Investigation of healthcare-associated SARS-CoV-2 infection: Learning outcomes from an investigative process in the initial phase of the pandemic.

Background: Healthcare-associated (HCA) SARS-CoV-2 infection is a significant contributor to the spread of the 2020 pandemic. Timely review of HCA cases is essential to identify learning to inform infection prevention and control (IPC) policies and organisational response. Aim: To identify key areas for improvement through rapid investigation of HCA SARS-CoV-2 cases and to implement change. Methods: Cases were identified based on date of first positive SARS-CoV-2 PCR sample in relation to date of hospital admission. Cases were reviewed using a structured gap analysis tool to identify key learning points. These were discussed in weekly multidisciplinary meetings to gain consensus on learning outcomes, level of harm incurred by the patient and required actions. Learning was then promptly fed back to individual teams and the organisation. Findings: Of the 489 SARS-CoV-2 cases admitted between 10th March and 23rd June 2020, 114 suspected HCA cases (23.3%) were reviewed; 58/489 (11.8%) were ultimately deemed to be HCA. Five themes were identified: individual patient vulnerability, communication, IPC implementation, policy issues and organisational response. Adaptations to policies based on these reviews were completed within the course of the initial phase of the pandemic. Conclusion: This approach enabled timely learning and implementation of control measures and policy development.

Rebooting medical education with virtual grand rounds during the COVID-19 pandemic.

Social distancing during the coronavirus disease 2019 (COVID-19) pandemic has necessitated drastic changes in the practice of hospital medicine, including the cancellation of many educational activities. At the same time, the emergence of a new disease with a rapidly evolving knowledge base has mandated timely educational updates. To resolve this conflict in our hospital, we substituted 'traditional' grand rounds with 'virtual' grand rounds delivered over Zoom, consisting of a local situation report and operational update, followed by a specialty-specific clinical presentation on management of COVID-19. Attendance was greatly increased (mean 384 attendees) compared to traditional grand rounds (mean 44 attendees) and included a diverse audience of medical professionals. Feedback was overwhelmingly positive, with >80% of responders stating that the sessions would or might inform their clinical practice. COVID-19 has therefore provided an opportunity to modernise grand rounds, and develop a new model matching the needs of medical education beyond the pandemic.

Admission COVID-19 clinical risk assessment for guiding patient placement and diagnostic testing strategy.

INTRODUCTION: Without universal access to point-of-care SARS-CoV-2 testing, many hospitals rely on clinical judgement alone for identifying cases of COVID-19 early. METHODS: Cambridge University Hospitals NHS Foundation Trust introduced a 'traffic light' clinical judgement aid to the COVID-19 admissions unit in mid-March 2020. Ability to accurately predict COVID-19 was audited retrospectively across different stages of the epidemic. RESULTS: One SARS-CoV-2 PCR positive patient (1/41, 2%) was misallocated to a 'green' (non-COVID-19) area during the first period of observation, and no patients (0/32, 0%) were mislabelled 'green' during the second period. 33 of 62 (53%) labelled 'red' (high risk) tested SARS-CoV-2 PCR positive during the first period, while 5 of 22 (23%) 'red' patients were PCR positive in the second. CONCLUSION: COVID-19 clinical risk stratification on initial assessment effectively identifies non-COVID-19 patients. However, diagnosing COVID-19 is challenging and risk of overcalling COVID-19 should be recognised, especially when background prevalence is low.

Rapid implementation of SARS-CoV-2 sequencing to investigate cases of health-care associated COVID-19: a prospective genomic surveillance study.

BACKGROUND: The burden and influence of health-care associated severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections is unknown. We aimed to examine the use of rapid SARS-CoV-2 sequencing combined with detailed epidemiological analysis to investigate health-care associated SARS-CoV-2 infections and inform infection control measures. METHODS: In this prospective surveillance study, we set up rapid SARS-CoV-2 nanopore sequencing from PCR-positive diagnostic samples collected from our hospital (Cambridge, UK) and a random selection from hospitals in the East of England, enabling sample-to-sequence in less than 24 h. We established a weekly review and reporting system with integration of genomic and epidemiological data to investigate suspected health-care associated COVID-19 cases. FINDINGS: Between March 13 and April 24, 2020, we collected clinical data and samples from 5613 patients with COVID-19 from across the East of England. We sequenced 1000 samples producing 747 high-quality genomes. We combined epidemiological and genomic analysis of the 299 patients from our hospital and identified 35 clusters of identical viruses involving 159 patients. 92 (58%) of 159 patients had strong epidemiological links and 32 (20%) patients had plausible epidemiological links. These results were fed back to clinical, infection control, and hospital management teams, leading to infection-control interventions and informing patient safety reporting. INTERPRETATION: We established real-time genomic surveillance of SARS-CoV-2 in a UK hospital and showed the benefit of combined genomic and epidemiological analysis for the investigation of health-care associated COVID-19. This approach enabled us to detect cryptic transmission events and identify opportunities to target infection-control interventions to further reduce health-care associated infections. Our findings have important implications for national public health policy as they enable rapid tracking and investigation of infections in hospital and community settings. FUNDING: COVID-19 Genomics UK funded by the Department of Health and Social Care, UK Research and Innovation, and the Wellcome Sanger Institute.