Using a previously developed agent-based artificial intelligence simulation platform (EnerPol) coupled with 'Big Data,' the evolution and containment of COVID-19 in Switzerland is examined. The EnerPol platform has been used in a broad range of case studies in different sectors in all of Europe, USA, Japan, South Korea and sub Saharan Africa over the last 10 years. In the present study, the entire Swiss population (8.57 million people), including cross-border commuters, and the entire

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Over the next 35 years, the population of Switzerland is expected to grow by 25%. One possible way to accommodate this larger population is to transform smaller cities in Switzerland through the direct intervention of urban planners. In this work, we integrate agent-based simulation models of people flow, mobility and urban infrastructure with models of the electricity and gas systems to examine the increase of the density of existing residential zones and the creation of new workplaces and commercial activities in these urban areas. This novel simulation framework is used to assess, for the year 2050, two different scenarios of urbanization in a region with small urban areas. It is shown that a densification scenario, with a preference for multi-dwelling buildings, consumes 93% less land than a sprawl scenario, with a preference for single-family houses. The former scenario also accommodates 27% more people than the latter scenario, as there is a higher penetration of battery electric vehicles – and therefore reduced air pollution from the transportation sector – and also a larger shift of commuters to the use of public transport. However, in the former scenario, the commuting time is 20% longer. The outcome of this work demonstrates how this novel simulation framework can be used to support the formulation of policies that can direct the transformation of urban areas.

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