News Release

THE LANCET: No new COVID-19 variants have emerged during China's recent outbreak, analysis of cases in Beijing suggests

Peer-Reviewed Publication

The Lancet

Peer-reviewed / Observational study / People

  • Genome analysis of 413 new COVID-19 infections in Beijing spanning the time period when China lifted its most strict pandemic control policies suggests all were caused by existing strains.
  • More than 90% of local infections in Beijing between November 14 and December 20, 2022, involved Omicron sub-variants BA.5.2 or BF.7. Imported cases during the same period mostly involved different variants to those dominant in Beijing.
  • The authors say the findings can be considered a snapshot of the current state of the pandemic in China.

No new COVID-19 variants have emerged in China during the recent surge in infections since the country ended its zero-COVID policy, according to an analysis of cases in Beijing.

The study, published in The Lancet, suggests two existing Omicron sub-variants, BA.5.2 and BF.7 – among the most dominant variants in Beijing during 2022 – accounted for more than 90% of local infections between November 14 and December 20 2022. 

The authors say the results represent a snapshot of the pandemic in China, due to the characteristics of Beijing’s population and the circulation of highly transmissible COVID-19 strains there. 

China is widely reported to have ended its zero-Covid strategy on 7 December 2022. Since the lifting of these strict COVID-19 control policies – which included targeted lockdowns, mass testing and quarantine – surging case numbers have raised concerns that new variants could emerge. In the three years since COVID-19 was declared a global pandemic, the emergence of variants such as Alpha, Beta, Gamma, Delta, and Omicron has caused multiple waves of cases around the world.

Since December 2019, the study authors routinely collected respiratory samples from imported and local COVID-19 cases in Beijing, and randomly selected samples for analysis. There had been no persistent local transmissions reported in Beijing before December 2022. 

In this latest study, the authors analysed COVID-19 samples detected in Beijing in 2022. Genome sequences were generated using rapid, large-scale sequencing technology, and their evolutionary history and population dynamics analysed using existing high quality COVID-19 sequences. 

From a total of 2,881 high quality sequences included in the study, 413 new samples were randomly selected and sequenced between November 14 – when infections began to increase sharply – and December 20 2022. Of these, 350 were local cases and 63 were imported. Imported cases came from 63 countries and regions.

Analysis of the 413 new sequences revealed they all belong to existing, known COVID-19 strains. The dominant strain in Beijing after November 14 2022 was BF.7, which accounted for 75.7% of local infections. Another Omicron sub-variant, BA5.2, was responsible for 16.3% of local cases. 

The populations of both BA5.2 and BF.7 in Beijing increased after November 14, 2022. The effective size of the BA.5.2 population did not change substantially between November 14 and 25, 2022, but increased sharply around November 30, 2022. The rise coincided with an increased number of BA.5.2 infections around November 30, 2022. The population of BF.7 increased gradually from November 14, 2022. 

Lead author Professor George Gao, of the Institute of Microbiology at the Chinese Academy of Sciences, said: “Given the impact that variants have had on the course of the pandemic, it was important to investigate whether any new ones emerged following the recent changes to China’s COVID-19 prevention and control policies. Our analysis suggests two known Omicron sub-variants – rather than any new variants – have chiefly been responsible for the current surge in Beijing, and likely China as a whole. However, with ongoing large-scale circulation of COVID-19 in China, it is important we continue to monitor the situation closely so that any new variants that might emerge are found as early as possible.” [1]

The authors acknowledge some limitations to their study. While only data in Beijing in 2022, rather than the Chinese mainland, was analysed, the authors say the data is representative of the country as a whole. The number of laboratory-confirmed COVID-19 cases in December 2022 was unavailable because mandatory large-scale testing ended, suggesting the true number of infections is underestimated, leading to a degree of sampling bias in the dataset. More sampling is required to study the transmissibility and pathogenicity of Omicron sub-variants. The evolutionary rate of the virus was assumed to be constant during the initial stage of the outbreak, though it is possible this could vary depending on the variant.

Writing in a linked Comment, Professor Wolfgang Preiser and Dr Tongai Maponga of the University of Stellenbosch, South Africa, who were not involved in the study, said: “It is welcome to see this much-needed data from China. It is certainly reassuring that this study yielded no evidence for novel variants but not a surprise: the surge is amply explained by the abrupt cessation of effective control measures.” However, they urge caution in drawing conclusions about China as a whole based on data from Beijing, saying: “The SARS-CoV-2 molecular epidemiological profile in one region of a vast and densely populated country cannot be extrapolated to the entire country. In other regions of China other evolutionary dynamics might unfold, possibly including animal species that could become infected by human beings and “spill back” a further evolved virus.”


This study was funded by the National Key Research and Development Program of China and the Strategic Priority Research Program of the Chinese Academy of Sciences. It was conducted by researchers from the Beijing Center for Disease Prevention and Control, Chinese Academy of Sciences, Chinese Center for Disease Control and Prevention, and University of Chinese Academy of Sciences. 

[1] Quote direct from author and cannot be found in the text of the Article.

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