A regime switching on Covid19 analysis and prediction in Romania
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In this paper we propose a regime separation for the analysis of Covid19 on Romania combined with mathematical models of SIR and SIRD. The main regimes we study are, the free spread of the virus, the quarantine and partial relaxation and the last one is the relaxation regime. The main model we use is SIR which is a classical model, but because we can not fully trust the numbers of infected or recovered we base our analysis on the number of deceased people which is more reliable. To actually deal with this we introduce a simple modification of the SIR model to account for the deceased separately. This in turn will be our base for fitting the parameters. The estimation of the parameters is done in two steps. The first one consists in training a neural network based on SIR models to detect the regime changes. Once this is done we fit the main parameters of the SIRD model using a grid search. At the end, we make some predictions on what the evolution will be in a timeframe of a month with the fitted parameters.
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