Continued high incidence of children with severe influenza A(H1N1)pdm09 admitted to paediatric intensive care units in Germany during the first three post-pandemic influenza seasons, 2010/11–2012/13

Background Previous influenza surveillance at paediatric intensive care units (PICUs) in Germany indicated increased incidence of PICU admissions for the pandemic influenza subtype A(H1N1)pdm09. We investigated incidence and clinical characteristics of influenza in children admitted to PICUs during the first three post-pandemic influenza seasons, using active screening. Methods We conducted a prospective surveillance study in 24 PICUs in Bavaria (Germany) from October 2010 to September 2013. Influenza cases among children between 1 month and 16 years of age admitted to these PICUs with acute respiratory infection were confirmed by PCR analysis of respiratory secretions. Results A total of 24/7/20 influenza-associated PICU admissions were recorded in the post-pandemic seasons 1/2/3; incidence estimates per 100,000 children were 1.72/0.76/1.80, respectively. Of all 51 patients, 80 % had influenza A, including 65 % with A(H1N1)pdm09. Influenza A(H1N1)pdm09 was almost absent in season 2 (incidence 0.11), but dominated PICU admissions in seasons 1 (incidence 1.35) and 3 (incidence 1.17). Clinical data was available for 47 influenza patients; median age was 4.8 years (IQR 1.6–11.0). The most frequent diagnoses were influenza-associated pneumonia (62 %), bronchitis/bronchiolitis (32 %), secondary bacterial pneumonia (26 %), and ARDS (21 %). Thirty-six patients (77 %) had underlying medical conditions. Median duration of PICU stay was 3 days (IQR 1–11). Forty-seven per cent of patients received mechanical ventilation, and one patient (2 %) extracorporeal membrane oxygenation; 19 % were treated with oseltamivir. Five children (11 %) had pulmonary sequelae. Five children (11 %) died; all had underlying chronic conditions and were infected with A(H1N1)pdm09. In season 3, patients with A(H1N1)pdm09 were younger than in season 1 (p = 0.020), were diagnosed more often with bronchitis/bronchiolitis (p = 0.004), and were admitted to a PICU later after the onset of influenza symptoms (p = 0.041). Conclusions Active screening showed a continued high incidence of A(H1N1)pdm09-associated PICU admissions in the post-pandemic seasons 1 and 3, and indicated possible underestimation of incidence in previous German studies. The age shift of severe A(H1N1)pdm09 towards younger children may be explained by increasing immunity in the older paediatric population. The high proportion of patients with underlying chronic conditions indicates the importance of consistent implementation of the current influenza vaccination recommendations for risk groups in Germany

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

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