Liu Bin, Wang Zhongliang, Lu Shanshan, Qi Zhongtian, Zhang Zhijie, Luan Jie, Ba Jianbo
Naval Medical Center, Naval Medical University, No.880 Xiangyin Road, Yangpu District, Shanghai, China.
Department of Mathematics and Physics, Faculty of Military Medical Services, Naval Medical University, Shanghai, China.
Sci Rep. 2025 Mar 24;15(1):10169. doi: 10.1038/s41598-025-91308-1.
The reported new confirmed cases of Coronavirus Disease 2019 (COVID-19) nowadays have diminished in their usefulness for assessing the pandemic situation. This study aimed to discover the correlation of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) variants recorded by Nextstrain clade and PANGO lineage and the number of new confirmed cases. Percent stacked area charts were utilized to display their development trends. 31 and 1452 variants were named according to Nextstrain clade and PANGO lineage, respectively. The branch step value maintained a stable increase by linear regression analysis. The changing trend in SARS-CoV-2 variants (PANGO lineage) correlated negatively with the number of new confirmed COVID-19 cases through Spearman rank correlation coefficient (17/06/2020-17/11/2021, ρ=-0.387, P < 0.01; 15/12/2021-11/01/2023, ρ=-0.458, P < 0.01). The proportion and composition of dominant virus variants had regional discrepancies, but some also fluctuated. The speed and quantity of SARS-CoV-2 variants objectively reflect the characteristics of the COVID-19 pandemic and viral dissemination in the population even without valuable data of reported new confirmed cases. The SARS-CoV-2 variation may be a better tool for epidemic monitoring and early-warning in the low epidemic state.
目前，报告的新型冠状病毒肺炎（COVID-19）新增确诊病例对于评估疫情形势的作用已有所减弱。本研究旨在探究Nextstrain分支和PANGO谱系记录的严重急性呼吸综合征冠状病毒2（SARS-CoV-2）变体与新增确诊病例数之间的相关性。使用百分比堆积面积图来展示它们的发展趋势。分别根据Nextstrain分支和PANGO谱系命名了31个和1452个变体。通过线性回归分析，分支步长值保持稳定增长。通过Spearman等级相关系数发现，SARS-CoV-2变体（PANGO谱系）的变化趋势与COVID-19新增确诊病例数呈负相关（2020年6月17日至2021年11月17日，ρ = -0.387，P < 0.01；2021年12月15日至2023年1月11日，ρ = -0.458，P < 0.01）。优势病毒变体的比例和组成存在地区差异，但也有一些波动。即使没有报告新增确诊病例的有价值数据，SARS-CoV-2变体的速度和数量也客观地反映了COVID-19大流行和病毒在人群中的传播特征。SARS-CoV-2变异可能是低流行状态下疫情监测和预警的更好工具。
