Monitoring of bivalve mollusk harvesting areas: the relevance of Salmonella spp.

The microbiological monitoring of bivalve mollusk harvesting areas in the Marche region is based on the parameters of Escherichia coli and Salmonella spp. However, Regulation EU/2019/627 stated criteria based on E. coli only to determine the health status of these areas. Therefore, the reason for Salmonella spp. monitoring, as provided in the Marche region, could be aimed at reducing the risk of placing on the market contaminated bivalve mollusks. This study, using the results of microbiological monitoring carried out in the Marche region from 2015 to 2022 and the methods based on Bayes' theorem and Poisson's distribution, evaluated the effectiveness and efficiency of Salmonella spp. monitoring in reducing the risk to the consumer. The results show that i) the use of a single sample unit significantly reduced the possibility of detecting non-compliance with the microbiological safety criterion; ii) the time taken to report positive results (average of approximately 10 days) did not allow the timely implementation of control measures; iii) the prevalence of positive outcomes was quite sporadic: a random trend of positivity is recognizable on a geographical and monthly basis for mussels and a geographical basis for striped clams; iv) considering the predictive value of E. coli against Salmonella spp., the specificity is very high and the negative predictive value versus Salmonella spp. would be >80%. In conclusion, the study shows that the monitoring of Salmonella spp. has a limited effect on reducing the risk to the consumer; however, in the cost/benefit assessment, other aspects not covered by this study should be considered.

Sample size planning and the statistical significance of official controls by sampling.

Acceptance sampling is important for food safety and is a relevant tool at production and official control levels, as it helps decision-making processes and verifies quality and food safety management. Generally, sampling plans are hypothesis tests of products that have been submitted for official appraisal and subsequent acceptance or rejection. The sample size is related to the set level of risk, the acceptable precision, and the tolerable misstatement size; therefore, sample size determination has a crucial role in setting up the accepted level of non-compliance and level of error. Using a simple predictive model based on combinatorics, this study showcases how sample size management can change the probability of rejecting good lots and/or accepting bad lots when the acceptance number is 0 (c=0). We showed that when c=0, a very high level of significance of the test corresponds to the high probability of rejecting a lot with an acceptable prevalence of defective items (type II error). We produced tables about the minimum sample size at different significance levels, which can be useful in the field. A paradigmatic example of the role of sample size in the acceptance-sampling plan is represented by the visual inspection for the detection of Anisakid larvae in fishery products. This study investigated this aspect and mainly referred to studies on the prevalence of larvae in farmed fish. We showed that, for lots ≥1000 items, the sample size is not strictly related to the lot size, but to draw a consistent control plan and reduce the variability in the clinical judgment, control authorities require a standardized approach. Because of this, the results on the prevalence of Anisakid larvae in farmed fish, if only based on sampling control plans, do not support a negligible risk statement, despite the claims reported in the EFSA opinion and several other studies.

European legislation and live bivalve molluscs: Are the criteria for microbiological safety matching with the criteria for sanitary classification of harvesting areas?

The European Union (EU) established the criteria for the classification of shellfish harvesting areas, based on the results of monitoring E. coli in shellfish. The EU also defined E. coli as a microbiological criterion for end product safety, based on a three-class sampling plan. Both criteria are based on the MPN method, a test with a statistical approach and in which different factors contribute to the variability of the outcomes. This theoretical study, based on combinatorics and Bayes' theorem for conditional probability, investigates the consistency between these two criteria and aims to determine the probability of obtaining false compliant and non-compliant results when applying the safety criterion test to shellfish placed on the market. The results show that in the second case, the probability of non-compliant outcomes does not appear negligible within a range between 10% and 50% in the different hypothesized scenarios, with a probability of false noncompliant outcomes over 10%. In addition, the Bayes' Theorem shows that Class A, or Class B areas (as allowed), could be the origin of non-compliant shellfish, with a not negligible frequency. Therefore, within the limits of the assumed working hypotheses, the safety criterion for E. coli, as described in Regulation EC/2073/2005, does not appear to be consistent and coordinated with the classification criteria stated in the Regulation EU/2019/627 and it is not closely related to the sanitary status of shellfish harvesting area.

Assessment of sampling methods about level of mercury in fish.

Mercury (Hg) seriously affects some sensitive subgroups of population and the detection of Hg content in fish and fishery products is one of the most important activities aimed at controlling their safety. In fact, Regulation (EC) No 1881/2006 set maximum levels for certain contaminants in foodstuffs and Regulation (EC) No 333/2007 laid down the methods of sampling and analysis for their control in foodstuffs. As Hg content highly varies among different fish species depending on a variety of factors and even among members of the same population, sampling methods play a crucial role in the accuracy, precision and statistical significance of Hg determination. By the use of an analysis method independent probabilistic model, based on the axioms of Kolmogorov's probability theory, this paper aims to assess the relationship between sampling methods set by Regulation (EC) No 333/2007 and the probability to detect compliant or non-compliant outcomes of Hg in fish.

Assessment of relationship between rainfall and Escherichia coli in clams (Chamelea gallina) using the Bayes Factor.

Consumption of bivalve shellfish harvested from water contaminated with sewage pollution presents a risk of human infections and targeting control measures require a good understanding of environmental factors influencing the transport and the fate of faecal contaminants within the hydrological catchments. Although there has been extensive development of regression models, the point of this paper, focused on the relationship between rainfall events and concentrations of Escherichia coli monitored in clams, was the use of a Bayesian approach, by the Bayes Factor. The study was conducted on clams harvested from the south coast of Marche Region (Italy), a coastal area impacted by continuous treated effluents, intermittent rainfalldependent untreated sewage spillage - as a consequence of stormwater overflowing - and rivers with an ephemeral flow regime. The work compared the different interpretation criteria of Bayes Factor, confirmed that E. coli concentrations in clams from the studied area varied in correlation with rainfall events, and demonstrated the effectiveness of Bayes Factor in the assessment of shellfish quality in coastal marine waters. However, it suggested that further investigations would be warranted to determine which environmental factors provide the better basis for accurate and timely predictions. Furthermore the gathered data could be useful, to the local authorities of Marche Region, in the definition of flexible monitoring programmes, taking into account the atmospheric events that could affect the correct functioning of sewage managing systems and the flow of tributary rivers.