title: Analysis of Practical Identifiability of a Viral Infection Model.
abstract: Mathematical modelling approaches have granted a significant contribution to life sciences and beyond to understand experimental results. However, incomplete and inadequate assessments in parameter estimation practices hamper the parameter reliability, and consequently the insights that ultimately could arise from a mathematical model. To keep the diligent works in modelling biological systems from being mistrusted, potential sources of error must be acknowledged. Employing a popular mathematical model in viral infection research, existing means and practices in parameter estimation are exemplified. Numerical results show that poor experimental data is a main source that can lead to erroneous parameter estimates despite the use of innovative parameter estimation algorithms. Arbitrary choices of initial conditions as well as data asynchrony distort the parameter estimates but are often overlooked in modelling studies. This work stresses the existence of several sources of error buried in reports of modelling biological systems, voicing the need for assessing the sources of error, consolidating efforts in solving the immediate difficulties, and possibly reconsidering the use of mathematical modelling to quantify experimental data.
authors.affiliation: Systems Medicine of Infectious Diseases, Department of Systems Immunology and Braunschweig Integrated Centre of Systems Biology, Helmholtz Centre for Infection Research, Braunschweig, Germany.|Epidemiology Department, Ho Chi Minh University of Medicine and Pharmacy, Ho Chi Minh, Vietnam.|PhD Programme "Epidemiology", Braunschweig-Hannover, Germany.
authors.forename: Van Kinh
authors.initials: VK
authors.lastname: Nguyen
authors.affiliation: Biostatistics, Helmholtz Centre for Infection Research, Braunschweig, Germany.|Department of Computer Science, Ostfalia University, Wolfenbüttel, Germany.
authors.forename: Frank
authors.initials: F
authors.lastname: Klawonn
authors.affiliation: Epidemiological and Statistical Methods, Helmholtz Centre for Infection Research, Braunschweig, Germany.|German Centre for Infection Research, site Hannover-Braunschweig, Germany.|Hannover Medical School, Hannover, Germany.|[Institute of] Medical Epidemiology, Biometry and Informatics, Martin-Luther University Halle-Wittenberg, Germany.
authors.forename: Rafael
authors.initials: R
authors.lastname: Mikolajczyk
authors.affiliation: Systems Medicine of Infectious Diseases, Department of Systems Immunology and Braunschweig Integrated Centre of Systems Biology, Helmholtz Centre for Infection Research, Braunschweig, Germany.
authors.forename: Esteban A
authors.initials: EA
authors.lastname: Hernandez-Vargas
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D008954:Models, Biological; D008962:Models, Theoretical; D015203:Reproducibility of Results; D014777:Virus Diseases / Q000821:virology*