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Frontiers of Medicine

ISSN 2095-0217

ISSN 2095-0225(Online)

CN 11-5983/R

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2018 Impact Factor: 1.847

Front. Med.    2023, Vol. 17 Issue (4) : 758-767    https://doi.org/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
Gang Lu1, Yun Ling2, Minghao Jiang1, Yun Tan1, Dong Wei3, Lu Jiang1, Shuting Yu1, Fangying Jiang1, Shuai Wang1, Yao Dai1, Jinzeng Wang1, Geng Wu4, Xinxin Zhang3, Guoyu Meng1(), Shengyue Wang1(), Feng Liu1(), Xiaohong Fan2(), Saijuan Chen1()
1. Shanghai Institute of Hematology, National Research Center for Translational Medicine, State Key Laboratory of Medical Genomics, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
2. Shanghai Public Health Clinical Center, Fudan University, Shanghai 200083, China
3. Department of Infectious Diseases, Research Laboratory of Clinical Virology, National Research Center for Translational Medicine, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
4. State Key Laboratory of Microbial Metabolism, School of Life Sciences and Biotechnology, The Joint International Research Laboratory of Metabolic and Developmental Sciences, Shanghai Jiao Tong University, Shanghai 200240, China
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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     
Corresponding Author(s): Guoyu Meng,Shengyue Wang,Feng Liu,Xiaohong Fan,Saijuan Chen   
Just Accepted Date: 30 December 2022   Online First Date: 29 March 2023    Issue Date: 12 October 2023
 Cite this article:   
Gang Lu,Yun Ling,Minghao Jiang, et al. Primary assessment of the diversity of Omicron sublineages and the epidemiologic features of autumn/winter 2022 COVID-19 wave in Chinese mainland[J]. Front. Med., 2023, 17(4): 758-767.
 URL:  
https://academic.hep.com.cn/fmd/EN/10.1007/s11684-022-0981-7
https://academic.hep.com.cn/fmd/EN/Y2023/V17/I4/758
Fig.1  Genomic epidemiology analysis of the SARS-CoV-2 genomes sampled from patients diagnosed during the outbreak of autumn/winter 2022. (A) Phylogenetic tree of recently sequenced viral genomes in Shanghai cases. Major sublineages are indicated by squares. (B) Bar plot of the number of genomes for different Omicron sublineages. (C) Pie charts of inferred origin-of-infection for indicated sublineages. (D) Pie charts of the relative fractions of Omicron sublineages per inferred origin-of-infection. Asterisk indicates all known subvariants grouped under each sublineage. The BF.7 sublineage was not included in counting of the BA.5.2 sublineage in (D).
Fig.2  Symptomatic patients during autumn/winter COVID-19 outbreaks in Chinese mainland. (A) Count of all infected cases (upper panel) and severe/critical cases (bottom panel) in Chinese mainland. (B) Pie chart of symptomatic patients with different severities treated in Shanghai Public Health Center (SHPHC).
Severe/critical cases(n = 20) Severe/critical cases with comorbidities exacerbated by COVID-19 (n = 153) Mild/moderate cases(n = 5533) P value
Age (year) P < 0.0001a
Median (range) 66 (55–79) 59 (46–73) 39 (28–53)
< 10, n (%) 0 (0%) 0 (0%) 179 (3.22%)
10–19, n (%) 0 (0%) 2 (1.31%) 289 (5.20%)
20–29, n (%) 0 (0%) 13 (8.50%) 1052 (18.94%)
30–39, n (%) 2 (10.00%) 19 (12.42%) 1284 (23.12%)
40–49, n (%) 2 (10.00%) 10 (6.54%) 1052 (18.94%)
50–59, n (%) 5 (25.00%) 33 (21.57%) 909 (16.37%)
60–69, n (%) 3 (15.00%) 28 (18.30%) 531 (9.56%)
70–79, n (%) 4 (20.00%) 29 (18.95%) 201 (3.62%)
80–89, n (%) 3 (15.00%) 16 (10.46%) 48 (0.86%)
≥ 90, n (%) 1 (5.00%) 3 (1.96%) 8 (0.14%)
Gender P < 0.0001b
Female, n (%) 6 (30%) 52 (33.99%) 3231 (41.82%)
Male, n (%) 14 (70%) 101 (66.01%) 2322 (58.18%)
Tab.1  Clinical features of enrolled patients as of December 26, 2022
Fig.3  Mathematical modeling of the ongoing Omicron outbreak in representative areas in Chinese mainland. (A) Plot of accumulated total COVID-19 cases in the modeling of the autumn/winter Omicron infection waves in selected regions (cities or provinces). (B) Plot of predicted number of daily COVID-19 cases and accumulated total cases as in (A). Total cases in each region were used for simulation except for Chongqing, where the cases in urban or suburban areas were separated. For Chongqing suburban cases, two independent simulations were performed to estimate the influence of Spring Festival travel rush on the rural areas.
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