Peer-reviewed veterinary case report
Exploring the Use of Passive Samplers for the Surveillance of Avian Influenza Viruses in Wetlands: A Laboratory and Field Validation Study.
- Journal:
- Food and environmental virology
- Year:
- 2025
- Authors:
- Panzarin, Valentina et al.
- Affiliation:
- Division of Comparative Biomedical Sciences · Italy
- Species:
- bird
Abstract
Surveillance in wild birds is essential for the timely detection of high pathogenicity avian influenza (HPAI) strains. As flocks congregate in large numbers in wetlands and may potentially contaminate the environment with pathogens, the monitoring of such water bodies represents an attractive opportunity to complement animal testing and to improve surveillance for avian influenza. To increase sensitivity, water concentration is often required but available methods based on (ultra)filtration and precipitation are mostly limited by the use of pumping equipment and by the need to identify the representative sample volumes. In contrast, passive samplers (PS) offer a cost-effective and scalable solution that requires basic devices for the deployment of adsorbent materials and minimal training for their installation in the field. This study evaluated nine materials for their virus adsorption efficiency in brackish and freshwater. Cotton gauze, nitrocellulose, and nylon showed the best performance across different deployment times, with the highest recovery after 24 h. Shorter (3 h) and longer (7 days) deployments also proved effective, accommodating different sampling regimens according to the logistical needs. Importantly, PS revealed their efficacy in adsorbing also deteriorated virions or in dynamic ecosystems subjected to changes in water volumes. Field trials in wetlands corroborated laboratory findings and demonstrated that PS allowed detecting avian influenza virus (AIV, including HPAI strains) genome in water bodies, yielding consistent results with active surveillance in wild birds. By offering a simple, cost-effective, and versatile solution, PS represent a promising tool for environmental AI monitoring and can successfully complement existing avian influenza surveillance activities.
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Search related cases →Original publication: https://pubmed.ncbi.nlm.nih.gov/40618304/