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Bridging the COVID-19 Data and the Epidemiological Model using Time Varying Parameter SIRD Model

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  • Cem Cakmakli
  • Yasin Simsek

Abstract

This paper extends the canonical model of epidemiology, SIRD model, to allow for time varying parameters for real-time measurement of the stance of the COVID-19 pandemic. Time variation in model parameters is captured using the generalized autoregressive score modelling structure designed for the typically daily count data related to pandemic. The resulting specification permits a flexible yet parsimonious model structure with a very low computational cost. This is especially crucial at the onset of the pandemic when the data is scarce and the uncertainty is abundant. Full sample results show that countries including US, Brazil and Russia are still not able to contain the pandemic with the US having the worst performance. Furthermore, Iran and South Korea are likely to experience the second wave of the pandemic. A real-time exercise show that the proposed structure delivers timely and precise information on the current stance of the pandemic ahead of the competitors that use rolling window. This, in turn, transforms into accurate short-term predictions of the active cases. We further modify the model to allow for unreported cases. Results suggest that the effects of the presence of these cases on the estimation results diminish towards the end of sample with the increasing number of testing.

Suggested Citation

  • Cem Cakmakli & Yasin Simsek, 2020. "Bridging the COVID-19 Data and the Epidemiological Model using Time Varying Parameter SIRD Model," Papers 2007.02726, arXiv.org, revised Feb 2021.
  • Handle: RePEc:arx:papers:2007.02726
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    Cited by:

    1. Muhammed A. Yildirim & Cem Cakmakli & Selva Demiralp & Sebnem Kalemli-Ozcan & Sevcan Yesiltas, 2021. "The Economic Case for Global Vaccinations: An Epidemiological Model with International Production Networks," CID Working Papers 390, Center for International Development at Harvard University.
    2. Alexander Chudik & M. Hashem Pesaran & Alessandro Rebucci, 2021. "COVID-19 Time-Varying Reproduction Numbers Worldwide: An Empirical Analysis of Mandatory and Voluntary Social Distancing," Globalization Institute Working Papers 407, Federal Reserve Bank of Dallas.

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    More about this item

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • I19 - Health, Education, and Welfare - - Health - - - Other

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