The real COVID-19 pandemic dynamics in Qatar in 2021: simulations, predictions and verifications of the SIR model

The real COVID-19 pandemic dynamics in Qatar in 2021: simulations, predictions and verifications of the SIR model

Authors

DOI:

https://doi.org/10.5433/1679-0375.2021v42n1Suplp55

Keywords:

COVID-19 pandemic. Vaccination efficiency, Epidemic dynamics in Qatar, SIR model, Parameter identification

Abstract

The third COVID-19 pandemic wave in Qatar was simulated with the use of the generalized SIR-model and the accumulated number of cases reported by Johns Hopkins University for the period: April 25 - May 8, 2021. The results were compared with the SIR simulations performed before for the second wave and the number of laboratory-confirmed cases in the first half of 2021. Despite the mass vaccination that began in December 2020, Qatar experienced a new epidemic wave in March-April 2021. As of the end of June 2021, the positive effects of vaccination were still unclear, although the number of fully vaccinated was already approaching half the population. Additional simulations have demonstrated that many COVID-19 cases are not detected. The real accumulated number of cases in Qatar can exceed the laboratory-confirmed one more than 5 times. This fact drastically increases the probability of meeting an infectious person and the epidemic duration.

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Author Biography

Igor Nesteruk, Institute of Hydromechanics, National Academy of Sciences of Ukraine

PhD., Institute of Hydromechanics, National Academy of Sciences of Ukraine, Kyiv, Ukraine

References

FAHMAYA, A. E.; EL-DESOUKYA, M. M.; MOHAMED, A. S. A. Epidemic analysis of COVID-19 in Egypt, Qatar and Saudi Arabia using the generalized seir model. MedRxiv, New Haven, p. 1-19, 2020. DOI: https://doi.org/10.1101/2020.08.19.20178129.


GHANAM, R.; BOONE, E.; ABDEL-SALAM, A.-S. G. Seird model for Qatar Covid-19 outbreak: a case study. Letters in Biomathematics, Illinois, p. 1-10, 2020. Preprint. Available from: https://arxiv.org/pdf/2005.12777.pdf. Access in: June, 24 2021.

KERMACK, W. O.; MCKENDRICK, A. G. A Contribution to the mathematical theory of epidemics. Proceedings of the royal society of London, series A., London, v. 115, p. 700-721, 1927.

KOTTASOVÁ, I.; ETZLER, T. Slovakia tested most of the country in two days. Here’s how they did it and what they found. CNN, Atlanta, 2020. Available from: https://edition.cnn.com/2020/11/02/europe/slovakia-mass-coronavirus-test-intl/index.html. Access in: 2 nov. 2020.

LANGEMANN, D.; NESTERUK, I.; PRESTIN, J. Comparison of mathematical models for the dynamics of the Chernivtsi children disease. Mathematics in computers and simulation, [London], v. 123, p. 68-79, 2016. DOI: 10.1016/j.matcom.2016.01.003. Access in: June, 24 2021.

MURRAY J. D. Mathematical biology I/II. New York:Springer, 2002.

NESTERUK, I. Visible and real sizes of new COVID-19 pandemic waves in Ukraine. Innov Biosyst Bioeng, Kyiv, v. 5, n. 2, p. 85–96, 2021a. DOI: 10.20535/ibb.2021.5.2.230487.

NESTERUK, I. COVID19 pandemic dynamics. Singapore: Springer Nature, 2021b. DOI 10.1007/978-981-33-6416-5.

NESTERUK, I. Procedures of parameter identification for the waves of epidemics. In: NESTERUK, I. COVID-19 Pandemic Dynamics. Singapore: Springer Nature, 2021c. p. 133-139. DOI 10.1007/978-981-33-6416-5_10.

NESTERUK, I. Classical SIR model and the exact solution of differential equations. In: NESTERUK, I. COVID-19 Pandemic Dynamics. Singapore: Springer Nature, 2021d. p. 23-32. DOI 10.1007/978-981-33-6416-5_4.

NESTERUK, I.; BENLAGHA, N. Predictions of Covid-19 pandemic dynamics in Ukraine and Qatar based on generalized sir model. Innov Biosyst Bioeng, Kyiv, v. 5, n. 1, p. 37–46, 2021. DOI 10.20535/ibb.2021.5.1.228605.

NOVAK, T. An experiment with mass testing for COVID-19 was conducted in Khmelnytsky (in Ukrainian). Podillya NEWS, Kiev, 2021. Available from: https://podillyanews.com/2020/12/17/u-shkolah-hmelnytskogo-provely-eksperyment-z-estuvannyam-na-covid-19/. Access in: June, 24 2021.

OUR WORLD IN DATA. COVID-19 Dataset by Our World in Data, 2021. Available from: https://github.com/owid/covid-19-data/tree/master/public/data. Access in: June, 24 2021.

SLOVAKIA’S second round of coronavirus tests draws large crowds. Voa, Lang, 2020. Available from: https://www.voanews.com/covid-19-pandemic/slovakias-second-round-coronavirus-tests-draws-large-crowds. Access in: 7 nov. 2020.

WEINBERGER, D. M., COHEN, T., CRAWFORD, F. W., MOSTASHARI, F., OLSON, D., PITZER, V. E., REICH, N., G., RUSSI, M., SIMONSEN, L., WATKINS, A., VIBOUD, C. Estimating the early death toll of COVID-19 in the United States. MedRxiv, New Haven, p. 1-28, 2020. Preprint. DOI: https://doi.org/10.1101/2020.04.15.20066431.

WHO - WORLD HEALTH ORGANIZATION. Coronavirus disease (COVID-19) weekly epidemiological update and weekly operational update. Geneva: WHO, 2019. Available from: https://www.who.int/emergencies/diseases/novel-coronavirus-2019/situation-reports/. Access in: June, 24 2021.

ZHEN, L. Coronavirus: ‘strange pneumonia’ seen in Lombardy in November, leading Italian doctor says. South China Morning Post, Hong Kong, 22 mar. 2020. Available from: https://www.scmp.com/news/china/society/article/3076334/coronavirus-strange-pneumonia-seen-lombardy-november-leading. Access in: June, 24 2021.

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Published

2021-09-06

How to Cite

Nesteruk, I. (2021). The real COVID-19 pandemic dynamics in Qatar in 2021: simulations, predictions and verifications of the SIR model. Semina: Ciências Exatas E Tecnológicas, 42(1Supl), 55–62. https://doi.org/10.5433/1679-0375.2021v42n1Suplp55
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