Pietro Terna (University of Torino) (webinar)

“An Agent-Based Model to simulate the Covid-19 epidemic diffusion with the use of Genetic Algorithms to optimize vaccinations”

Abstract: An Agent-Based Model to simulate the Covid-19 epidemic diffusion will be introduced, with Susceptible, Infected, symptomatic, asymptomatic, and Recovered people: hence the name S.I.s.a.R. The scheme comes from S.I.R. models, with (i) infected agents categorized as symptomatic and asymptomatic and (ii) the contagion places specified in a detailed way, thanks to agent-based modeling capabilities. The infection transmission is related to three factors: the infected person’s characteristics and the susceptible one, plus those of the space in which contact occurs. The model allows both to analyze the contagions’ sequences in simulated epidemics and identify the places where they occur.

A new layer of analysis has the goal of optimizing vaccination. We apply Genetic Algorithms to decide the quotas of vaccinations for different groups of persons to reduce symptomatic infections.

Link to a very preliminary paper: https://rofasss.org/2020/10/20/sisar/.

Link to a draft report on GA for vaccinations: https://terna.to.it/simul/GAresultPresentation.pdf (frequently updated).

Affiliations: University of Torino, retired; Fondazione Collegio Carlo Alberto, Honorary Fellow