An evaluation of the impact of mitigation policies on health and the economy by managing social distancing during outbreaks.

The COVID-19 pandemic has necessitated various unavoidable social restrictions, leading to questions about the effectiveness of public emergency interventions and their impact economic growth. Block et al. (2020) conducted a notably study using an agent-based model to evaluate policies for reducing contact and demonstrated how choices in contact behavior can influence the rate and spread of the virus. However, their approach did not consider the economic consequences of these social restrictions. In response, we propose a set of strategies for governments to plan and evaluate policies during emergencies, aiming to contain infections while minimizing negative economic consequences. Our results indicate that there is no trade-off between containment strategies and economic output loss, making containment measures necessary policy instruments. However, potential trade-offs do emerge when selecting the most effective strategy. In this context, we propose and evaluate various policy alternatives to extreme "social distancing" measures, which can partially restore essential social interactions while preventing economic disasters induced by productivity losses.

A Combined method to model policy interventions for local communities based on people knowledge.

Policy interventions to promote innovative industries in peripheral regions are often hampered by lack of information on the functioning of the local socio-economic systems, due to their complexity. This might result in mismatches between policy objectives and the actual needs and capability of local communities. To overcome this drawback, it is crucial to obtain appropriate knowledge on the local system, which nevertheless is typically embedded in local actors' minds in uncodified and tacit form. Fuzzy Cognitive Maps (FCMs) have been employed to decode this kind of knowledge in a reproducible manner. However, some problems remain as to how to integrate the necessary vagueness of local actors' heuristic with experts' knowledge into a rational framework. The following methodology customization is proposed: • Combine the FCMs with the Discourse Analysis to obtain relevant narratives (i.e. concepts, visions, insights, etc.) needed to define system boundaries and variables. • Employ individual interviews - rather than a participatory approach - to define the causal relations among system variables. • Integrate tacit and uncodified knowledge embedded in local actors within experts' scientific knowledge.