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Updated: Jan 10, 2026
High-throughput Detection Method for Influenza Virus
Published on: February 4, 2012
High-Resolution Wastewater-Based Surveillance of Three Influenza Seasons (2022-2025) Reveals Distinct Seasonal
Jessica Neusser1,2, Astrid Zierer2, Anna Riedl2
1Institute of Infectious Diseases and Tropical Medicine, LMU University Hospital, Ludwig-Maximilians-Universität (LMU) München, 80802 Munich, Germany.
Abstract:
In the Northern Hemisphere, annual waves of influenza disease with varying degrees of spread and severity are observed each winter. With wastewater-based surveillance (WBS), including both centralized (one wastewater treatment plant, WWTP) and decentralized (three sewers) sampling, we aimed to detect differences in influenza viral copy numbers in wastewater over time, to investigate (sub)-community transmission within a city. A total of 313 grab/spot and composite samples were collected in Munich, Germany, during three consecutive influenza seasons (2022/23, 2023/24, and 2024/25) and were analyzed for influenza A virus (IAV) and influenza B virus (IBV) nucleic acids using digital droplet PCR (ddPCR). IAV and IBV wastewater copy numbers and citywide reported influenza cases showed strong correlations in both sampling approaches, suggesting the decentralized approach to be a reliable indicator of infection trends across the city. The three influenza seasons analyzed differed significantly in terms of their seasonal distribution, for example, exhibiting a strong co-circulation of IAV and IBV only in the 2024/25 season. Only with wastewater analysis, we reveal a reporting delay of influenza A cases at the beginning of the 2023/24 season. Higher influenza copy numbers were detected in sewer samples compared to the WWTP influent, likely due to viral decay. The study underscores the potential of influenza WBS to enable detection of seasonal onset early, identify local transmission patterns, and reveal underreporting in routine surveillance systems.
Insights
Wastewater surveillance effectively tracks influenza A and B virus trends, correlating strongly with reported cases. This method offers early detection of seasonal onset and reveals underreporting in public health surveillance systems.
Area of Science:
- Environmental microbiology
- Public health surveillance
- Virology
Background:
- Influenza causes annual epidemics in the Northern Hemisphere.
- Wastewater-based surveillance (WBS) offers a promising tool for monitoring infectious diseases.
- Understanding community transmission requires robust surveillance methods.
Purpose of the Study:
- To compare centralized and decentralized WBS for influenza detection.
- To investigate influenza A virus (IAV) and influenza B virus (IBV) transmission dynamics.
- To assess WBS for early detection and underreporting of influenza.
Main Methods:
- Collected 313 wastewater samples from Munich over three influenza seasons (2022/23-2024/25).
- Analyzed samples using digital droplet PCR (ddPCR) for IAV and IBV nucleic acids.
- Compared wastewater data with citywide reported influenza cases.
Main Results:
- Strong correlations observed between wastewater viral copy numbers and reported influenza cases for both sampling methods.
- Decentralized sampling (sewers) showed higher viral loads than centralized (WWTP), likely due to decay.
- Revealed a reporting delay for influenza A cases in the 2023/24 season.
- Identified unique seasonal patterns, including IAV and IBV co-circulation in 2024/25.
Conclusions:
- Wastewater-based surveillance is a reliable indicator of citywide influenza infection trends.
- WBS enables early detection of seasonal influenza onset and local transmission patterns.
- WBS can identify underreporting in traditional public health surveillance systems.
