PREVISION aims to prevent foodborne human norovirus infections by conducting a translational research focused on providing predictive tools to assess viral infectivity needed to implement preventive and control strategies along the food chain.

Food safety has become an issue of crucial importance to public health. In this scenario, human noroviruses (HuNoVs) represent the leading cause of viral acute gastroenteritis (AGE) worldwide and cause 120 million cases attributed to contaminated water and food.

Most of the foodborne outbreaks have been linked to shellfish, fresh and frozen berries and leaf greens, even any food item could be potentially implicated depending on production, handling, processing, and storage conditions, since HuNoVs cross-contamination can occur at any point the food chain, from the farm to fork.

Given the increased awareness on foodborne viruses and the impact that different factors (globalization of the market, increased international travel, consumer demands, changes in food-processing, pathogen evolution, etc.) may have on the occurrence and severity of foodborne outbreaks, it is clear that priority needs to be given to expanding the knowledge on potential preventive and control measures along the food chain.

In this sense, the efforts of the ISO scientific committee CEN/TC 275 conducted to the recent publication of the ISO 15216-1 standard norm that specify methods for the quantification of levels of hepatitis A virus (HAV) and norovirus genogroup I (GI) and II (GII) RNA in food (including soft fruit, leaf, stem and bulb vegetables, bottled water, bivalve mollusks) and food contact surfaces. The detection is reliant on the reverse-transcriptase polymerase chain reaction (RT-PCR), which represents the golden standard for food and environmental virology studies. Although RT-qPCR is highly sensitive, it detects the viral RNA of both infectious and inactivated viral particles, potentially overestimating the amount of infectious viruses.

Recently, a novel three-dimensional cell culture technique based on stem-cell-derived human intestinal enteroids (HIEs) (referred as mini-gut), retaining the hallmarks of the in-vivo intestinal epithelium, has been described and HuNoVs was finally proved to replicate on this system. Following studies confirmed the system to be robust, which is currently the only system to directly measure HuNoVs infectivity.

However, this system result to be sophisticated, highly expensive, extremely technically demanding, and so far not standardized. As a matter of facts, it has not being used yet in food and environmental virology.

To overcome these limitations, the generation of robust data set on viral infectivity measured by the innovative HIEs system and its correlation to traditional and widely used methods (i.e. surrogates, molecular and binding techniques) constitutes the key strategy of this project proposal, PREVISION.

In fact, this project pursues the goal of preventing foodborne HuNoVs infections by providing predictive tools to assess the efficacy of common treatments applied in the food supply chain in a comprehensive vision, from farm to fork.

PREVISION uses an innovative perspective to address the need of food industry to prevent foodborne infections by reducing the risk of exposure to infectious HuNoVs. To this end, preventive and control strategies applied for HuNoVs inactivation in critical points along the food supply chain will be evaluated for the first time. In addition, the emphasis of PREVISION on providing predictive tools is innovative and could be further improved for its use in different settings.