A seafood risk tool for assessing and mitigating chemical and pathogen hazards in the aquaculture supply chain.

Intricate links between aquatic animals and their environment expose them to chemical and pathogenic hazards, which can disrupt seafood supply. Here we outline a risk schema for assessing potential impacts of chemical and microbial hazards on discrete subsectors of aquaculture-and control measures that may protect supply. As national governments develop strategies to achieve volumetric expansion in seafood production from aquaculture to meet increasing demand, we propose an urgent need for simultaneous focus on controlling those hazards that limit its production, harvesting, processing, trade and safe consumption. Policies aligning national and international water quality control measures for minimizing interaction with, and impact of, hazards on seafood supply will be critical as consumers increasingly rely on the aquaculture sector to supply safe, nutritious and healthy diets.

Evaluation of the protection against norovirus afforded by E. coli monitoring of shellfish production areas under EU regulations.

EC Regulation 854/2004 requires the classification of bivalve mollusc harvesting areas according to the faecal pollution status of sites. It has been reported that determination of Escherichia coli in bivalve shellfish is a poor predictor of norovirus (NoV) contamination in individual samples. We explore the correlation of shellfish E. coli data with norovirus presence using data from studies across 88 UK sites (1,184 paired samples). We investigate whether current E. coli legislative standards could be refined to reduce NoV infection risk. A significant relationship between E. coli and NoV was found in the winter months (October to February) using data from sites with at least 10 data pairs (51 sites). We found that the ratio of arithmetic means (log10 E. coli to log10 NoV) at these sites ranged from 0.6 to 1.4. The lower ratios (towards 0.6) might typically indicate situations where the contribution from UV disinfected sewage discharges was more significant. Conversely, higher ratios (towards 1.4) might indicate a prevalence of animal sources of pollution; however, this relationship did not always hold true and so further work is required to fully elucidate the factors of relevance. Reducing the current class B maximum (allowed in 10% of samples) from 46,000 E. coli per 100 g (corresponding NoV value of 75750 ± 103) to 18,000 E. coli per 100 g (corresponding NoV value of 29365 ± 69) reduces maximum levels of NoV by a factor of 2.6 to 1; reducing the upper class B limit to 100% compliance with 4,600 E. coli per 100 g (corresponding NoV value of 7403 ± 39) reduces maximum levels of NoV by a factor of 10.2 to 1. We found using the UK filtered winter dataset that a maximum of 200 NoV corresponded to a maximum of 128 ± 7 E. coli per 100 g. A maximum of 1,000 NoV corresponded to a maximum of 631 ± 14 E. coli per 100 g.