M.Sc. C.S. Thesis Defense: Berwin Jarret T. Yu (Optimal Resource Allocation for a Coronavirus Epidemic via a Discrete Lagrangian SEIR-type Model)

Zoom Link

Meeting ID: 835 0947 5244

Meeting Password: BYuDefense

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Panel Members

Adrian Roy L. Valdez, Ph.D. (Adviser)

Fredegusto Guido P. David, Ph.D. (Reader)

Vena Pearl A. Bongolan, Ph.D. (Chairman)

ABSTRACT

Infectious diseases like the coronavirus have affected a lot of people in the world. Interventions must be made to reduce the severity of these diseases. This research has created a discrete Lagrangian model for a coronavirus epidemic. This model would consider different intervention strategies as well as their costs. A genetic algorithm was created to solve for the minimum budget required to stop a pandemic. Another genetic algorithm was developed to solve for the budget allocation that would minimize the total infection, the total deaths, or the peak of newly infected cases. The results show that the contact tracing control is the most cost-effective control in stopping the pandemic. The results also show that the best way to save money is to try to stop the pandemic as soon as possible.