Search

Several pufferfish species belonging to the Tetraodontidae family are currently present in the Mediterranean Sea. Since 2013 Lagocephalus sceleratus is increasingly reported also along Italian coasts, where other two species of less concern, Lagocephalus lagocephalus and Sphoeroides pachygaster , have also occured since a long time. This study represents one of the first attempts to sistematically describe the occurrence in the Mediterranean, and in particular along Italian coasts, of the three aforesaid species, in order to characterize an emerging public health hazard. Reports were searched in scientific articles and dedicated online databases. The following data were collected: number of specimens and type of record, geographical location and date of report, fish size, depth and type of seabed. Overall, at least 111079 individuals of the three species were found in the Mediterranean Sea, including 110237 specimens of L. sceleratus (since 2003), 126 of L. lagocephalus (1878–2017) and 716 of S. pachygaster (1979–2017). The evident differences confirm the invasive character of the toxic Lessepsian immigrant L. sceleratus , the species of main public health concern. Despite this species was recorded along Italian coasts in low numbers (0.08% of the total individuals of L. sceleratus ) and its current distribution is limited to southern regions, the picture could change rapidly. Moreover, the collected data show that most L. sceleratus specimens have a large size and are mainly caught by commercial fishing gears. These factors may increase the risk of this species entering the seafood chain with serious consequences for consumers’ health. Results suggest that the presence of L. sceleratus should be strictly monitored. Institutional measures should be implemented to inform people as regards a new hazard that has the potential to affect the Italian seafood chain. [ABSTRACT FROM AUTHOR]

Considerable research effort is invested in the development of evidence to help policy makers and industry deal with the challenges associated with existing and emerging food safety threats. This research aimed to elicit expert views regarding the relationship between the drivers of existing and emerging food safety risks, in order to facilitate their control and mitigation, and to provide the basis for further international policy integration. A Delphi approach involving repeated polling of n = 106 global food safety experts was adopted. The primary drivers of existing and emerging food safety risks were identified to be demographic change, economic driving forces, resource shortages, environmental driving forces, increased complexity of the food supply chain, water security and malevolent activities . The identification of socio-economic and biophysical drivers emphasises the need for a transdisciplinary and systems approach to food safety management and mitigation. The mitigation of hazards on a case-by-case basis is unlikely to have a major impact on food safety hazards but may have unintended effects (where positive or negative) across a broad spectrum of food safety issues. Rather a holistic or systems approach is required which can address both the intended and unintended effects of different drivers and their interactions. [ABSTRACT FROM AUTHOR]

The European Food Safety Authority (EFSA) established an Emerging Risks Exchange Network (EREN) to exchange information between EFSA and the Member states (MSs) on possible emerging risks for food and feed safety in 2010. The Network is composed of delegates from MSs and Norway designated through the Advisory Forum of EFSA and observers from the European Commission, EU pre-accession countries, the Food and Drug Administration of the USA and the Food and Agricultural Organisation of the United Nations. Through 2010 to 2014, the EREN met 12 times. The EREN discussed a total of 63 signals of potential emerging issues that were presented and assessed using a standard template developed by the Emerging Risks unit of EFSA (EMRISK). Out of these signals, 39 originated from EFSA, 24 from MSs. The issues discussed were mainly microbiological and chemical hazards, but also food safety issues as result of illegal activity, new consumer consumption trends, biotoxins, new technologies and processes, allergens, animal health, environmental pollution, new analytical methods, new food packaging technology and unknown hazards were on the agenda. Based on the available evidence, EREN recommended whether an issue should be considered emerging or not, and if it merited further consideration, such as generating data on the issue, starting a full risk assessment and/or consultation of other bodies. According to the emerging risks identification process set in place at EFSA, the issues discussed and found of relevance by EREN were sent to the EFSA's Scientific Committee Standing Working Group on Emerging Risks for final evaluation. With four case studies, i.e the zoonotic potential of Usutu virus, risk of ciguatera fish poisoning in EU, zoonotic aspects of illegally imported wildlife products and benefits and risks of 3D food printing, the method developed to preliminary assess signals of potential emerging issues is presented and discussed. [ABSTRACT FROM AUTHOR]

