Prospective Analysis of Seasonal Influenza - Viral Transmission and Evolution in the City of Basel, Switzerland

Overview

Influenza associated illness has a global annual impact with high morbidity and mortality. Transmission mechanisms and rates are under-investigated and overall poorly understood. This project aims to use epidemiological tools to understand the transmission and evolution of influenza viruses at an individual and population level within a small-scale city (Basel) through a combination of experimental, clinical and mathematical advances. The investigators aim to quantitatively characterize the viral transmission using novel molecular-epidemiological tools based on whole genome sequencing.

In this prospective observational study, paediatric and adult outpatients presenting with influenza-like illness will be enrolled at the emergency departments of the University Hospital Basel (USB), the paediatric University Hospital of both Basel (UKBB), or a network of family doctors (associated with Center of Primary Health Care). The Clinical Trial Unit at the University Hospital Basel will coordinated the recruitment process, collect data and sample all patients during the influenza season 2016/17. Samples will be collected such as whole blood, serum and DNA, nasopharyngeal swamps to diagnose influenza by polymerase chain reaction (PCR) assay and to determine colonization rates with Staphylococcus aureus and Streptococcus pneumonia. All samples except the first naso-pharyngeal swab for influenza diagnostics will be stored in a biobank and analysed in batches. Each influenza virus isolate will be sequenced using a "whole genome sequencing" approach. The viral transmission and evolution will be analysed using whole genome data for a detailed molecular and phylogenetic tree analysis, respectively. The epidemiological and geographical data will be incorporated into the phylogenetic model. Specific aims are: (i) to determine the impact of the most important epidemiological parameters, first focusing on the age profile, followed by children per house hold, and population density, on influenza transmission at an individual and population level, drawing on an analysis of baseline humoral immunity and whole genome sequencing data, (ii) to understand the viral evolution during seasonal epidemics, (iii) to develop dynamic mathematical models that are able to predict viral transmission and evolution based on the retrospective results from (i) and (ii) and to validate this model in future influenza seasons. To realize the interdisciplinary approach, the investigators will rely on the expertise in mathematical modelling of viral epidemiology and evolution and established geographical expertise, next generation sequencing, clinical epidemiology, and immunologic diagnostic techniques.