https://doi.org/10.4081/ijfs.2026.15116
Integrating uncertainty into official control decisions: Bayesian risk-based decision support for the safe reopening of live bivalve mollusk harvesting areas
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.
Published: 12 June 2026
The safety of live bivalve mollusks (LBM) depends on complex interactions between pathogen ecology, environmental variability, and regulatory monitoring outcomes. Conventional compliance-based reopening decisions for classified harvesting areas often rely on limited sampling data and deterministic thresholds, without formally accounting for prior scientific evidence or uncertainty. This study proposes a Bayesian decision-support framework that integrates peer-reviewed evidence on pathogen occurrence, accumulation dynamics, and persistence in LBM into a probabilistic regulatory model for area classification and reopening decisions.
A structured literature review was conducted to identify quantitative evidence describing the prevalence and behavior of bacterial, viral, and protozoan hazards in bivalve mollusks, including Escherichia coli, Salmonella spp., norovirus, hepatitis A virus, and protozoan parasites. This evidence was translated into literature-informed prior distributions representing baseline contamination probability and environmental risk conditions. A conjugate Bayesian β-binomial model was applied to integrate official monitoring data with prior knowledge, generating posterior distributions of the probability that microbial contamination exceeds acceptable thresholds. Decision criteria were established according to precautionary regulatory tolerance levels, expressed as the posterior probability of unacceptable contamination.
Numerical case studies and Monte Carlo simulations demonstrated how the proposed framework supports transparent and risk-based regulatory decisions: scenarios included reopening under low residual risk, persistent closure under high posterior probability of exceedance and borderline situations requiring additional sampling. Integration of environmental evidence and pathogen-specific persistence (notably viral contamination with slow depuration dynamics) substantially influenced posterior risk estimates and decision outcomes. The results demonstrate that identical monitoring outcomes may lead to different regulatory decisions depending on prior ecological evidence and uncertainty quantification.
The proposed Bayesian decision framework integrating ecological evidence provides a scientifically robust and transparent tool for competent authorities managing LBM harvesting areas. By formally incorporating prior scientific knowledge, environmental indicators, and uncertainty, the framework operationalizes the precautionary principle while enabling adaptive, evidence-based reopening decisions consistent with European Union food safety legislation.
Downloads
Baker-Austin C, Oliver JD, Alam M, Ali A, Waldor MK, Qadri F, Martinez-Urtaza J, 2018. Vibrio spp. infections. Nature Rev Dis Primers 4:8. DOI: https://doi.org/10.1038/s41572-018-0005-8
Bernardo JM, Smith AFM, 1994. Bayesian Theory. Wiley, Chichester, UK. DOI: https://doi.org/10.1002/9780470316870
Campos CJA, Lees DN, 2014. Environmental transmission of human noroviruses in shellfish waters. Appl Environ Microbiol 80:3552-61. DOI: https://doi.org/10.1128/AEM.04188-13
Codex Alimentarius Commission, 2013. Principles and guidelines for the conduct of microbiological risk management (CAC/GL 63-2007). FAO/WHO, Rome, Italy.
Desdouits M, Reynaud Y, Philippe C, Le Guyader FS, 2023. A comprehensive review for the surveillance of human pathogenic microorganisms in shellfish. Microorganisms 11:2218. DOI: https://doi.org/10.3390/microorganisms11092218
European Commission, 2019. Commission Implementing Regulation (EU) 2019/627 of 15 March 2019 laying down uniform practical arrangements for the performance of official controls on products of animal origin intended for human consumption. In: Official Journal, L131, 17/05/2019.
European Commission, 2021. Guidance document for competent authorities on the implementation of official controls on live bivalve molluscs. Brussels, Belgium: European Commission.
European Parliament, Council of the European Union, 2004. Regulation (EC) No 853/2004 laying down specific hygiene rules for food of animal origin. In: Official Journal, L139, 30/04/2004.
EFSA BIOHAZ Panel, 2011. Scientific opinion on an update on the present knowledge on the occurrence and control of foodborne viruses. EFSA J 9:2190. DOI: https://doi.org/10.2903/j.efsa.2011.2190
EFSA BIOHAZ Panel, 2012. Scientific opinion on norovirus in oysters: methods, limits and control options. EFSA J 10:2500. DOI: https://doi.org/10.2903/j.efsa.2012.2500
EFSA, 2019. Analysis of the European baseline survey of norovirus in oysters. EFSA J 17:e05762. DOI: https://doi.org/10.2903/j.efsa.2019.5762
EFSA BIOHAZ Panel, 2024. Scientific Opinion on Public health aspects of Vibrio spp. related to the consumption of seafood in the EU. EFSA J 22:e8896. DOI: https://doi.org/10.2903/j.efsa.2024.8896
Ekundayo TC, Ijabadeniyi OA, 2024. Systematic review and meta-analysis of human bocavirus as food safety risk in shellfish. Sci Rep 14:26968. DOI: https://doi.org/10.1038/s41598-024-75744-z
FAO, WHO, 2021. Technical guidance for the development of the growing area aspects of Bivalve Mollusc Sanitation Programmes. Second edition. Food Safety and Quality Series No.5A. Rome, Italy.
