# Wastewater as Sentinel for Emerging Viral Diseases in Livestock: A Systematic Review

## TL;DR

This paper reviews how wastewater can be used to detect emerging viruses in livestock, offering early warnings to protect food security and public health.

## Contribution

The study provides a systematic review and conceptual framework for standardizing wastewater-based surveillance in livestock systems.

## Key findings

- Livestock wastewater-based surveillance detects emerging viral pathogens before clinical outbreaks.
- Economic losses from viral outbreaks like H5N1 and ASFV are substantial, with indirect costs from biosecurity and supply-chain issues.
- A multifactorial framework links environmental and agricultural factors to pathogen emergence dynamics.

## Abstract

The accelerating frequency of emerging infectious diseases (EIDs) in livestock poses a significant threat to global food security, as well as to animal and public health. While wastewater-based surveillance (WBS) has advanced significantly for human health surveillance, its application to livestock production systems remains fragmented and lacks standardization. This review synthesizes current evidence on livestock wastewater-based surveillance (L-WBS) as an early-warning sentinel for emerging viral pathogens, evaluating their dynamics, economic impacts, biosecurity measures, and One Health implications. Existing studies demonstrate that L-WBS effectively detects emerging viral pathogens in agricultural effluent, swine manure, and municipal wastewater systems serving livestock regions, frequently preceding clinical outbreak recognition. We further conceptualized a multifactorial framework linking environmental drivers such as climate and ecological disruption and agricultural intensification to pathogen emergence dynamics. Economic assessments show substantial direct losses (approximately US$ 950 per H5N1-infected dairy cow and US$ 25.9 billion in African swine fever virus (ASFV)-related damages across China) alongside indirect costs from biosecurity implementation, workforce disruption, and supply-chain instability. We recommend prioritizing methodological standardization through unified sampling and extraction protocols, integration of next-generation sequencing for genomic surveillance, and cross-sectoral policy frameworks to operationalize L-WBS as a global early-warning infrastructure for mitigating zoonotic spillover and livestock-dependent community resilience.