Thesis title: Mathematical models for food safety and public health
This project of applied science was undertaken to provide evidence to face complex and multifaceted issues posed by the control of zoonotic foodborne pathogens and the related challenges for public health, veterinary medicine, food and environmental safety.
The thesis is divided in two different parts, each addressing a specific zoonotic pathogens: Hepatitis E virus (HEV) and Shiga toxin-producing E.coli (STEC). The main goal was to produce estimations to help targeting intervention strategies in livestock and in food production chain.
In Part I, a bottom-up risk assessment approach has been followed using original and existing data, to analyse the risk of consumers exposure to HEV through the consumption of contaminated food, following the from farm to fork approach, i.e. considering the two main compartments of the food production chain: the primary production level and the consumer level. In the pre-harvest block the HEV transmission dynamic was modeled to identify risk factors influencing the prevalence of HEV positive pigs entering the food-production chain at slaughtering. In the post-harvest block we compared several foodstuff to evaluate the risk of transmission of HEV to humans and to underline possible risk factors in the primary production that can lead to higher contamination of food products.
In Part II, the objective of our quantitative assessment were Shiga toxin-producing E.coli (STEC). In this case the availability of subtyping characterisation data of STEC isolated from different non-human sources and the complexity of transmission cycle of the STEC led us to choose a top-down approach, from the reported cases of infection in humans, through the food chain up to the primary source of STEC infection. This project was carried out within an ongoing European project (DISCOVER) were a original dataset were put together. We were able to adapt classical source attribution model to STEC using a novel approach for pathogenicity definition that allowed us to weigh the importance of the different sources in causation of human infection.