<abstract xml:lang="en" xmlns="http://www.w3.org/1999/xhtml"><p>Epidemiological models can be used to study the impact of an infection within a population. These models often involve parameters that are not known with certainty. Using a method for verified solution of nonlinear dynamic models, we can bound the disease trajectories that are possible for given bounds on the uncertain parameters. The method is based on the use of an interval Taylor series to represent dependence on time and the use of Taylor models to represent dependence on uncertain parameters and/or initial conditions. The use of this method in epidemiology is demonstrated using the SIRS model, and other variations of Kermack-McKendrick models, including the case of time-dependent transmission.</p></abstract>

Epidemiological models can be used to study the impact of an infection within a population. These models often involve parameters that are not known with certainty. Using a method for verified solution of nonlinear dynamic models, we can bound the disease trajectories that are possible for given bounds on the uncertain parameters. The method is based on the use of an interval Taylor series to represent dependence on time and the use of Taylor models to represent dependence on uncertain parameters and/or initial conditions. The use of this method in epidemiology is demonstrated using the SIRS model, and other variations of Kermack-McKendrick models, including the case of time-dependent transmission.

Verified Solution Method for Population Epidemiology Models with Uncertainty

Department of Chemical and Biomolecular Engineering, University of Notre Dame, Notre Dame, IN 46556, USA

International Journal of Applied Mathematics and Computer Science

{"article-title":"Verified Solution Method for Population Epidemiology Models with Uncertainty"}

Epidemiological models can be used to study the impact of an infection within a population. These models often involve parameters that are not known with...

Verified Solution Method for Population Epidemiology Models with Uncertainty

Online veröffentlicht: 24. Sept. 2009

Seitenbereich: 501 - 512

DOI: https://doi.org/10.2478/v10006-009-0040-4

Schlüsselwörter
nonlinear dynamics, epidemiology, interval analysis, verified computing, ordinary differential equations

This content is open access.

Verified Solution Method for Population Epidemiology Models with Uncertainty

Online veröffentlicht: 24. Sept. 2009

Seitenbereich: 501 - 512

DOI: https://doi.org/10.2478/v10006-009-0040-4

Schlüsselwörternonlinear dynamics, epidemiology, interval analysis, verified computing, ordinary differential equations

This content is open access.

Schlüsselwörter
nonlinear dynamics, epidemiology, interval analysis, verified computing, ordinary differential equations