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Branching Process Modelling of COVID-19 Pandemic Including Immunity and Vaccination

Author

Listed:
  • Atanasov Dimitar

    (Department of Informatics, New Bulgarian University, 21, Montevideo Blv., 1618Sofia, Bulgaria)

  • Stoimenova Vessela

    (Faculty of Mathematics and Informatics, Sofia University “St. Kliment Ohridski”, 5, James Bourchier Blvd, 1164Sofia, Bulgaria)

  • Yanev Nikolay M.

    (Institute of Mathematics and Informatics, Bulgarian Academy of Sciences, Acad G. Bonchev St, Bl. 8, 1113Sofia, Bulgaria)

Abstract

We propose modeling COVID-19 infection dynamics using a class of two-type branching processes. These models require only observations on daily statistics to estimate the average number of secondary infections caused by a host and to predict the mean number of the non-observed infected individuals. The development of the epidemic process depends on the reproduction rate as well as on additional facets as immigration, adaptive immunity, and vaccination. Usually, in the existing deterministic and stochastic models, the officially reported and publicly available data are not sufficient for estimating model parameters. An important advantage of the proposed model, in addition to its simplicity, is the possibility of direct computation of its parameters estimates from the daily available data. We illustrate the proposed model and the corresponding data analysis with data from Bulgaria, however they are not limited to Bulgaria and can be applied to other countries subject to data availability.

Suggested Citation

  • Atanasov Dimitar & Stoimenova Vessela & Yanev Nikolay M., 2021. "Branching Process Modelling of COVID-19 Pandemic Including Immunity and Vaccination," Stochastics and Quality Control, De Gruyter, vol. 36(2), pages 157-164, December.
    • Handle: RePEc:bpj:ecqcon:v:36:y:2021:i:2:p:157-164:n:1
    DOI: 10.1515/eqc-2021-0040
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