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Optimal management of vaccination and isolation in an epidemic situation

Authors: Maslakov A.V.
Published in issue: #11(64)/2021
DOI: 10.18698/2541-8009-2021-11-752


Category: Medical sciences | Chapter: Medical equipment and devices

Keywords: mathematical epidemiology, measles, SEIR model, quarantine, isolation, vaccination, optimal management, coronavirus
Published: 10.12.2021

Against the background of the spread of coronavirus infection, various control measures are being introduced to prevent its further spread. It is imperative to assess the impact of such measures on the dynamics of the epidemic. In the above work, the compartment models used in mathematical epidemiology to describe the dynamics of epidemics are considered, extended to describe control measures in the form of vaccination and isolation using the example of measles disease. The task of optimal control of vaccination and isolation regimes is set. A numerical solution to the problem is obtained for various values of the weight coefficient and the threshold of the control action to assess their influence on the effectiveness of control measures. A close to linear dependence of the effectiveness of control measures on the threshold of control action was obtained.


References

[1] Zhou P., Yang X.L., Wang X.G. et al. A pneumonia outbreak associated with a new coronavirus of probable bat origin. Nature, 2020, vol. 579, no. 7798, pp. 270–273. DOI: https://doi.org/10.1038/s41586-020-2012-7

[2] Coronavirus disease 2019 (COVID-19), situation report. apps.who.int: website (in Russ.). URL: https://apps.who.int/iris/handle/10665/331686 (accessed: 20.12.2020)

[3] Yang Z., Zeng Z., Wang K. et al. Modified SEIR and AI prediction of the epidemics trend of COVID-19 in China under public health interventions. J. Thorac. Dis., 2020, vol. 12, no. 3, pp. 165–174. DOI: https://doi.org/10.21037/jtd.2020.02.64

[4] Martcheva M. An introduction to mathematical epidemiology. Springer, 2015.

[5] Hansen E., Day T. Optimal control of epidemics with limited resources. J. Math. Biol., 2011, vol. 62, no. 3, pp. 423–451. DOI: https://doi.org/10.1007/s00285-010-0341-0

[6] Zhou Y., Wu J., Wu M. Optimal isolation strategies of emerging infectious diseases with limited resources. Math. Biosci. Eng., 2013, vol. 10, no. 5-6, pp. 1691–1701. DOI: https://doi.org/10.3934/mbe.2013.10.1691

[7] Yan X., Zou Y. Control of Epidemics by quarantine and isolation strategies in highly mobile populations. Int. J. Inform. Syst. Sci., 2009, vol. 5, no. 3-4, pp. 271–286.

[8] Kotin V.V., Sychugina A.S. Cination procedures program control optimization. Biomeditsinskaya radioelektronika [Biomedical Radioelectronics], 2016, no. 7, pp. 25–30 (in Russ.).

[9] Kotin V.V., Litun E.I., Litun S.I. The consecutive vaccination mode optimization and feasible sets estimations. Biomeditsinskaya radioelektronika [Biomedical Radioelectronics], 2017, no. 9, pp. 29–34 (in Russ.).

[10] Kotin V.V., Chervyakov N.M. Uncertainty of initial conditions in a SEIR-model with vaccination. Biomeditsinskaya radioelektronika [Biomedical Radioelectronics], 2019, no. 6, pp. 40–47 (in Russ.).

[11] ICLOCS2 (Version 2.5). ee.ic.ac.uk: website. URL: http://www.ee.ic.ac.uk/ICLOCS/ (accessed: 27.12.2020).

[12] Zhukov V.V., Kotin V.V. Efficiency, control and optimality of vaccination. Biomeditsinskaya radioelektronika [Biomedical Radioelectronics], 2018, no. 10, pp. 52–56 (in Russ.).

[13] Yan X., Zou Y. Optimal and sub-optimal quarantine and isolation control in SARS epidemics. Math. Comput. Model., 2008, vol. 47, no. 1, pp. 235–245. DOI: https://doi.org/10.1016/j.mcm.2007.04.003