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Abstracts

XXVI conference

Feasible sets for SEIR-model with control

Kotin V., Chervyakov N.

Bauman Moscow State Technical University, Biomedical technologies faculty, Russia, 105005, Moscow, Vtoraya Baumanskaya ul. b.5, +7 (916) 609-59-06, v.kotin@gmail.com Bauman Moscow State Technical University, Biomedical technologies faculty, Russia, 105005, Moscow, Vtoraya Baumanskaya ul. b.5, +7 (961) 228-02-92, nm.chervyakov@yandex.ru

2 pp. (accepted)

Mathematical models of the morbidity dynamics (often called “epidemiological models”) are traditionally considered extremely important for solving the problems of predicting and controlling human infectious diseases [1]. The current urgency of this range of problems is due to such factors as large-scale migration flows [2], the emergence of resistant strains of pathogens [3], a clearly growing need for economic analysis of anti-epidemic procedures [4,5].

This paper analyzes the SEIR model [1] of morbidity dynamics, taking into account migration and morbidity control (vaccination) [6]. Feasible sets for the SEIR system are found to assess the most accessible control possibilities. The influence of the model input data (initial conditions) uncertainty is considered. The results obtained form the basis for choosing the most effective way to use limited resources during vaccination and other anti-epidemic measures.

References

1. Roy M. Anderson and Robert M. May, Infectious Diseases of Humans: Dynamics and Control, Oxford University Press, New York, 1991, 757 pp.

2. Castelli, F. and Sulis, G. Migration and infectious diseases. Clinical Microbiology and Infection , Volume 23 , Issue 5 , 2017, 283 - 289

3. Temime, L., et al. The rising impact of mathematical modelling in epidemiology: antibiotic resistance research as a case study. Epidemiology and infection, 136(3), 2007, 289-298.

4. Charles Perrings, et al. Merging Economics and Epidemiology to Improve the Prediction and Management of Infectious Disease. EcoHealth 11, 464–475, 2014

5. Moneim I. A. Efficiency of different vaccination strategies for childhood diseases: A simulation study. Advances in Bioscience and Biotechnology, 2013, 4, 193-205.

6. Kotin,V.V., Litun, E.I. and Litun,S.I., The consecutive vaccination mode optimization and feasible sets estimations, Journal Biomedical Radioelectronics №9, 2017, 29-34.



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