title: An evolutionary computing approach for parameter estimation investigation of a model for cholera.
abstract: We consider the problem of using time-series data to inform a corresponding deterministic model and introduce the concept of genetic algorithms (GA) as a tool for parameter estimation, providing instructions for an implementation of the method that does not require access to special toolboxes or software. We give as an example a model for cholera, a disease for which there is much mechanistic uncertainty in the literature. We use GA to find parameter sets using available time-series data from the introduction of cholera in Haiti and we discuss the value of comparing multiple parameter sets with similar performances in describing the data.
authors.affiliation: a Department of Mathematics , Illinois State University , Normal , IL 61790 , USA.
authors.forename: Olcay
authors.initials: O
authors.lastname: Akman
authors.forename: Elsa
authors.initials: E
authors.lastname: Schaefer
mesh_terms: D000465:Algorithms; D005075:Biological Evolution; D002771:Cholera / Q000503:physiopathology / Q000635:transmission*; D003198:Computer Simulation; D006801:Humans; D055552:Infectious Disease Medicine; D008954:Models, Biological; D012984:Software
keywords: 62B10; 92B01; 92B20; cholera; genetic algorithms; parameter estimation; parameter fitting