Agricultural Detection of Norovirus and Hepatitis A Using Fecal Indicators: A Systematic Review.
Courtney P VictorKaren EllisFrederica LamarJuan S LeonPublished in: International journal of microbiology (2021)
Fresh-produce consumers may be at risk of pathogen infection due to fecal contamination of the agricultural environment. Indicators of fecal contamination may be used as a proxy to evaluate the potential presence of human pathogens, such as norovirus and hepatitis A, on agricultural samples. The objective of this systematic review was to determine whether the presence of human norovirus or hepatitis A was associated with microbial indicators in agricultural samples including fresh produce, equipment surfaces, and hands. Four databases (Embase, PubMed, Web of Science, and Agricola) were systematically searched and fifteen articles met inclusion and exclusion criteria. After data extraction, individual indicator-pathogen relationships were assessed using Cohen's Kappa coefficient. The level of agreement between norovirus with adenovirus was 0.09 (n = 16, 95% CI -0.05, 0.23), indicating poor agreement using Landis and Koch's criterion. Similarly, the Kappa coefficient between norovirus with E. coli (κ = 0.04, n = 14, 95% CI -0.05, 0.49) or total coliforms (κ = 0.03, n = 4, 95% CI -0.01, 0.02) was also poor. The level of agreement between hepatitis A with adenovirus (κ = -0.03, n = 3, 95% CI -0.06, 0.01) or fecal coliforms (κ = 0, n = 1, 95% CI 0, 0) was also poor. There were moderate relationships between hepatitis A with E. coli (κ = 0.49, n = 3, 95% CI 0.28, 0.70) and total coliforms (κ = 0.47, n = 2, 95% CI 0.47, 0.47). Based on these limited results, common indicator organisms are not strong predictors of the presence of norovirus and hepatitis A virus in the agricultural environment.
Keyphrases
- risk assessment
- human health
- heavy metals
- climate change
- systematic review
- endothelial cells
- escherichia coli
- drinking water
- nuclear factor
- big data
- magnetic resonance imaging
- randomized controlled trial
- health risk
- gram negative
- tyrosine kinase
- high intensity
- microbial community
- inflammatory response
- pseudomonas aeruginosa
- meta analyses
- staphylococcus aureus
- multidrug resistant
- pluripotent stem cells
- deep learning
- loop mediated isothermal amplification
- artificial intelligence
- electronic health record
- cystic fibrosis