Our goal with this WP is to work on a common modelling framework that can be used across regions (both cities and rural areas) with a vision of weaving outcomes together for regional and global comparative analyses. Simulation models that are able to more clearly articulate how actions on a micro level are going to have an impact on a macro level can be used to design solutions at a macro level and vice versa.
The applicability for policy makers will be key and the produced model will be as easy to handle as possible. Formally, the model will make it possible to i) characterise and prioritise the determinants of food system evolution and ii) assess the impacts of public actions or changes in behaviours. Our approach will directly address the challenge of building an architecture that takes into account the heterogeneity of the nature of the information and the scales of relations.
- To identify factors influencing dietary choice and behaviour.
- To determine the environmental, social, economic and health impacts of dietary choice and behaviour.
- To co-construct a modelling framework to understand the barriers and enabling factors affecting dietary choice and behaviour.
- To establish the impact on health and sustainability of the solutions and strategies co-constructed on the living labs for promoting sustainable and healthy dietary behaviours and lives.
Primary data will be qualitative and make it possible to finely characterise trends observed on dietary choice and behaviour in small areas. Secondary data will be collected from multiple freely accessible sources including: official databases, surveys, reports and scientific studies at European, national, regional and local levels. Secondary data will be quantitative and georeferenced enabling characterisation of external factors and represent current socio-spatial trends and phenomena over large areas. This data will be analysed to quantify the effect of geography, socio-economic status (SES), behaviour and cultural factors on dietary choice and behaviour of target groups, particularly vulnerable subgroups in selected study cases across Europe.
We will also use structural estimates modelling, to co-construct a modelling framework to understand the barriers and enabling factors affecting dietary choice and behaviour. Structural estimates modelling is dependent on the association between observed (manifest) and unobservable (latent) variables, i.e., the association between internal and external factors influencing dietary choice and behaviour at multiple levels of decision making, including policy impacts. We will assess trade-offs and synergies between environment, social, economic and health impacts from empirical data collected through study cases.
Using the outputs of WP4 (community-based solutions), WP5 (technology-based solutions) and WP7 (policy recommendations), we will conduct scenario modelling by upscaling and combining solutions to quantify the overall improvements to social (i.e., inequalities), health (i.e., DALYs saved), environmental (i.e., greenhouse gas emissions reductions) and economic (i.e., cost/benefit of different solutions) at the local, regional, national and EU levels. Policymakers will have access to modelling frameworks which will be integrated in an open-source simulation library. Through simulations, we will understand linkages, negative externalities, positive synergies, and optimal trade-offs between implementing solutions in the nexus of health and sustainability. Policymakers can effectively assess the acceptance of different policy strategies identified and the impact of different strategies to arbitrate between goals.