First and second SARS-CoV-2 waves in inner London: A comparison of admission characteristics and the effects of the B.1.1.7 variant

Luke B Snell, Wenjuan Wang, Adela Alcolea-Medina, Themoula Charalampous, Gaia Nebbia, Rahul Batra, Leonardo de Jongh, Finola Higgins, Yanzhong Wang, Jonathan D Edgeworth, Vasa Curcin

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Abstract

Introduction: A second wave of SARS-CoV-2 infection spread across the UK in 2020 linked with emergence of the more transmissible B.1.1.7 variant. The emergence of new variants, particularly during relaxation of social distancing policies and implementation of mass vaccination, highlights the need for real-time integration of detailed patient clinical data alongside pathogen genomic data. We linked clinical data with viral genome sequence data to compare patients admitted during the first and second waves of SARS-CoV-2 infection.

Methods: Clinical, laboratory and demographic data from five electronic health record (EHR) systems was collected for all cases with a positive SARS-CoV-2 RNA test between March 13th 2020 and February 17th 2021. SARS-CoV-2 viral sequencing was performed using Oxford Nanopore Technology. Descriptive data are presented comparing cases between waves, and between cases of B.1.1.7 and non-B.1.1.7 variants.

Results: There were 5810 SARS-CoV-2 RNA positive cases comprising inpatients (n=2341), healthcare workers (n=1549), outpatients (n=874), emergency department (ED) attenders not subsequently admitted (n=532), inter-hospital transfers (n=281) and nosocomial cases (n=233). There were two dominant waves of admissions starting from around March 13th and October 20th, both with a temporally aligned rise in nosocomial cases (n=96 in wave one, n=137 in wave two). 1470 SARS-CoV-2 isolates were successfully sequenced, including 216/838 (26 admitted cases from wave one, 472/1503 (31 admitted cases in wave two and 121/233 (52 nosocomial cases. 400/472 (85 of sequenced isolates from admitted cases in wave two were the B.1.1.7 variant. The first B.1.1.7 variant was identified on 15th November 2020 and increased rapidly to comprise almost all sequenced isolates in January 2021 (n=600/617, 97. Females made up a larger proportion of admitted cases in wave two (47.21.8 p=0.012), and in those infected with the B.1.1.7 variant compared to non-B.1.1.7 variants (48.01.8 p=0.042). A diagnosis of frailty was less common in wave two (11.52.8 plt;0.001) and in the group infected with B.1.1.7 (14.52.4 p=0.001). There was no difference in severity on admission between waves, as measured by hypoxia at admission (wave one: 64.3 65.6 p=0.658). However, a higher proportion of cases infected with the B.1.1.7 variant were hypoxic on admission compared to other variants (70.02.5 p=0.029).

Conclusions: Automated EHR data extraction linked with SARS-CoV-2 genome sequence data provides valuable insight into the evolving characteristics of cases admitted to hospital with COVID-19. The proportion of cases with hypoxia on admission was greater in those infected with the B.1.1.7 variant, which supports evidence the B.1.1.7 variant is associated with more severe disease. The number of nosocomial cases was similar in both waves despite introduction of many infection control interventions before wave two, an observation requiring further investigation.

Competing Interest StatementThe authors have declared no competing interest.

Funding StatementThis work was supported by the King’s Together Multi and Interdisciplinary Research Scheme (Wellcome Trust Revenue Retention Award). FH, LBS, YW, and VC are supported by the National Institute for Health Research (NIHR) Biomedical Research Centre programme of Infection and Immunity (RJ112/N027) based at Guy’s and St Thomas’ National Health Service NHS) Foundation Trust and King’s College London. This work was also supported by The Health Foundation and the Guy’s and St Thomas’ Charity. COG-UK is supported by funding from the Medical Research Council (MRC) part of UK Research amp; Innovation (UKRI), the National Institute of Health Research (NIHR) and Genome Research Limited, operating as the Wellcome Sanger Institute.Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesThe details of the IRB/oversight body that provided approval or exemption for the research described are given below:

Ethical approval for data informatics was granted by The London Bromley Research Ethics Committee (reference (20/HRA/1871)) to the King’s Health Partners Data Analytics and Modelling COVID-19 Group to collect clinically relevant data points from patient’s electronic health records. Whole genome sequencing of residual viral isolates was conducted under the COVID-19 Genomics UK (COG-UK) consortium study protocol, which was approved by the Public Health England Research Ethics and Governance Group (reference: Ramp;D NR0195).All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived.

YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).Yes I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.YesThe original clinical and genomic datasets are not made available.
Original languageEnglish
JournalMedRxiv
DOIs
Publication statusPublished - 24 Mar 2021

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