Passive Sampler Technology for Viral Detection in Wastewater-Based Surveillance: Current State and Nanomaterial Opportunities

Viruses. 2023 Sep 16;15(9):1941. doi: 10.3390/v15091941.

Abstract

Although wastewater-based surveillance (WBS) is an efficient community-wide surveillance tool, its implementation for pathogen surveillance remains limited by ineffective sample treatment procedures, as the complex composition of wastewater often interferes with biomarker recovery. Moreover, current sampling protocols based on grab samples are susceptible to fluctuant biomarker concentrations and may increase operative costs, often rendering such systems inaccessible to communities in low-to-middle-income countries (LMICs). As a response, passive samplers have emerged as a way to make wastewater sampling more efficient and obtain more reliable, consistent data. Therefore, this study aims to review recent developments in passive sampling technologies to provide researchers with the tools to develop novel passive sampling strategies. Although promising advances in the development of nanostructured passive samplers have been reported, optimization remains a significant area of opportunity for researchers in the area, as methods for flexible, robust adsorption and recovery of viral genetic materials would greatly improve the efficacy of WBS systems while making them more accessible for communities worldwide.

Keywords: nanostructured materials; passive samplers; solid surface adsorption; wastewater-based surveillance; waterborne viruses.

Publication types

  • Review
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Environmental Monitoring / methods
  • Technology
  • Wastewater
  • Wastewater-Based Epidemiological Monitoring*
  • Water Pollutants, Chemical* / analysis

Substances

  • Wastewater
  • Water Pollutants, Chemical

Grants and funding

This research was funded by the Fundación FEMSA project entitled “Unidad de respuesta rápida al monitoreo de COVID19 por agua residual” (grant number NA) and Tecnologico de Monterrey through the project Challenge-Based Research Funding Program 2022 (Muestreador Pasivo I026-IAMSM005-C4-T1-T).