Optimal control for a discrete time influenza model

Paula Andrea Gonzalez Parra, Martine Ceberio, Sunmi Lee, Carlos Castillo-Chavez

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We formulated a discrete time model in order to study optimal control strategies for a single influenza outbreak. In our model, we divided the population into four classes: susceptible, infectious, treated, and recovered individuals. The total population was divided into subgroups according to activity or susceptibility levels. The goal was to determine how treatment doses should be distributed in each group in order to reduce the final epidemic size. The case of limited resources is considered by including an isoperimetric constraint. We found that the use of antiviral treatment resulted in reductions in the cumulative number of infected individuals. We proposed to solve the problem by using the primal-dual interior-point method that enforces epidemiological constraints explicitly.

Original languageEnglish (US)
Title of host publicationAdvances in Computational Biology - Proceedings of the 2nd Colombian Congress on Computational Biology and Bioinformatics CCBCOL 2013
PublisherSpringer Verlag
Pages231-237
Number of pages7
ISBN (Print)9783319015675
DOIs
StatePublished - Jan 1 2014
Event2nd Colombian Congress on Computational Biology and Bioinformatics, CCBCOL 2013 - Manizales, Colombia
Duration: Sep 25 2013Sep 27 2013

Publication series

NameAdvances in Intelligent Systems and Computing
Volume232
ISSN (Print)2194-5357

Other

Other2nd Colombian Congress on Computational Biology and Bioinformatics, CCBCOL 2013
CountryColombia
CityManizales
Period9/25/139/27/13

Keywords

  • Epidemiology
  • Influenza
  • Interior-Point methods
  • Optimal Control

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science(all)

Cite this

Parra, P. A. G., Ceberio, M., Lee, S., & Castillo-Chavez, C. (2014). Optimal control for a discrete time influenza model. In Advances in Computational Biology - Proceedings of the 2nd Colombian Congress on Computational Biology and Bioinformatics CCBCOL 2013 (pp. 231-237). (Advances in Intelligent Systems and Computing; Vol. 232). Springer Verlag. https://doi.org/10.1007/978-3-319-01568-2_33