Abstract: During the last decades multiple unexpected and wide spread food safety incidents have occurred. The aim of this study is to learn from the past by studying the early emergence of historic food safety risks and apply these lessons for future early identification of emerging food safety risks. Information on the early signals preceding the emergence of thirteen diverse food safety incidents was collected, categorized and evaluated. It was found that in all cases early signals did precede the actual emergence of the incidents. The time interval between early signal and emergence varied between some months to multiple decades. Almost all early signals identified originated from two textual data sources: science and food safety authorities. It is concluded that in order to detect early signals semantic relationships between three key hazard concepts (food, substance and adverse health effect) must be extracted primarily from these data sources. A conceptual emerging food hazard model to visualize the concepts and relationships is proposed. When new information or a change in information is found for the hazard concepts a new food safety hazard may be emerging. Furthermore, we present the design of the Emerging Risk Identification Support system (ERIS) to support the risk manager with the identification of emerging risks. Some key factors for identifying emerging hazards (or risks) and the requirements of information systems to support this are discussed. With a functional system at hand and using science based information, the risk manager will be able to develop scenarios and, subsequently, the risk manager can initiate measures pro-actively to influence the development of the emerging risks. [Copyright &y& Elsevier]

Abstract: According to a recent report of the Intergovernmental Panel on Climate Change, the frequency of certain climate extremes is expected to increase under the influence of climate change. This review presents potential direct and indirect effects of such extremes as well as other severe weather and hydro-meteorological events on the occurrence of hazards in food produced by various agricultural systems. In addition, we review the applicability of early warning systems to warn of the development of food safety hazards induced by natural disasters, with climate-change-induced extreme events as case in point. Monitoring systems focused on food safety hazards may miss - or pick up with delay - the occurrence of new hazards or known hazards in food products in which they previously did not occur. We conclude that, by better use of the available information (being plant-, animal-, human disease-focused systems monitoring weather and other environmental conditions and/or systems collecting publications on the internet), the negative impact of severe natural events on food safety can be minimized. [Copyright &y& Elsevier]

The world market for food supplements is large and is driven by the claims of these products to, for example, treat obesity, increase focus and alertness, decrease appetite, decrease the need for sleep or reduce impulsivity. The use of illegal compounds in food supplements is a continuous threat, certainly because these compounds and products have not been tested for safety by competent authorities. It is therefore of the utmost importance for the competent authorities to know when new products are being marketed and to warn users against potential health risks. In this study, an approach is presented to detect new and unknown stimulants in food supplements using machine learning. Twenty new stimulants were identified from two different data sources, namely scientific literature applying word embedding on > 2 million abstracts and articles from formal and social media on the world wide web using text mining. The results show that the developed approach may be suitable to detect "unknowns" in the emerging risk identification activities performed by the competent authorities, which is currently a major hurdle. [ABSTRACT FROM AUTHOR]

The European Food Safety Authority (EFSA) develops methodologies and tools for the detection of emerging risks in food and feed. This includes the identification of drivers of emerging risks, such as food frauds, which requires innovative approaches. In this study, an unsupervised machine learning technique called the Latent Dirichlet Allocation (LDA) topic model, was applied on a media corpus in the view of detecting rapidly specific food fraud incidents in the media, i.e. on the Europe Media Monitor Medical Information System (EMM/MEDISYS). LDA topic model can explore large collection of documents discovering the themes associated with the corpus and organize and summarize text documents identifying topics comprised in them, where a topic is defined as a pattern of words with their probability to belong to it. As a specific food fraud incident, beeswax adulteration was taken as an example. Beeswax can be adulterated for financial gain, and, although it is a product from apiculture, it might enter the food chain when it is introduced as honeycomb in honey pots. With the beeswax example, a total of 2276 news articles were retrieved on EMM/MEDISYS and classified into 10 topics showing different levels of relatedness to beeswax adulteration. A manual screening of all articles allowed to validate the classification made by the topic model. The topics that were found the most relevant contained indeed articles on beeswax adulteration incidents reported from official sources. In addition, those topics contained signals of potential emerging risks in the cosmetic and food wrapping sectors. The remaining topics highlighted the emergence of new beeswax market opportunities which supported the identified signals. It is concluded that the LDA topic model can be used to process rapidly information in the media, support the definition of more specific food fraud filters on EMM/MEDISYS and be of direct use for all stakeholders involved in the monitoring, assessment and management of food frauds. • Adulteration of beeswax used in apiculture may pose emerging food safety concerns. • MedISys monitors efficiently beeswax adulteration events in the media. • Topic models for rapid identification of emerging risks on beeswax adulteration. [ABSTRACT FROM AUTHOR]