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. 2023 Nov 2;9(11):e21716.
doi: 10.1016/j.heliyon.2023.e21716. eCollection 2023 Nov.

Risk valuation for E. coli contamination in Campania region shellfish from 2016 to 2021

Affiliations

Risk valuation for E. coli contamination in Campania region shellfish from 2016 to 2021

Roberta Pellicanò et al. Heliyon. .

Abstract

This study set out to assess the microbiological quality of shellfish collected over a six-year period of time in the Campania Region Sea. A total of 1459 samples were examined in order to determine whether Escherichia coli was present. To investigate potential correlations between the E. coli counts and environmental parameters (salinity, pH, dissolved oxygen, seawater temperature, turbidity, rainfall) and pollution variables (density and distance of heavy and light discharges), data were gathered. With only roughly 19% of the samples not meeting European and Italian criteria (E. coli counts more than 230 most likely number MPN per 100 g of pulp and intravalvar liquid), the results showed that the microbiological quality of the shellfish was good. A correlation between microbial contamination, season, rainfall, and dissolved oxygen was found using statistical analysis. However, the discharge density along the coast per spatial unit (a 200 × 200 MT cell), which was determined using the "quartic" Kernel function, showed found to be the primary factor determining the E. coli concentration in the shellfish. An increase in rain millimeters was found to be associated with a higher risk of heightened E. coli contamination, according to a model that was fitted to assess the probability of detecting a higher E. coli count in connection to environmental parameters. This outcome could be explained by the discharge density near the coast as well as the increased availability of coliforms, particularly E. coli, and nutrients during periods of heavier rainfall.

Keywords: E. coli; Food safety; Multivariate logistic regression model; Shellfish.

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Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Fig. 1
Fig. 1
Forest plot for prevalence per cities.
Fig. 2
Fig. 2
Forest plot for prevalence per farms.
Fig. 3
Fig. 3
Kernel density of heavy discharges along the Pozzuoli coast.
Fig. 4
Fig. 4
Kernel density of heavy discharges along the Gulf of Naples.
Fig. 5
Fig. 5
Kernel density of heavy discharges in Caserta.
Fig. 6
Fig. 6
Kernel density of light discharges along the Pozzuoli coast.
Fig. 7
Fig. 7
Kernel density of light discharges along the Gulf of Naples.
Fig. 8
Fig. 8
Kernel density of light discharges in Caserta.

References

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Further reading

    1. Angioni S.A., Giansante C., Ferri N. The clam (Chamelea gallina): evaluation of the effects of solid suspended in seawater on bivalve shellfish. Vet. Ital. 2010;46:101–106. - PubMed
    1. Carella F., Aceto S., Mangoni O., Mollica M.P., Cavaliere G., Trinchese G., Aniello F., De Vico G. Assessment of the health status of mussels Mytilus galloprovincialis along the Campania coastal areas: a multidisciplinary approach. Front. Physiol. 2018;9:683. doi: 10.3389/fphys.2018.00683. PMID: 29946265; PMCID: PMC6005891. - DOI - PMC - PubMed
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    1. Lee R.J., Silk R. Sources of variation of Escherichia coli concentrations in bivalve molluscs. J. Water Health. 2013;(1):78–83. doi: 10.2166/wh.2012.114. PMID: 23428551. - DOI - PubMed
    1. Lees D. Viruses and bivalve shellfish. Int. J. Food Microbiol. 2000;59:81–116. - PubMed

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