Respiratory viruses dynamics and interactions: ten years of surveillance in central Europe

Abstract

Background Lower respiratory tract infections are among the main causes of death. Although there are many respiratory viruses, diagnostic efforts are focused mainly on influenza. The Respiratory Viruses Network (RespVir) collects infection data, primarily from German university hospitals, for a high diversity of infections by respiratory pathogens. In this study, we computationally analysed a subset of the RespVir database, covering 217,150 samples tested for 17 different viral pathogens in the time span from 2010 to 2019. Methods We calculated the prevalence of 17 respiratory viruses, analysed their seasonality patterns using information-theoretic measures and agglomerative clustering, and analysed their propensity for dual infection using a new metric dubbed average coinfection exclusion score (ACES). Results After initial data pre-processing, we retained 206,814 samples, corresponding to 1,408,657 performed tests. We found that Influenza viruses were reported for almost the half of all infections and that they exhibited the highest degree of seasonality. Coinfections of viruses are frequent; the most prevalent coinfection was rhinovirus/bocavirus and most of the virus pairs had a positive ACES indicating a tendency to exclude each other regarding infection. Conclusions The analysis of respiratory viruses dynamics in monoinfection and coinfection contributes to the prevention, diagnostic, treatment, and development of new therapeutics. Data obtained from multiplex testing is fundamental for this analysis and should be prioritized over single pathogen testing.

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

“…In adjusted analyses, we observed positive correlations among pairs of viruses including RSV‐B, HBoV, HAdV, and HMPV—viruses that frequently cause lower respiratory tract infections in young children. This is consistent with a 10‐year study in central Europe, which found that HRV/HBoV, HRV/HAdV, RSV/HBoV, RSV/HAdV, RSV/HRV, and RSV/HCoV‐OC43 were the most prevalent co‐infections 27 . A study in central Europe that examined prevalence of 17 respiratory viruses over a 10‐year period also found that HRV/HBoV, HRV/HAdV, RSV/HBoV, RSV/HAdV, RSV/HRV, and RSV/HCoV‐OC43 were the most prevalent co‐infections 27 .…”

“…27 A study in central Europe that examined prevalence of 17 respiratory viruses over a 10-year period also found that HRV/HBoV, HRV/HAdV, RSV/HBoV, RSV/HAdV, RSV/HRV, and RSV/HCoV-OC43 were the most prevalent co-infections. 27 Children, particularly those <5 years, are known to be more susceptible to viral co-infections than adults possibly due to higher contact frequencies with peers and/or immune system immaturity. 28 Among children, IAV was negatively correlated with HAdV in three cities, and HRV, HBoV, HMPV, and RSV-B in Chongqing, which is in accord with several studies that reported shifts in the timing and severity of other respiratory infections following IAV epidemics.…”

Assessing respiratory viral exclusion and affinity interactions through co-infection incidence in a pediatric population during the 2022 resurgence of influenza and RSV

“…We also cannot distinguish from our analysis whether reduced probability of viral co-infection was due to, or contributed to, distinct trends in monthly incidence in nearly each viral category assessed over the study period. Due to the limited number of coinfections for some targets, such as individual parainfluenza viruses, coronaviruses, and influenza viruses, their incidence was combined by group, which prevents assessment for specific viruses within each category, such as some of those observed by Horemheb-Rubio et al (2022). For example, these authors found increases in the probability of interaction between specific HPIV 4 and influenza A(H3N2), as well as HPIV 1 and HCOV-NL63, while we found overall decrease in the interaction probability of these viral categories, but were not able to assess affinity between specific viruses within each category (Horemheb-Rubio et al, 2022).…”

“…By normalizing for the probability of mono-infection, when comparing the relative incidence of various forms of viral coinfection, we can therefore gain novel insights into viral interactions within human hosts that have thus far only been studied in animal models. Horemheb-Rubio et al (2022) conducted such an examination of respiratory viral interactions from 2010-2019 in Europe found relatively few synergistic viral interactions, such as between influenza H3N2 and parainfluenza virus 4 or HCoV-NL63 and parainfluenza virus 1, and predominantly viral exclusion between influenza and RSV, rhinovirus and most parainfluenza viruses (Horemheb-Rubio et al, 2022). However, such an analysis has not been conducted on a pediatric population, which have been shown to have higher rates of respiratory viral co-infection (Dao et al, 2021;Chen and Er, 2022;Krumbein et al, 2023), in general, nor been conducted since the beginning of the COVID-19 pandemic and therefore systematically assessed such viral co-infection dynamics in patients with SARS-CoV-2.…”

Hospitalisation trends from 2019 to 2023 illustrate the persistent resurgence of bronchiolitis in Italy

“…The relaxation of public health non‐pharmacological interventions may have contributed to the circulation of respiratory viruses other than RSV. Moreover, the complex epidemiology of bronchiolitis between 2021 and 2023 could have also been influenced by dynamic interactions between different viruses 5 . More studies are required to identify specific pathogens and evaluate their impact on disease severity and clinical outcomes.…”