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

Abstract

BackgroundA 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.

Sentinel Enhanced Dengue Surveillance System — Puerto Rico, 2012–2022

“…Distinct seasonality in the circulation of respiratory viruses was observed, consistent with findings documented in the literature on virus-virus interactions and their effect on disease dynamics ( 58 – 60 ). A related study using SEDSS found distinct seasonal patterns in Puerto Rico, with respiratory viruses peaking in fall and winter, while arboviruses (e.g., dengue) peaked in summer and early fall, emphasizing the importance of recognizing these seasonal trends for accurate diagnosis and public health interventions in pediatric patients with AFI ( 10 ).…”

“…Viral interference, a phenomenon highlighted in previous research, plays a role in shaping the observed patterns ( 61 , 62 ). At the population level, viral interference might be induced when an outbreak caused by one virus hastens or delays an epidemic caused by another virus ( 58 , 60 ). These results indicate that the seasonality of IAV typically precedes that of IBV each year, consistent with documented interactions between influenza types and subtypes that might involve cross-immunity mechanisms ( 63 , 64 ).…”

“…The findings from this report revealed a high proportion of acute respiratory viral cases among children aged <5 years, including RSV, HPIV-3, HPIV-1, HAdV, and HMPV. Children, particularly those aged <5 years, have increased susceptibility to viral infections compared with adults, possibly because of higher contact frequencies with peers in school and child care settings, naïve immune systems, limited previous exposure, and a greater likelihood of medical care-seeking by parents ( 60 , 66 ).…”

Epidemiological Characteristics of Human Parainfluenza Viruses Infections — China, 2019–2023

“…The decrease may be attributed to the reduced presence of common co-infecting viruses due to NPIs. HRV was frequently identified as a co-infecting agent, showing a positive correlation with HPIVs ( 13 ). The high occurrence of HPIVs and HRV co-infections could be linked to their transmission modes via direct contact, which might have been facilitated by lower adherence to preventive measures during NPIs.…”