Interactions among acute respiratory viruses in Beijing, Chongqing, Guangzhou, and Shanghai, China, 2009–2019

• Type of Material: Article
• Authors: Zachary J. Madewell, University of Florida; Li-Ping Wang, Chinese Center for Disease Control and Prevention; Natalie Exner Dean, Emory University; Hai-Yang Zhang, Beijing Institute of Microbiology and Epidemiology; Yi-Fei Wang, Beijing Institute of Microbiology and Epidemiology; Xiao-Ai Zhang, Beijing Institute of Microbiology and Epidemiology; Wei Liu, Beijing Institute of Microbiology and Epidemiology; Wei-Zhong Yang, Chinese Center for Disease Control and Prevention; Ira M. Longini, University of Florida; Goerge F. Gao, Chinese Center for Disease Control and Prevention; Zhong-Jie Li, Chinese Center for Disease Control and Prevention; Li-Qun Fang, Beijing Institute of Microbiology and Epidemiology; Yang Yang, University of Georgia
• Language: English
• Date: 2023-11-12
• Publisher: John Wiley and Sons
• Publication Version: Final Published Version
• Copyright Statement: © 2023 The Authors. Influenza and Other Respiratory Viruses published by John Wiley & Sons Ltd.
• License: Creative Commons Attribution 4.0 International
• Final Published Version (URL): https://doi.org/10.1111/irv.13212
• Title of Journal or Parent Work: Influenza and Other Respiratory Viruses
• Volume: 17
• Issue: 11
• Start Page: e13212
• Grant/Funding Information: This work was supported by the National Natural Science Funds grant 91846302 (L. Q. F. and L. W.), the China Mega‐Project on Infectious Disease Prevention grant 2018ZX10713001 (L. Q. F., L. P. W., W. Z. Y., G. F. G., and Z. J. L.), and the National Institutes of Health R56 AI148284 (Y. Y., I. L., and N. E. D.).
• Keywords: viral synergism; acute respiratory infections; pathogen interactions; co‐infection; viral interference
• Research Categories: Health Sciences, Immunology; Health Sciences, Public Health; Health Sciences, Epidemiology

Abstract

Background A viral infection can modify the risk to subsequent viral infections via cross‐protective immunity, increased immunopathology, or disease‐driven behavioral change. There is limited understanding of virus–virus interactions due to lack of long‐term population‐level data. Methods Our study leverages passive surveillance data of 10 human acute respiratory viruses from Beijing, Chongqing, Guangzhou, and Shanghai collected during 2009 to 2019: influenza A and B viruses; respiratory syncytial virus A and B; human parainfluenza virus (HPIV), adenovirus, metapneumovirus (HMPV), coronavirus, bocavirus (HBoV), and rhinovirus (HRV). We used a multivariate Bayesian hierarchical model to evaluate correlations in monthly prevalence of test‐positive samples between virus pairs, adjusting for potential confounders. Results Of 101,643 lab‐tested patients, 33,650 tested positive for any acute respiratory virus, and 4,113 were co‐infected with multiple viruses. After adjusting for intrinsic seasonality, long‐term trends and multiple comparisons, Bayesian multivariate modeling found positive correlations for HPIV/HRV in all cities and for HBoV/HRV and HBoV/HMPV in three cities. Models restricted to children further revealed statistically significant associations for another ten pairs in three of the four cities. In contrast, no consistent correlation across cities was found among adults. Most virus–virus interactions exhibited substantial spatial heterogeneity. Conclusions There was strong evidence for interactions among common respiratory viruses in highly populated urban settings. Consistent positive interactions across multiple cities were observed in viruses known to typically infect children. Future intervention programs such as development of combination vaccines may consider spatially consistent virus–virus interactions for more effective control.