Dynamic noise, chaos and parameter estimation in population biology
Author(s) -
Nico Stollenwerk,
Maíra Aguiar,
Sébastien Ballesteros,
João Pedro Boto,
Bob W. Kooi,
Luís Mateus
Publication year - 2012
Publication title -
interface focus
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.1
H-Index - 49
eISSN - 2042-8901
pISSN - 2042-8898
DOI - 10.1098/rsfs.2011.0103
Subject(s) - estimation theory , dengue fever , computer science , attractor , population , estimation , noise (video) , statistical physics , iterated function , dynamical systems theory , chaos (operating system) , mathematics , biology , algorithm , artificial intelligence , virology , physics , mathematical analysis , demography , management , computer security , quantum mechanics , sociology , economics , image (mathematics)
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 such as multi-strain dynamics to describe the virus-host interaction in dengue fever, even the most recently developed parameter estimation techniques, such as maximum likelihood iterated filtering, reach their computational limits. However, the first results of parameter estimation with data on dengue fever from Thailand indicate a subtle interplay between stochasticity and the deterministic skeleton. The deterministic system on its own already displays complex dynamics up to deterministic chaos and coexistence of multiple attractors.
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