the health service, with sequence reports returned for 650/1320 (49.2%) during intervention phases. We did not detect a statistically significant change in weekly incidence of HAIs in longer-turnaround (incidence rate ratio 1.60, 95%CI 0.85-3.01; P=0.14) or rapid (0.85, 0.48-1.50; P=0.54) intervention phases compared to baseline phase. However, IPC practice was changed in 7.8% and 7.4% of all HOCI cases in rapid and longer-turnaround phases, respectively, and 17.2% and 11.6% of cases where the report was returned. In a 'per-protocol' sensitivity analysis there was an impact on IPC actions in 20.7% of HOCI cases when the SRT report was returned within 5 days. Capacity to respond effectively to insights from sequencing was breached in most sites by the volume of cases and limited resources. Conclusion: While we did not demonstrate a direct impact of sequencing on the incidence of nosocomial transmission, our results suggest that sequencing can inform IPC response to HOCIs, particularly when returned within 5 days. Funding: COG-UK is supported by funding from the Medical Research Council (MRC) part of UK Research & Innovation (UKRI), the National Institute of Health Research (NIHR) [grant code: MC_PC_19027], and Genome Research Limited, operating as the Wellcome Sanger Institute. Clinical trial number: ClinicalTrials.gov Identifier: NCT04405934.

BackgroundRapid identification and investigation of healthcare-associated infections (HCAIs) is important for suppression of SARS-CoV-2, but the infection source for hospital onset COVID-19 infections (HOCIs) cannot always be readily identified based only on epidemiological data. Viral sequencing data provides additional information regarding potential transmission clusters, but the low mutation rate of SARS-CoV-2 can make interpretation using standard phylogenetic methods difficult.MethodsWe developed a novel statistical method and sequence reporting tool (SRT) that combines epidemiological and sequence data in order to provide a rapid assessment of the probability of HCAI among HOCI cases (defined as first positive test >48 hours following admission) and to identify infections that could plausibly constitute outbreak events. The method is designed for prospective use, but was validated using retrospective datasets from hospitals in Glasgow and Sheffield collected February-May 2020.ResultsWe analysed data from 326 HOCIs. Among HOCIs with time-from-admission ≥8 days the SRT algorithm identified close sequence matches from the same ward for 160/244 (65.6%) and in the remainder 68/84 (81.0%) had at least one similar sequence elsewhere in the hospital, resulting in high estimated probabilities of within-ward and within-hospital transmission. For HOCIs with time-from-admission 3-7 days, the SRT probability of healthcare acquisition was >0.5 in 33/82 (40.2%).ConclusionsThe methodology developed can provide rapid feedback on HOCIs that could be useful for infection prevention and control teams, and warrants further prospective evaluation. The integration of epidemiological and sequence data is important given the low mutation rate of SARS-CoV-2 and its variable incubation period.

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ObjectivesNosocomial transmission of SARS-CoV-2 has been a significant cause of mortality in National Health Service (NHS) hospitals during the COVID-19 pandemic. The COG-UK Consortium Hospital-Onset COVID-19 Infections (COG-UK HOCI) study aims to evaluate whether the use of rapid whole-genome sequencing of SARS-CoV-2, supported by a novel probabilistic reporting methodology, can inform infection prevention and control (IPC) practice within NHS hospital settings.DesignMulticentre, prospective, interventional, superiority study.Setting14 participating NHS hospitals over winter–spring 2020/2021 in the UK.ParticipantsEligible patients must be admitted to hospital with first-confirmed SARS-CoV-2 PCR-positive test result >48 hour from time of admission, where COVID-19 diagnosis not suspected on admission. The projected sample size is 2380 patients.InterventionThe intervention is the return of a sequence report, within 48 hours in one phase (rapid local lab processing) and within 5–10 days in a second phase (mimicking central lab), comparing the viral genome from an eligible study participant with others within and outside the hospital site.Primary and secondary outcome measuresThe primary outcomes are incidence of Public Health England (PHE)/IPC-defined SARS-CoV-2 hospital-acquired infection during the baseline and two interventional phases, and proportion of hospital-onset cases with genomic evidence of transmission linkage following implementation of the intervention where such linkage was not suspected by initial IPC investigation. Secondary outcomes include incidence of hospital outbreaks, with and without sequencing data; actual and desirable changes to IPC actions; periods of healthcare worker (HCW) absence. Health economic analysis will be conducted to determine cost benefit of the intervention. A process evaluation using qualitative interviews with HCWs will be conducted alongside the study.Trial registration numberISRCTN50212645. Pre-results stage. This manuscript is based on protocol V.6.0. 2 September 2021.

