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 (preprint)

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 (47.2% vs 41.8%, p=0.012), and in those infected with the B.1.1.7 variant compared to non-B.1.1.7 variants (48.0% vs 41.8%, p=0.042). A diagnosis of frailty was less common in wave two (11.5% v 22.8%, p<0.001) and in the group infected with B.1.1.7 (14.5% v 22.4%, p=0.001). There was no difference in severity on admission between waves, as measured by hypoxia at admission (wave one 64.3% vs wave two 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 (70.0% vs 62.5%, 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.