The sentinel sewers: wastewater surveillance as an AMR early warning system
1
Department of Molecular Biology and Genomics, Redeemers University, Ede/Osun State, Nigeria
Popul. Med. 2026;8(Supplement Supplement 1):A227
ABSTRACT
INTRODUCTION:
Traditional antimicrobial resistance surveillance relies on clinical isolates from symptomatic patients, a method that often captures data too late for preventative intervention. Wastewater-Based Epidemiology (WBE) has emerged as a non-invasive, cost-effective alternative that monitors the collective metagenome of entire populations. By sampling urban effluent, researchers can detect resistance genes before they manifest as clinical outbreaks. This review evaluates the transition of WBE from a COVID-19 tracking tool to a permanent pillar of global AMR surveillance.
METHODS:
This study synthesizes findings from global pilot programs conducted between 2022 and 2025, specifically focusing on the Global Sewage Surveillance Project and the EU-WISH (EU Wastewater Integrated Surveillance for Public Health) initiative. We analyzed the efficacy of HT-qPCR and Metagenomic Next-Generation Sequencing (mNGS) in identifying resistomes across diverse urban landscapes. The review compares wastewater-derived gene abundance with corresponding clinical hospital admissions records.
RESULTS:
Synthesis of 2024–2025 data indicates that WBE can identify Carbapenemase-Producing Enterobacteriaceae (CPE) in a community 10–14 days before clinical reports emerge. Recent longitudinal studies showed a 92% correlation between the abundance of the blaNDM-1 gene in wastewater and subsequent hospitalizations. Furthermore, detection of the colistin-resistance gene mcr-1 in effluent samples was found to be 30 times more sensitive than individual patient screenings in low-prevalence areas. From a policy perspective, WBE was found to reduce surveillance costs by approximately 65% compared to traditional clinical swabbing, while the sentinel AI algorithm successfully reduced false-positive resistance spikes to under 5% through adaptive baseline modeling.
CONCLUSIONS:
Wastewater surveillance represents a paradigm shift in AMR management, moving from reactive treatment to proactive environmental monitoring. By providing a real-time map of community resistance, WBE allows for targeted antibiotic stewardship in specific high-risk zones.
Traditional antimicrobial resistance surveillance relies on clinical isolates from symptomatic patients, a method that often captures data too late for preventative intervention. Wastewater-Based Epidemiology (WBE) has emerged as a non-invasive, cost-effective alternative that monitors the collective metagenome of entire populations. By sampling urban effluent, researchers can detect resistance genes before they manifest as clinical outbreaks. This review evaluates the transition of WBE from a COVID-19 tracking tool to a permanent pillar of global AMR surveillance.
METHODS:
This study synthesizes findings from global pilot programs conducted between 2022 and 2025, specifically focusing on the Global Sewage Surveillance Project and the EU-WISH (EU Wastewater Integrated Surveillance for Public Health) initiative. We analyzed the efficacy of HT-qPCR and Metagenomic Next-Generation Sequencing (mNGS) in identifying resistomes across diverse urban landscapes. The review compares wastewater-derived gene abundance with corresponding clinical hospital admissions records.
RESULTS:
Synthesis of 2024–2025 data indicates that WBE can identify Carbapenemase-Producing Enterobacteriaceae (CPE) in a community 10–14 days before clinical reports emerge. Recent longitudinal studies showed a 92% correlation between the abundance of the blaNDM-1 gene in wastewater and subsequent hospitalizations. Furthermore, detection of the colistin-resistance gene mcr-1 in effluent samples was found to be 30 times more sensitive than individual patient screenings in low-prevalence areas. From a policy perspective, WBE was found to reduce surveillance costs by approximately 65% compared to traditional clinical swabbing, while the sentinel AI algorithm successfully reduced false-positive resistance spikes to under 5% through adaptive baseline modeling.
CONCLUSIONS:
Wastewater surveillance represents a paradigm shift in AMR management, moving from reactive treatment to proactive environmental monitoring. By providing a real-time map of community resistance, WBE allows for targeted antibiotic stewardship in specific high-risk zones.
| eISSN: | 2654-1459 |
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