Toward a quality-managed operational architecture for wastewater surveillance of zoonotic and emerging pathogens.

Authors

Rajendra Kothavade

Published in

Applied and environmental microbiology. Pages e0095026. Jul 10, 2026. Epub Jul 10, 2026.

Abstract

Wastewater surveillance provides population-level insights into infectious disease dynamics independent of clinical testing, with increasing relevance for zoonotic and emerging pathogens, such as avian influenza A (H5 subtypes), influenza B, respiratory syncytial virus, measles, and mpox. This minireview integrates quality management system (QMS) principles across the entire wastewater surveillance workflow, including sample collection, laboratory analysis, data interpretation, and reporting, to ensure reliability, reproducibility, and cross-site comparability. The review presents the novel framework of wastewater surveillance as a structured operational architecture, highlighting how biological variability, sampling design, analytical workflows, and interpretive strategies interact within a unified system. It provides decision-oriented guidance for interpreting heterogeneous and low-prevalence signals, integrating system-level metadata, tiered analytical approaches (reverse transcription quantitative PCR [RT-qPCR], digital PCR, sequencing), and strategies for linking molecular measurements to actionable public health decisions. Additionally, it addresses the incorporation of One Health perspectives and multi-level governance-from municipal infrastructure to national coordination-to enhance early detection, outbreak mitigation, and coordinated response. By translating complex environmental and molecular inputs into a coherent operational framework, this work equips public health agencies and researchers to design resilient, scalable, and evidence-based wastewater surveillance systems that support early warning and effective management of emerging infectious disease threats.

PMID:
42429767
Bibliographic data and abstract were imported from PubMed on 10 Jul 2026.

Read full publication at:
Please sign in to see all details.

Stats

1-terrible, 9-excellent. How would you rate this publication? Sign in in to submit your rating.

Post a comment

You need to be signed in to post comments. You can sign in here.

Comments

There are no comments yet.