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Abstract
The SARS-CoV-2 Omicron variant sparked the largest wave of infections worldwide. Mainland China eased its strict COVID-19 measures in late 2022 and experienced two nationwide Omicron waves in 2023. Here, we investigated lineage distribution and virus evolution in Guangdong, China, 2022-2023 by comparing 5813 local viral genomes with the datasets from other regions of China and worldwide. Additionally, we conducted three large-scale serological surveys involving 1696 participants to measure their immune response to the BA.5 and XBB.1.9 before and after the corresponding waves. Our findings revealed the Omicron variants, mainly the BA.5.2.48 lineage, causing infections in over 90% of individuals across different age groups within a month. This rapid spread led to the establishment of widespread immunity, limiting the virus’s ability to further adaptive mutation and dissemination. While similar immune responses to BA.5 were observed across all age groups after the initial wave, children aged 3 to 11 developed a stronger cross immune response to the XBB.1.9 strain, possibly explaining their lower infection rates in the following XBB.1 wave. Reinfection with Omicron XBB.1 variant triggered a more potent neutralizing immune response among older adults. These findings highlight the impact of age-specific immune responses on viral spread in potential future waves.
Release of the zero-COVID policy in China in late 2022 led to two large Omicron-driven waves of infection in 2023. Here, the authors analyze virus genomes and serology data from before and after the two waves and describe changes in virus lineage distribution and age-specific antibody responses.
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1 Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China (GRID:grid.508326.a) (ISNI:0000 0004 1754 9032); Guangdong Provincial Center for Disease Control and Prevention, Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangzhou, China (GRID:grid.508326.a) (ISNI:0000 0004 1754 9032)
2 Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China (GRID:grid.508326.a) (ISNI:0000 0004 1754 9032)
3 Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China (GRID:grid.508326.a) (ISNI:0000 0004 1754 9032); Sun Yat-sen University, School of Public Health, Guangzhou, China (GRID:grid.12981.33) (ISNI:0000 0001 2360 039X); Guangdong Provincial Institution of Public Health, Guangzhou, China (GRID:grid.12981.33)
4 Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China (GRID:grid.508326.a) (ISNI:0000 0004 1754 9032); Guangdong Provincial Institution of Public Health, Guangzhou, China (GRID:grid.508326.a); Jinan University, School of Basic Medicine and Public Health, Guangzhou, China (GRID:grid.258164.c) (ISNI:0000 0004 1790 3548)
5 Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China (GRID:grid.508326.a) (ISNI:0000 0004 1754 9032); Guangdong Provincial Institution of Public Health, Guangzhou, China (GRID:grid.508326.a)
6 Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China (GRID:grid.508326.a) (ISNI:0000 0004 1754 9032); Guangdong Provincial Institution of Public Health, Guangzhou, China (GRID:grid.508326.a); Southern Medical University, School of Public Health, Guangzhou, China (GRID:grid.284723.8) (ISNI:0000 0000 8877 7471)
7 Guangdong Provincial Center for Disease Control and Prevention, Guangzhou, China (GRID:grid.508326.a) (ISNI:0000 0004 1754 9032); Guangdong Provincial Institution of Public Health, Guangzhou, China (GRID:grid.508326.a); Guangdong Pharmaceutical University, School of Public Health, Guangzhou, China (GRID:grid.411847.f) (ISNI:0000 0004 1804 4300)
8 Longhua District Center for Disease Control and Prevention, Shenzhen, China (GRID:grid.411847.f)
9 Nanshan District Center for Disease Control and Prevention, Shenzhen, China (GRID:grid.411847.f)