Intervention programme theory enhances the development, evaluation, optimisation and translation of complex interventions. It clearly specifies the ways intervention context and content combine to produce intervention outcomes. We report the development of initial programme theory for a SARS-CoV-2 genome sequence-report tool (SRT). The SRT translates genome sequencing data to drive changes in the intensity and location of infection prevention and control (IPC) and related cleaning activities within UK NHS hospitals to reduce nosocomial infections. The SRT is being trialled within the COVID-19 Genomics UK Consortium Hospital-Onset COVID-19 study (HOCI). Within the HOCI study, we will assess the impact of the SRT, and its timing, when compared to no sequence data, on the occurrence and transmission location of nosocomial infection, reducing its incidence rate and identifying previously undetected nosocomial transmission. To develop the initial programme theory we used documentary analysis (e.g. trial protocol, case report forms, drafts of the SRT), informal discussions with trial team members, and the iterative development of logic models. The intervention’s causal mechanisms were conceptualised using combined insights from behavioural, implementation science and complex adaptive systems perspectives. Our initial programme theory will subsequently be used to shape a process evaluation within a diverse sample of trial sites. The planned process evaluation will use the initial programme theory and assess SRT acceptability, support for its putative causal mechanisms, issues of fidelity and adaptation, and examine how the planned intervention has worked, or not, in relation to intended and unintended consequences.

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Background Mental health disorders in the context of long-term conditions in children and young people are currently overlooked and undertreated. Evidence-based psychological treatments for common childhood mental health disorders (anxiety, depression and disruptive behaviour disorders) have not been systematically evaluated in young people with epilepsy despite their high prevalence in this population. The aim of this multi-site randomised controlled trial is to determine the clinical and cost-effectiveness of adding a modular psychological intervention to usual care for the mental health disorders in comparison to assessment-enhanced usual care alone. Methods In total, 334 participants aged 3–18 years attending epilepsy services will be screened for mental health disorders with the Strengths and Difficulties Questionnaire (SDQ) and the diagnostic Development and Wellbeing Assessment (DAWBA). Those identified as having a mental health disorder and consenting to the trial will be randomised to either receive up to 22 sessions of the modular psychological intervention (MATCH-ADTC) delivered over the telephone over 6 months by non-mental health professionals in addition to usual care or to assessment-enhanced usual care alone. Outcomes will be measured at baseline, 6 months and 12 months post-randomisation. It is hypothesised that MATCH-ADTC plus usual care will be superior to assessment-enhanced usual care in improving emotional and behavioural symptoms. The primary outcome is the SDQ reported by parents at 6 months. Secondary outcomes include parent-reported mental health measures such as the Revised Children’s Anxiety and Depression Scale, quality of life measures such as the Paediatric Quality of Life Inventory and physical health measures such as the Hague Seizure Severity Scale. Outcome assessors will be blinded to group assignment. Qualitative process evaluations and a health economic evaluation will also be completed. Discussion This trial aims to determine whether a systematic and integrated approach to the identification and treatment of mental health disorders in children and young people with epilepsy is clinically and cost-effective. The findings will contribute to policies and practice with regard to addressing mental health needs in children and young people with other long-term conditions. Trial registration ISRCTN ISRCTN57823197. Registered on 25 February 2019.