The new study, which has not yet been peer-reviewed, also estimated that the risk of being reinfected with omicron is more than five times higher than that of Delta variant.
https://www.imperial.ac.uk/media/imperial-college/medicine/mrc-gida/2021-12-16-COVID19-Report-49.pdf
The growth rates estimated for Omicron translate into doubling times of under 2.5 days, even allowing for the potentially slowing of growth up to 11th December. These estimates are consistent or even faster than doubling times reported from South Africa (13).
The distribution of Omicron by age, region and ethnicity currently differs markedly from Delta, indicating Omicron transmission is not yet uniformly distributed across the population. However, we note that given its immune evasion, the age distribution of Omicron infection in the coming weeks may continue to differ from that of Delta. London is substantially ahead of other English regions in Omicron frequency.
We find strong evidence of immune evasion, both from natural infection, where the risk of reinfection is 5.41 (95% CI: 4.87-6.00) fold higher for Omicron than for Delta, and from vaccine-induced protection. Our VE estimates largely agree with those from UKHSA’s TNCC study (11) and predictions from predicting VE from neutralising antibody titres (4,14), suggesting very limited remaining protection against symptomatic infection afforded by two doses of AZ, low protection afforded by two doses of Pfizer, but moderate to high (55-80%) protection in people boosted with an mRNA vaccine.
Our hazard ratio estimate would suggest the relative risk of reinfection has risen to 0.81 [95%CI: 0.73-1.00] (i.e. remaining protection of 19% [95%CI: 0-27%]) against Omicron.
We find no evidence (for both risk of hospitalisation attendance and symptom status) of Omicron having different severity from Delta, though data on hospitalisations are still very limited.
There are several limitations of this analysis. While case numbers are increasing quickly, there are still limits in our ability to examine interactions between the variables considered. The distribution of Omicron differed markedly from Delta across the English population at the time this analysis was conducted, likely due to the population groups in which it was initially seeded, which increases the risks of confounding in analyses.
SGTF is an imperfect proxy for Omicron, though SGTF had over 60% specificity for Omicron over the date range analysed in the SGTF analysis (and close to 100% by 10th December). Intensified contact tracing around known Omicron cases may have increased case ascertainment over time, potentially introducing additional biases.