TraceMap supports national authorities in identifying food safety threats and improving EU-wide coordinated response. A pilot version of TraceMap was recently used to support the investigation of globally distributed cereulide-contaminated infant formula.
The theme, “From Burden to Solutions—Safe Food Everywhere,” stresses the role of evidence-based action, promoting the forthcoming updated WHO global foodborne disease estimates as a data source to inform targeted food safety and public health interventions.
A literature review conducted by Greenpeace concluded that heating food in plastic packaging—even ready-to-heat meals labeled as “microwave-safe” or “oven-safe”—may significantly increase the migration of microplastics and chemical additives into food.
Despite having Listeria-positive samples that matched the outbreak strain via whole genome sequencing (WGS), which prompted an FDA Import Alert and a company recall for the suspected vehicle of illness, FDA did not disclose the specific product or any of the firms implicated.
Elevated levels of certain metals and the presence of commonly used disinfectants were found to inactivate Salmonella vaccines administered to poultry via drinking water.
The California Longitudinal Study, a five-year environmental study of California’s Central Coast produce-growing region, identified wildlife, livestock, and surface water as potential contributors to the persistence and movement of Shiga toxin-producing Escherichia coli (STEC).
Maximum reductions in norovirus infectivity occurred rapidly once temperatures reached 60 °C (140 °F). The findings could help inform improved thermal processing recommendations for foodborne norovirus.
Marking the first time an SQF Code is introduced as a fully digital experience, the newly released Edition 10 is designed to strengthen audit credibility, reinforce food safety culture, and provide clearer signals around risk.
In his remarks on a recent Joe Rogan Experience podcast episode, Secretary Kennedy also suggested FDA is considering a new approach to front-of-pack nutrition labeling.
The researchers positioned the machine learning model as a low-cost complement to traditional testing workflows, helping dairy processors enhance food safety while targeting laboratory resources.
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