Molecular Monitoring of Enteropathogens in Sewage During NATO Exercise Trident Juncture 2018: Potential Tool in Early Outbreak Warning?

Abstract

Outbreaks of gastrointestinal disease among military service personnel can have severe impact on operational effectivity and force readiness. Thus, early outbreak detection is critical to minimize spread. This pilot study aimed to explore field-based molecular screening of sewage as a supplemental tool in early outbreak warning before disease is diagnosed in personnel seeking medical care. Sewage from permanent (n = 3) and temporary (n = 3) military camps, hosting national and international military personnel, were sampled during the NATO Exercise TRJE18 taking place in southern Norway during fall 2018. Samples were screened for 22 gastrointestinal pathogens using multiplex PCR. Markers of multiple enteropathogens were detected in samples from all locations with some variations in diversity. Yersinia enterocolitica, pathogenic Escherichia coli, adenovirus, and Giardia were detected in sewage from all six camps during the exercise. Agent diversity seemed to increase with population size, regardless of nationality. Only a minor outbreak (n = 6) of norovirus was reported in one of the permanent camps. From the same camp, genetic markers of norovirus were detected in sewage 2 days before outbreak notification. No other outbreaks of gastrointestinal disease were reported during the exercise, indicating that markers of several enteropathogens can be normally found in sewage from healthy soldier populations. Thus, discriminating between true outbreaks and nonrelevant "background levels" would be of critical importance for correct decision-making in operational contexts. Molecular screening of sewage allows rapid detection of multiple gastrointestinal pathogens in biological waste from military camps. However, background levels of pathogens challenges interpretation of qualitative analyses in outbreak situations. As such, quantitative measures, as well as high-resolution sequence-based methods, which allows strain identification and broader target spectrum, should be further explored in future studies.