Climate change is expected to worsen food security and increase foodborne diseases through supply chain interactions and behavioural changes. Studies identify foodborne pathogens that are critical in the climate context, that will significantly increase the burden of foodborne disease in Europe and in Canada. For several years, the link between direct factors of climate change to microbial behaviour has been explored. Quantitative risk assessments to predict the effects of climate change on food safety are more challenging. A recent review outlines criteria for quantitative methods linking climate projections to the impact on food microbiology.
Studies explore the “farm to fork” aspect, with the current processes in their approach.
Nevertheless, the impact of climate change on food safety is a global challenge. EFSA's CLEFSA project identifies generic factors affecting food safety, including social behaviours, societal changes, new food sources, consumption patterns or agriculture practices, that are intertwined with climate change.
The public is becoming increasingly concerned and affected by climate change. Consumers have adjusted their habits in response to climate-related factors for several years. This can be voluntary, like reducing waste or choosing package-free items to combat climate change. It can also occur unintentionally when extreme heat or floods affect food production, availability, and prices.
Studying consumer practices is challenging due to diverse data sources and data volume. Some data can be used to assess health risks, as the 2017 French study on food consumption. However, consumer habits evolve rapidly, making it difficult to gather information in real-time to stay relevant.
Surveys can be conducted while focusing on specific issues or groups. Furthermore, scientific literature or newspapers can also be explored to identify emerging trends. Text mining methods could be useful for automating analyses and information extraction from large quantities of text from a variety of sources. Advanced automatic natural language processing (NLP) techniques can help to identify emerging trends, detect newly consumed foods based on their frequency of occurrence, and extract useful information to understand consumer preferences better.
The impact of changes in food consumption linked to climate change has rarely been studied, let alone quantified. These new consumption practices therefore require a more thorough risk assessment to protect the health of consumers.