Primary assessment of the diversity of Omicron sublineages and the epidemiologic features of autumn/winter 2022 COVID-19 wave in Chinese mainland

Gang Lu, Yun Ling, Minghao Jiang, Yun Tan, Dong Wei, Lu Jiang, Shuting Yu, Fangying Jiang, Shuai Wang, Yao Dai, Jinzeng Wang, Geng Wu, Xinxin Zhang, Guoyu Meng, Shengyue Wang, Feng Liu, Xiaohong Fan, Saijuan Chen

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Front. Med. ›› 2023, Vol. 17 ›› Issue (4) : 758-767. DOI: 10.1007/s11684-022-0981-7
RESEARCH ARTICLE

Primary assessment of the diversity of Omicron sublineages and the epidemiologic features of autumn/winter 2022 COVID-19 wave in Chinese mainland

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Abstract

With the recent ongoing autumn/winter 2022 COVID-19 wave and the adjustment of public health control measures, there have been widespread SARS-CoV-2 infections in Chinese mainland. Here we have analyzed 369 viral genomes from recently diagnosed COVID-19 patients in Shanghai, identifying a large number of sublineages of the SARS-CoV-2 Omicron family. Phylogenetic analysis, coupled with contact history tracing, revealed simultaneous community transmission of two Omicron sublineages dominating the infections in some areas of China (BA.5.2 mainly in Guangzhou and Shanghai, and BF.7 mainly in Beijing) and two highly infectious sublineages recently imported from abroad (XBB and BQ.1). Publicly available data from August 31 to November 29, 2022 indicated an overall severe/critical case rate of 0.035% nationwide, while analysis of 5706 symptomatic patients treated at the Shanghai Public Health Center between September 1 and December 26, 2022 showed that 20 cases (0.35%) without comorbidities progressed into severe/critical conditions and 153 cases (2.68%) with COVID-19-exacerbated comorbidities progressed into severe/critical conditions. These observations shall alert healthcare providers to place more resources for the treatment of severe/critical cases. Furthermore, mathematical modeling predicts this autumn/winter wave might pass through major cities in China by the end of the year, whereas some middle and western provinces and rural areas would be hit by the upcoming infection wave in mid-to-late January 2023, and the duration and magnitude of upcoming outbreak could be dramatically enhanced by the extensive travels during the Spring Festival (January 21, 2023). Altogether, these preliminary data highlight the needs to allocate resources to early diagnosis and effective treatment of severe cases and the protection of vulnerable population, especially in the rural areas, to ensure the country’s smooth exit from the ongoing pandemic and accelerate socio-economic recovery.

Keywords

SARS-CoV-2 / COVID-19 / Omicron / genomic epidemiology

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Gang Lu, Yun Ling, Minghao Jiang, Yun Tan, Dong Wei, Lu Jiang, Shuting Yu, Fangying Jiang, Shuai Wang, Yao Dai, Jinzeng Wang, Geng Wu, Xinxin Zhang, Guoyu Meng, Shengyue Wang, Feng Liu, Xiaohong Fan, Saijuan Chen. Primary assessment of the diversity of Omicron sublineages and the epidemiologic features of autumn/winter 2022 COVID-19 wave in Chinese mainland. Front. Med., 2023, 17(4): 758‒767 https://doi.org/10.1007/s11684-022-0981-7

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Acknowledgements

This work was supported by grants from the National Natural Science Foundation of China (Nos. 82100158, 81890994, 81770143, 81970130, and 81861148030), Double First-Class Project (No. WF510162602) from the Ministry of Education, State Key Laboratory of Medical Genomics, Overseas Expertise Introduction Project for Discipline Innovation (111 Project, No. B17029), National Key R&D Program of China (Nos. 2019YFA0905902 and 2018YFA0107802), Natural Science Foundation of Shanghai (Nos. 20JC1410600, 21ZR1480900, and 21YF1427900), Shanghai Clinical Research Center for Hematologic Disease (No. 19MC1910700), Shanghai Major Project for Clinical Medicine (No. 2017ZZ01002), Shanghai Shenkang Hospital Development Center (No. SHDC2020CR5002), Innovative Research Team of High-level Local Universities in Shanghai, Shanghai Collaborative Innovation Program on Regenerative Medicine and Stem Cell Research (No. 2019CXJQ01), Shanghai Jiao Tong University (No. YG2021QN19), Shanghai Guangci Translational Medical Research Development Foundation. We thank the support from Prof. Hai Fang, the ASTRA computing platform, and the high-throughput sequencing platform in the National Research Center for Translational Medicine (Shanghai). In addition, we thank the Pi computing platform in the Center for High-Performance Computing at Shanghai Jiao Tong University.

Compliance with ethics guidelines

Gang Lu, Yun Ling, Minghao Jiang, Yun Tan, Dong Wei, Lu Jiang, Shuting Yu, Fangying Jiang, Shuai Wang, Yao Dai, Jinzeng Wang, Geng Wu, Xinxin Zhang, Guoyu Meng, Shengyue Wang, Feng Liu, Xiaohong Fan, and Saijuan Chen declare no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. All procedures followed were in accordance with the ethical standards of the responsible committee on human experimentation (institutional and national) and with the Helsinki Declaration of 1975, as revised in 2000(5). Informed consent was obtained from all patients for being included in the study.

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