Modeling COVID-19 in Italy




Sullivan, Kevin

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Six SEIR models are considered in attempting to replicate the COVID-19 outbreak in Italy in the first quarter of 2020. The Excel models make a variety of assumptions, and modifications are assessed to determine which factors created the rise in cases. In each model, the discrete equation I(t) = I(t-1) +1/ξ ∙ E(t-1) – 1/δ ∙ I(t-1) is used to compare how close the simulation got to the actual number of infected individuals at day 50, the peak of the initial outbreak. Modifications to the models and adjustments in parametric values enabled the simulations to closely replicate the actual number of cases. The models indicate that higher values of R0 than those documented in Wuhan, China may have driven case growth. The potential for asymptomatic spread, may have also contributed to the rapid rise of the number of infected in Italy. Future modeling considerations and limitations are also discussed.


Creative Arts and Research Symposium
Creative Arts and Research Symposium