Comparative assessment of combined concentration and extraction methods for Influenza A and B virus detection in wastewater - Fretschner, Till; Zeisler, Edgar Elon; Scheller, Steffi; Aurenz, Andreas; Schneider, Beate; Lukas, Marcus; Braun, Ulrike; Greiner, Timo; Schumacher, Jakob; Selinka, Hans Christoph; Walther, Birgit; Kallies, René (Frontiers in Environmental Science, 2025)
Influenza, caused by Influenza A and B viruses, represents a significant global health burden due to recurrent seasonal epidemics and the risk of pandemics. To gauge the large volume of seasonal influenza cases, it may be helpful to complement classical surveillance systems with additional approaches such as wastewater-based epidemiology (WBE), which can aid in the early trend assessment of seasonal epidemics. WBE has emerged as a promising tool for population-level surveillance, enabling the detection of viral nucleic acids in wastewater and offering unique advantages over individual-based surveillance. This study evaluates the performance of different combinations of virus concentration (i.e., PEG precipitation, centrifugal filtration, and silica membrane filtration) together with two distinct RNA extraction methods for the detection of Influenza A and B viruses in wastewater. Composite samples from four wastewater treatment plants in North Germany were analyzed using precipitation, filtration, and automated extraction protocols. Method performance for six combinations was evaluated by quantitative recovery of viral RNA and a spike-and-recovery experiment. Recovery efficiencies were determined from controlled spiking experiments, which provide a standardised method of comparison but may not fully reflect the complexity of real wastewater samples, in which viral genomes may be fragmented and associated with solids. The combination of PureYield™ filtration and Maxwell® RSC extraction (PYC/EX1) consistently demonstrated the highest recovery rates for both Influenza virus A and B, achieving recovery efficiencies of up to 44.4% and 76.4%, respectively. This method also enabled reliable detection of low viral loads, which is critical for an early detection of rising incidence. Our findings demonstrate the importance of rigorous method evaluation to optimize WBE for influenza surveillance. By providing robust, sensitive, and reproducible protocols, this study highlights the potential of WBE to improve public health preparedness, enables timely interventions and reduces the spread of influenza viruses within communities.