A novel path for microbial risk assessment towards sustainable food systems: employing AI-based risk management concepts from Stochastic Finance

The United Nations’ Sustainable Development Goals, adopted by the United Nations in 2015, are committed to the ambitious 2030 Agenda aiming to end hunger and assure health and well-being, while promoting the protection of aquatic and terrestrial ecosystems. A key cornerstone in reaching these goals is the Farm to Fork Strategy of the European Green Deal. It aims to halve food waste per capita, promote healthy foods and preserve biodiversity, while increasing organic farming to 25% of total farmland and reducing chemical pesticides by 50% by 2030. These efforts started a disruptive transformation process towards fair, healthy and environmentally friendly agricultural production and food systems. At the same time, novel concepts balancing food security and food safety are urgently needed to minimize food waste, while at the same time shielding consumers from foodborne infections and intoxications. Such concepts need to leverage the benefits of circular economy, while taking into consideration health costs, biodiversity costs, and food waste. Current microbial food safety concepts are not equipped to take these complex factors into consideration. A striking example for the failure of traditional microbial risk assessment concepts is the Bacillus cereus group. The B. cereus group of bacterial organisms comprises different Bacillus species that vary widely in toxicity for both humans and animals including insect vectors. B. cereus sensu stricto is recognized as an important foodborne cause of infections and intoxications and B. anthracis leads to fatal anthrax cases in humans and animals. In contrast, other members of the B. cereus group are widely used in crop production and applied to foods as biopesticides or used as feed additives in animal husbandry. In addition, large strips of land are treated with biopesticides based on B. thuringiensis for mosquito control. The safety of residues of these agents on food and a potential spillover of biopesticides is increasingly controversially discussed. As species differentiation is difficult and not routinely done by outbreak investigation teams, it is unclear to which extent foodborne outbreaks due to B. thuringiensis biopesticides occur. In addition, whole genome sequence analyses have led to a collapse of traditional B. cereus group taxonomy and risk categorization. A new path towards innovative microbial risk assessment concepts must move from taxonomy to risk and can be created using the B. cereus group as a role model for future microbial risk assessment. Risk concepts from other disciplines such as stochastic Finance that are designed to integrate a multitude of complex factors can enable a more comprehensive approach to microbial risk assessment. This project leverages the expertise of an interdisciplinary consortium to answer the pivotal question: Can risk assessment concepts from Stochastic Finance improve microbial risk assessment? To this end, the project uses the B. cereus group as a role model for translating risk concepts from Finance to a microbial context. We will develop a comprehensive new microbial risk assessment scheme that contributes to the 2030 Agenda by protecting human health and ecosystem biodiversity. We also expect that our novel risk assessment concept could provide a substantial contribution to the reduction of food waste and thus could be an important step towards sustainable and resilient food systems and a circular economy.

Sinergia

Zentrum für Pathobiologie

Scuola universitaria professionale della Svizzera italiana
Funktion: Partner
Abteilung: Laboratorio di Microbiologia
Eidgenössische Technische Hochschule Zürich
Funktion: Partner
Abteilung: Stochastic Finance Group & ETH Risk Center
Universität Zürich
Funktion: ProjektkoordinationGesamt
Abteilung: Institut für Lebensmittelsicherheit