Fehrenbach GV, Murphy E, Pogue R, Carter F, Clifford E, Major I, 2024. Comprehensive analysis and assessment of exposure to enteric viruses and bacteria in shellfish. Mar Environ Res 196:106404. DOI: https://doi.org/10.1016/j.marenvres.2024.106404
Gelman A, Carlin JB, Stern HS, Dunson DB, Vehtari A, Rubin D, 2014. Bayesian data analysis, 3rd ed. Chapman & Hall/CRC, Boca Raton, FL, USA. DOI: https://doi.org/10.1201/b16018
Greenland S, 2006. Bayesian perspectives for epidemiological research. Int J Epidemiol 35:765-75. DOI: https://doi.org/10.1093/ije/dyi312
Kim M, Rueda L, Shapiro K, 2024. Protozoa in bivalve shellfish: gaps and opportunities to better understand risk to consumers. Current Opinion Food Sci 55:101104. DOI: https://doi.org/10.1016/j.cofs.2023.101104
Johnson AA, Ott MQ, Dogucu M, 2022. Bayes rules! An introduction to applied Bayesian modeling. 1st ed. Chapman & Hall, Boca Raton, FL, USA. DOI: https://doi.org/10.1201/9780429288340
Le Guyader FS, Atmar RL, Le Pendu J, 2012. Transmission of viruses through shellfish: when specific ligands come into play. Current Opinion Virol 2:103-10. DOI: https://doi.org/10.1016/j.coviro.2011.10.029
Lees D, 2000. Viruses and bivalve shellfish. Int J Food Microbiol 59:81-116. DOI: https://doi.org/10.1016/S0168-1605(00)00248-8
Maalouf H, Zakhour M, Le Pendu J, Le Saux JC, Atmar RL, Le Guyader FS, 2011. Distribution and seasonal variation of norovirus in oysters. Appl Environ Microbiol 77:5621-30. DOI: https://doi.org/10.1128/AEM.00148-10
Malham SK, Taft H, Farkas K Ladd CJT, Seymour M, Robins PE, Jones DL, McDonald JE, Le Vay L, Jones L, 2025. Multi-scale influences on Escherichia coli concentrations in shellfish: from catchment to estuary. Environ Pollution 366:125476. DOI: https://doi.org/10.1016/j.envpol.2024.125476
Nemes K, Person S, Simonsson M, 2023. Hepatitis A virus and hepatitis E virus as food- and waterborne pathogens—transmission routes and methods for detection in food. Viruses 15:1725. DOI: https://doi.org/10.3390/v15081725
Okamoto H, 2026. Shellfish as a potential source of hepatitis e virus: epidemiological evidence, biological plausibility, and research gaps. Viruses 18:220. DOI: https://doi.org/10.3390/v18020220
Pavlova A, Kocikova B, Dolinska MU, Jackova A, 2025. Hepatitis E virus in the role of an emerging food-borne pathogen. Microorganisms 13:885. DOI: https://doi.org/10.3390/microorganisms13040885
Ranta J, Maijala R, Peltola J, 2015. Bayesian evaluation of microbiological criteria for food safety. Risk Analysis 35:1456-67.
Savini F, Giacometti F, Tomasello F, Pollesel M, Piva S, Serraino A, De Cesare A, 2021. Assessment of the impact on human health of the presence of norovirus in bivalve molluscs: what data do we miss? Foods 10:2444. DOI: https://doi.org/10.3390/foods10102444
Schets FM, van den Berg HHJL, Engels GB, Lodder WJ, de Roda Husman AM, 2007. Cryptosporidium and Giardia in shellfish. Int J Food Microbiol 120:14-9.
Simental L, Martinez-Urtaza J, 2008. Climate patterns governing the presence and permanence of Salmonellae in coastal areas of Bahia de Todos Santos, Mexico. Appl Environ Microbiol 74:5918-24. DOI: https://doi.org/10.1128/AEM.01139-08
Spiegelhalter DJ, Abrams KR, Myles JP, 2004. Bayesian approaches to clinical trials and health-care evaluation. Wiley, Chichester, UK. DOI: https://doi.org/10.1002/0470092602
Tene SD, Diouara AAM , Sané S, Coundoul S, 2025. Hepatitis E virus (HEV) infection in the context of the one health approach: a systematic review. Pathogens 14:704. DOI: https://doi.org/10.3390/pathogens14070704
Van der Voet H, Slob W, 2007. Integration of probabilistic exposure assessment and probabilistic hazard characterization. Risk Analysis 27:351-71. DOI: https://doi.org/10.1111/j.1539-6924.2007.00887.x
CRediT authorship contribution
Cesare Ciccarelli: study concept, statistical analysis and writing - original draft. Angela Marisa Semeraro, Vittoria Di Trani: writing – review and editing. Michela Conquista: methodology, writing – review and editing. Elena Ciccarelli: study concept, writing – review and editing.
How to Cite
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
PAGEPress has chosen to apply the Creative Commons Attribution NonCommercial 4.0 International License (CC BY-NC 4.0) to all manuscripts to be published.