%0 Journal Article %1 Parra2014231 %A Parra, P.A.G. %A Ceberio, M. %A Lee, S. %A Castillo-Chavez, C. %D 2014 %I Springer Verlag %J Advances in Intelligent Systems and Computing %K Antiviral Bioinformatics Control; Cumulative Discrete-time Epidemiology, Influenza; Interior-point Optimal Primal-dual control controls; interior method; methods, model; number; point strategy; treatments; %P 231-237 %R http://dx.doi.org/10.1007/978-3-319-01568-2_33 %T Optimal control for a discrete time influenza model %U http://dx.doi.org/10.1007/978-3-319-01568-2_33 %V 232 %X 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. Â\copyright Springer International Publishing Switzerland 2014. %@ 9783319015675

@article{Parra2014231, 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. {\^A}{\copyright} Springer International Publishing Switzerland 2014.}, added-at = {2017-11-10T22:48:29.000+0100}, affiliation = {Universidad Aut{\~A}³noma de Occidente, Departamento de Matematicas, Cali, Colombia; The University of Texas at El Paso, Computer Science Department, El Paso, TX 79968-0514, United States; Kyung Hee University, Department of Applied Mathematics, Yongin, 446-701, South Korea; Arizona State University, Mathematical, Computational and Modeling Sciences Center, Tempe, AZ 85287, United States}, author = {Parra, P.A.G. and Ceberio, M. and Lee, S. and Castillo-Chavez, C.}, author_keywords = {Epidemiology; Influenza; Interior-Point methods; Optimal Control}, biburl = {https://www.bibsonomy.org/bibtex/2406076bc77fc424378cecf654b1dc139/ccchavez}, date-added = {2017-11-10 21:45:26 +0000}, date-modified = {2017-11-10 21:45:26 +0000}, document_type = {Conference Paper}, doi = {http://dx.doi.org/10.1007/978-3-319-01568-2_33}, interhash = {ab53fa719d8e4488f8f06c633f70f0b1}, intrahash = {406076bc77fc424378cecf654b1dc139}, isbn = {9783319015675}, issn = {21945357}, journal = {Advances in Intelligent Systems and Computing}, keywords = {Antiviral Bioinformatics Control; Cumulative Discrete-time Epidemiology, Influenza; Interior-point Optimal Primal-dual control controls; interior method; methods, model; number; point strategy; treatments;}, language = {English}, pages = {231-237}, publisher = {Springer Verlag}, timestamp = {2017-11-10T22:48:29.000+0100}, title = {Optimal control for a discrete time influenza model}, url = {http://dx.doi.org/10.1007/978-3-319-01568-2_33}, volume = 232, year = 2014 }