Affiliation:
1. Department of Biostatistics, College of Public Health and Health Professions & Emerging Pathogens Institute University of Florida Gainesville Florida USA
2. Division of Infectious Disease Key Laboratory of Surveillance and Early‐Warning on Infectious Diseases, Chinese Center for Disease Control and Prevention Beijing China
3. Department of Biostatistics and Bioinformatics Emory University Atlanta Georgia USA
4. State Key Laboratory of Pathogen and Biosecurity Beijing Institute of Microbiology and Epidemiology Beijing China
5. Department of Statistics, Franklin College of Arts and Sciences University of Georgia Athens Georgia USA
Abstract
AbstractBackgroundA 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.MethodsOur 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.ResultsOf 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.ConclusionsThere 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.
Funder
National Institutes of Health
Innovative Research Group Project of the National Natural Science Foundation of China
National Mega Project on Major Infectious Disease Prevention
Subject
Infectious Diseases,Public Health, Environmental and Occupational Health,Pulmonary and Respiratory Medicine,Epidemiology