Abstract
We explore the Covid-19 diffusion with an agent-based model of an Italian region with a population on a scale of 1:1000. We also simulate different vaccination strategies. From a decision support system perspective, we investigate the adoption of artificial intelligence techniques to provide suggestions about more effective policies. We adopt the widely used multi-agent programmable modeling environment NetLogo, adding genetic algorithms to evolve the best vaccination criteria. The results suggest a promising methodology for defining vaccine rates by population types over time. The results are encouraging towards a more extensive application of agent-oriented methods in public healthcare policies.
Highlights
Modelling diffusion phenomena is a subject of increasing interest in many different research areas, e.g. the spread of information in a social context, the supply chain in business process management, as well as the virus diffusion in an environment
This paper proposes to apply an Artificial Intelligence (AI) technique on the top of an AgentBased Modeling (ABM) concerning the virus spreading by consider- ing where contagions may occur, i.e. the interactions among people and the environment
The simulation in the baseline scenario obtains about 325,000 infected cases, while the ImmuneInfecting scenario obtains an improvement with a decrease of about 215,000 infected at the end of the simulation
Summary
Modelling diffusion phenomena is a subject of increasing interest in many different research areas, e.g. the spread of information in a social context, the supply chain in business process management, as well as the virus diffusion in an environment. ABM typically deals with complex systems, where the interaction between multiple actors are neither predictable with systems of equations, as in SD approaches, nor with sequences of events, as in DES [5, 6]. This paper proposes to apply an AI technique on the top of an ABM concerning the virus spreading by consider- ing where contagions may occur, i.e. the interactions among people and the environment. In the recent Covid-19 pandemic, the introduction of vaccines cope with the fight against the virus diffusion. In this context, the vaccine distribution policies play a relevant role. Our results suggest how Genetic Algorithms (GA) can be applied to an ABM in order to provide parameter estimates for administering the vaccine to groups of people. We conclude the paper in "Conclusions and future work" with some remarks and future work
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