Zhang Suyi, Liang Hongbiao, Xu Jiahao, Chen Bingzhi, Zheng Xiang, Lin Haijiang, Wang Weibing, Yao Ye
Shanghai Institute of Infectious Disease and Biosecurity, School of Public Health, Fudan University, Shanghai 200032, China; Key Laboratory of Public Health Safety of Ministry of Education, Fudan University, Shanghai 200032, China.
Taizhou Center for Disease Control and Prevention, Taizhou, Zhejiang 318000, China.
J Infect. 2025 Aug;91(2):106556. doi: 10.1016/j.jinf.2025.106556. Epub 2025 Jul 22.
It is evident that respiratory viruses exhibit a discernible spatial and temporal transmission pattern, and severe acute respiratory syndrome (SARS-CoV-2) has profoundly altered the dynamics of these pathogens. The viral interference has led to greater complexity in the surveillance. This study aims to examine the spatiotemporal transmission patterns of respiratory viruses in the post-pandemic era and assess the impact of virus interactions on virus outbreaks.
A multi-pathogen surveillance program was conducted in Taizhou, Zhejiang Province, commencing in 2021. The study utilized spatial-temporal modeling to analyze four respiratory viruses, namely SARS-CoV-2, influenza, human rhinovirus (HRV) and respiratory syncytial virus (RSV), with the objective of identifying interaction patterns and their lagged effects.
Each virus is influenced to varying degrees by economic and traffic-related factors. Even after adjusting for spatiotemporal variables and baseline factors, significant interactions were observed between different viruses. These interactions were not always bidirectional and demonstrated specific patterns and lag times. RSV outbreaks are influenced by HRV, but the converse is not true. The effect of SARS-CoV-2 on influenza manifested 12 weeks later, whereas influenza affected SARS-CoV-2 with only 1-week lag. Potential competitive relationships between viruses were also evident in their spatial distribution, such as the nearly opposite high- and low-prevalence areas of influenza and HRV. Furthermore, the coexistence of multiple pathogens resulted in substantial alterations to virus diffusion patterns and epidemic duration.
This study integrates multi-pathogen surveillance with spatiotemporal modeling, confirming that the viral interference relationships derived from population-level incidence data are consistent with experimental findings, thereby revealing potential interactions between SARS-CoV-2 and other viruses. Our findings confirm that SARS-CoV-2 has altered transmission patterns of respiratory viruses and highlight the critical role of viral interactions in shaping epidemic dynamics.
显然，呼吸道病毒呈现出明显的时空传播模式，而严重急性呼吸综合征冠状病毒2（SARS-CoV-2）已深刻改变了这些病原体的传播动态。病毒间的干扰使得监测工作变得更加复杂。本研究旨在探讨大流行后时代呼吸道病毒的时空传播模式，并评估病毒相互作用对病毒爆发的影响。
2021年起在浙江省台州市开展了一项多病原体监测项目。该研究利用时空建模分析了四种呼吸道病毒，即SARS-CoV-2、流感病毒、人鼻病毒（HRV）和呼吸道合胞病毒（RSV），目的是确定相互作用模式及其滞后效应。
每种病毒都受到经济和交通相关因素的不同程度影响。即使在调整了时空变量和基线因素后，不同病毒之间仍观察到显著的相互作用。这些相互作用并非总是双向的，而是呈现出特定的模式和滞后时间。呼吸道合胞病毒的爆发受人类鼻病毒影响，但反之则不然。SARS-CoV-2对流感的影响在12周后显现，而流感对SARS-CoV-2的影响仅滞后1周。病毒之间潜在的竞争关系在其空间分布上也很明显，例如流感病毒和人鼻病毒的高流行区和低流行区几乎相反。此外，多种病原体的共存导致病毒传播模式和流行持续时间发生了实质性改变。
本研究将多病原体监测与时空建模相结合，证实了从人群水平发病率数据得出的病毒干扰关系与实验结果一致，从而揭示了SARS-CoV-2与其他病毒之间的潜在相互作用。我们的研究结果证实，SARS-CoV-2改变了呼吸道病毒的传播模式，并突出了病毒相互作用在塑造疫情动态中的关键作用。
