Skip to main content
AIP Publishing Selective Deposit logoLink to AIP Publishing Selective Deposit
. 2011 Sep 14;1389(1):1248–1251. doi: 10.1063/1.3637843

Parameter Estimation in Epidemiology: from Simple to Complex Dynamics

Maíra Aguiar a, Sebastién Ballesteros b, João Pedro Boto a, Bob W Kooi b, Luís Mateus a, Nico Stollenwerk a
Editors: Theodore E Simosc,d,e,f, George Psihoyiosc,d,e,f, Ch Tsitourasc,d,e,f, Zacharias Anastassic,d,e,f
PMCID: PMC7108775  PMID: 32255869

Abstract

We revisit the parameter estimation framework for population biological dynamical systems, and apply it to calibrate various models in epidemiology with empirical time series, namely influenza and dengue fever. When it comes to more complex models like multi‐strain dynamics to describe the virus‐host interaction in dengue fever, even most recently developed parameter estimation techniques, like maximum likelihood iterated filtering, come to their computational limits. However, the first results of parameter estimation with data on dengue fever from Thailand indicate a subtle interplay between stochasticity and deterministic skeleton. The deterministic system on its own already displays complex dynamics up to deterministic chaos and coexistence of multiple attractors.


Articles from Aip Conference Proceedings are provided here courtesy of American Institute of Physics

RESOURCES