Abstract
Owing to the ongoing pandemic of COVID-19 an increased interest in epidemiological mathematical modelling arised. Several specific extensions of the classical susceptible-infected-recovered (SIR) modeling approach for the COVID-19 pandemic were developed to make forecasts. However, in all models, parameters have to be fitted on historical data. In this work we restrict ourselves to a simple model assuming however time dependent parameters. This makes sense as the parameters represent contact rate as well as recovery and death rate which are parameters that change with mutation of the virus and change in behaviour of the population. We estimate them using a Markov Chain Monte Carlo method. On the example of gender we split the model in society subgroups and estimate group specific parameters as well.
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Mahmoudi, M.H., Grundel, S. (2022). Estimation of Time-Dependent Parameters in a Simple Compartment Model Using Covid-19 Data. In: Ehrhardt, M., Günther, M. (eds) Progress in Industrial Mathematics at ECMI 2021. ECMI 2021. Mathematics in Industry(), vol 39. Springer, Cham. https://doi.org/10.1007/978-3-031-11818-0_31
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DOI: https://doi.org/10.1007/978-3-031-11818-0_31
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