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Towards ultra-sensitive and rapid near-source wastewater-based epidemiology

  • University College London

Research output: Contribution to journalArticlepeer-review

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Abstract

Wastewater-based epidemiology is emerging as a powerful early-warning public health surveillance tool. However, gold-standard PCR necessitates transporting samples to laboratories, with significant reporting delays (24-72 h), prompting growing interest in rapid, near-source tests for resource-limited settings. Research has focused on gold nanoparticle dipsticks, but these typically lack sensitivity in wastewater. Herein, we explore two complementary nanomaterial based approaches, using SARS-CoV-2 as an exemplar: 1) visually-read carbon black dipsticks; 2) spin-enhanced fluorescent nanodiamond dipsticks, exploiting selective separation from background autofluorescence. The assay provides a 2-hour turnaround from sample preparation to result with minimal equipment and achieves a limit of detection down to 7 copies per assay. A pilot study with samples from the Welsh National WBE programme finds 80% sensitivity and 100% specificity for carbon black, and 100% sensitivity, specificity for nanodiamonds. A proof-of-concept lab-in-a-suitcase nanodiamond assay tests raw, unprocessed wastewater samples. These findings lay the foundations for near-source WBE early-warning quantum sensors in the environment.
Original languageEnglish
Article number8158
JournalNature Communications
Volume16
Early online date1 Sept 2025
DOIs
Publication statusE-pub ahead of print - 1 Sept 2025

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • COVID-19 - diagnosis - epidemiology - virology
  • Humans
  • Metal Nanoparticles - chemistry
  • Nanodiamonds - chemistry
  • Pilot Projects
  • SARS-CoV-2 - isolation & purification - genetics
  • Sensitivity and Specificity
  • Wastewater - virology
  • Wastewater-Based Epidemiological Monitoring

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