Abstract
In this work we propose a method for numerical finding of a function representing the time-dependent virus transmission intensity coefficient in the exemplary SEIR model of infectious disease. Our method is based on gradient minimization of a predefined functional and uses a gradient obtained from adjoint sensitivity analysis. To apply this method to the exemplary SEIR model we used publicly available infection data concerning the COVID-19 cumulative cases in Poland.
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Acknowledgement
This work was supported by the Polish National Science Centre under grant number UMO-2020/37/B/ST6/01959 and by the Silesian University of Technology under statutory research funds. Calculations were performed on the Ziemowit computer cluster in the Laboratory of Bioinformatics and Computational Biology, created in the EU Innovative Economy Programme POIG.02.01.00-00-166/08 and expanded in the POIG.02.03.01-00-040/13 project. Data analysis was partially carried out using the Biotest Platform developed within Project n. PBS3/B3/32/2015 financed by the Polish National Centre of Research and Development (NCBiR). This work was carried out in part by the Silesian University of Technology internal research funding.
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Łakomiec, K., Wilk, A., Psiuk-Maksymowicz, K., Fujarewicz, K. (2022). Finding the Time-Dependent Virus Transmission Intensity via Gradient Method and Adjoint Sensitivity Analysis. In: Pietka, E., Badura, P., Kawa, J., Wieclawek, W. (eds) Information Technology in Biomedicine. ITIB 2022. Advances in Intelligent Systems and Computing, vol 1429. Springer, Cham. https://doi.org/10.1007/978-3-031-09135-3_41
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