State estimators for some epidemiological systems
Author(s) -
Abderrahman Iggidr,
Max O. Souza
Publication year - 2018
Publication title -
journal of mathematical biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.928
H-Index - 97
eISSN - 1432-1416
pISSN - 0303-6812
DOI - 10.1007/s00285-018-1273-3
Subject(s) - observer (physics) , estimator , mathematics , simple (philosophy) , convergence (economics) , class (philosophy) , state vector , epidemic model , exponential function , computer science , statistics , mathematical analysis , artificial intelligence , medicine , population , philosophy , physics , environmental health , epistemology , classical mechanics , quantum mechanics , economics , economic growth
We consider a class of epidemiological models that includes most well-known dynamics for directly transmitted diseases, and some reduced models for indirectly transmitted diseases. We then propose a simple observer that can be applied to models in this class. The error analysis of this observer leads to a non-autonomous error equation, and a new bound for fundamental matrices is also presented. We analyse and implement this observer in two examples: the classical SIR model, and a reduced Bailey-Dietz model for vector-borne diseases. In both cases we obtain arbitrary exponential convergence of the observer. For the latter model, we also applied the observer to recover the number of susceptible using dengue infection data from a district in the city of Rio de Janeiro.
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