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Report 49: Growth, population distribution and immune escape of Omicron in England

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Title: Report 49: Growth, population distribution and immune escape of Omicron in England
Authors: Ferguson, N
Ghani, A
Cori, A
Hogan, A
Hinsley, W
Volz, E
Item Type: Report
Abstract: To estimate the growth of the Omicron variant of concern (1) and its immune escape (2–9) characteristics, we analysed data from all PCR-confirmed SARS-CoV-2 cases in England excluding those with a history of recent international travel. We undertook separate analyses according to two case definitions. For the first definition, we included all cases with a definitive negative S-gene Target Failure (SGTF) result and specimen dates between 29/11/2021 and 11/12/2021 inclusive. For the second definition, we included cases with a positive genotype result and specimen date between 23/11/2021 and 11/12/2021 inclusive. We chose a later start date for the SGTF definition to ensure greater specificity of SGTF for Omicron. We used logistic and Poisson regression to identify factors associated with testing positive for Omicron compared to non-Omicron (mostly Delta) cases. We explored the following predictors: day, region, symptomatic status, sex, ethnicity, age band and vaccination status. Our results suggest rapid growth of the frequency of the Omicron variant relative to Delta, with the exponential growth rate of its frequency estimated to be 0.34/day (95% CI: 0.33-0.35) [2.0 day doubling time] over the study period from both SGTF and genotype data. The distribution of Omicron by age, region and ethnicity currently differs markedly from Delta, with 18–29-year-olds, residents in the London region, and those of African ethnicity having significantly higher rates of infection with Omicron relative to Delta. Hospitalisation and asymptomatic infection indicators were not significantly associated with Omicron infection, suggesting at most limited changes in severity compared with Delta. To estimate the impact of Omicron on vaccine effectiveness (VE) for symptomatic infection we used conditional Poisson regression to estimate the hazard ratio of being an Omicron case (using SGTF definition) compared with Delta, restricting our analysis to symptomatic cases and matching by day, region, 10-year age band, sex and ethnicity. We found a significant increased risk of an Omicron case compared to Delta for those with vaccine status AZ 2+weeks post-dose 2 (PD2) , Pfizer 2+w PD2, AZ 2+w post-dose 3 (PD3) and PF 2+w PD3 vaccine states with hazard ratios of 1.86 (95%CI: 1.67-2.08), 2.68 (95%CI: 2.54-2.83), 4.32 (95%CI: 3.84-4.85) and 4.07 (95%CI: 3.66-4.51), respectively, where PD3 states are categorised by the dose 1/2 vaccine used. Depending on the Delta VE estimates used (10), these estimates translate into Omicron VE estimates of between 0% and 20% PD2 and between 55% and 80% PD3 against Omicron, consistent with other estimates (11). Similar estimates were obtained using genotype data, albeit with greater uncertainty. To assess the impact of Omicron on reinfection rates we relied on genotype data, since SGTF is associated with a higher observed rate of reinfection, likely due to reinfections typically having higher Ct values than primary infections and therefore being subject to a higher rate of random PCR target failure. Controlling for vaccine status, age, sex, ethnicity, asymptomatic status, region and specimen date and using conditional Poisson regression to predict reinfection status, Omicron was associated with a 5.41 (95% CI: 4.87-6.00) fold higher risk of reinfection compared with Delta. This suggests relatively low remaining levels of immunity from prior infection.
Issue Date: 15-Dec-2021
URI: http://hdl.handle.net/10044/1/93038
DOI: 10.25561/93038
Start Page: 1
End Page: 10
Journal / Book Title: Imperial College London
Copyright Statement: © 2021 The Author(s). This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
Sponsor/Funder: Medical Research Council (MRC)
Funder's Grant Number: MR/R015600/1
Keywords: COVID-19
Coronavirus
Publication Status: Published
Appears in Collections:Faculty of Medicine
School of Public Health



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