ISME Communications (Oct 2022)

The one health perspective to improve environmental surveillance of zoonotic viruses: lessons from COVID-19 and outlook beyond

  • Mats Leifels,
  • Omar Khalilur Rahman,
  • I-Ching Sam,
  • Dan Cheng,
  • Feng Jun Desmond Chua,
  • Dhiraj Nainani,
  • Se Yeon Kim,
  • Wei Jie Ng,
  • Wee Chiew Kwok,
  • Kwanrawee Sirikanchana,
  • Stefan Wuertz,
  • Janelle Thompson,
  • Yoke Fun Chan

DOI
https://doi.org/10.1038/s43705-022-00191-8
Journal volume & issue
Vol. 2, no. 1
pp. 1 – 9

Abstract

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Abstract The human population has doubled in the last 50 years from about 3.7 billion to approximately 7.8 billion. With this rapid expansion, more people live in close contact with wildlife, livestock, and pets, which in turn creates increasing opportunities for zoonotic diseases to pass between animals and people. At present an estimated 75% of all emerging virus-associated infectious diseases possess a zoonotic origin, and outbreaks of Zika, Ebola and COVID-19 in the past decade showed their huge disruptive potential on the global economy. Here, we describe how One Health inspired environmental surveillance campaigns have emerged as the preferred tools to monitor human-adjacent environments for known and yet to be discovered infectious diseases, and how they can complement classical clinical diagnostics. We highlight the importance of environmental factors concerning interactions between animals, pathogens and/or humans that drive the emergence of zoonoses, and the methodologies currently proposed to monitor them—the surveillance of wastewater, for example, was identified as one of the main tools to assess the spread of SARS-CoV-2 by public health professionals and policy makers during the COVID-19 pandemic. One-Health driven approaches that facilitate surveillance, thus harbour the potential of preparing humanity for future pandemics caused by aetiological agents with environmental reservoirs. Via the example of COVID-19 and other viral diseases, we propose that wastewater surveillance is a useful complement to clinical diagnosis as it is centralized, robust, cost-effective, and relatively easy to implement.