Linking digital surveillance and in-depth virology to study clinical patterns of viral respiratory infections in vulnerable patient populations
Patrick E. Obermeier,
Albert Heim,
Barbara Biere,
Elias Hage,
Maren Alchikh,
Tim Conrad,
Brunhilde Schweiger,
Barbara A. Rath
Affiliations
Patrick E. Obermeier
Vienna Vaccine Safety Initiative, Pediatric Infectious Diseases, Berlin, Germany; Charité University Medical Center, Department of Pediatrics, Berlin, Germany; UMR Chrono-environnement, Université Bourgogne Franche-Comté, Besançon, France
Albert Heim
National Reference Laboratory for Adenoviruses, Hannover Medical School, Hannover, Germany
Barbara Biere
National Reference Centre for Influenza, Robert Koch-Institute, Berlin, Germany
Elias Hage
National Reference Laboratory for Adenoviruses, Hannover Medical School, Hannover, Germany
Maren Alchikh
Vienna Vaccine Safety Initiative, Pediatric Infectious Diseases, Berlin, Germany; Charité University Medical Center, Department of Pediatrics, Berlin, Germany; UMR Chrono-environnement, Université Bourgogne Franche-Comté, Besançon, France
Tim Conrad
Department of Mathematics and Computer Science, Freie Universität Berlin, Berlin, Germany
Brunhilde Schweiger
National Reference Centre for Influenza, Robert Koch-Institute, Berlin, Germany
Barbara A. Rath
Vienna Vaccine Safety Initiative, Pediatric Infectious Diseases, Berlin, Germany; Charité University Medical Center, Department of Pediatrics, Berlin, Germany; UMR Chrono-environnement, Université Bourgogne Franche-Comté, Besançon, France; Corresponding author
Summary: To improve the identification and management of viral respiratory infections, we established a clinical and virologic surveillance program for pediatric patients fulfilling pre-defined case criteria of influenza-like illness and viral respiratory infections. The program resulted in a cohort comprising 6,073 patients (56% male, median age 1.6 years, range 0–18.8 years), where every patient was assessed with a validated disease severity score at the point-of-care using the ViVI ScoreApp. We used machine learning and agnostic feature selection to identify characteristic clinical patterns. We tested all patients for human adenoviruses, 571 (9%) were positive. Adenovirus infections were particularly common and mild in children ≥1 month of age but rare and potentially severe in neonates: with lower airway involvement, disseminated disease, and a 50% mortality rate (n = 2/4). In one fatal case, we discovered a novel virus: HAdV-80. Standardized surveillance leveraging digital technology helps to identify characteristic clinical patterns, risk factors, and emerging pathogens.
