Abstract
The first case of Corona Virus Disease (COVID-19) was registered in Wuhan, China, in November 2019. In March, the World Health Organization (WHO) declared COVID-19 as a global pandemic. The effects of this pandemic have been devastating worldwide, especially in Brazil, which occupies the third position in the absolute number of cases of COVID-19 and the second position in the absolute number of deaths by the virus. A big question that the population yearns to be answered is: When can life return to normal? To address this question, this work proposes an extension of a SIRD-based mathematical model that includes vaccination effects. The model takes into account different rates of daily vaccination and different values of vaccine effectiveness. The results show that although the discussion is very much around the effectiveness of the vaccine, the daily vaccination rate is the most important variable for mitigating the pandemic. Vaccination rates of 1M per day can potentially stop the progression of COVID-19 epidemics in Brazil in less than one year.
Supported by UFSJ, UFJF, Capes, CNPq and Fapemig.
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Available at https://ourworldindata.org/covid-vaccinations.
References
Borse, R.H., et al.: Effects of vaccine program against pandemic influenza A (H1N1) virus, United States, 2009–2010. Emerg. Infect. Diseas. 19(3), 439 (2013)
Diekmann, O., Heesterbeek, J.: Mathematical Epidemiology of Infectious Diseases: Model Building, Analysis and Interpretation. Wiley Series in Mathematical & Computational Biology, Wiley, Hoboken (2000). https://books.google.com.br/books?id=5VjSaAf35pMC
Dong, E., Du, H., Gardner, L.: An interactive web-based dashboard to track COVID-19 in real time. Lancet Infect. Diseas. (2020). https://doi.org/10.1016/S1473-3099(20)30120-1
Espinosa, M.M., de Oliveira, E.C., Melo, J.S., Damaceno, R.D., Terças-Trettel, A.C.P.: Prediction of COVID -19 cases and deaths in Mato Grosso state and Brazil. J. Health Biol. Sci. 1–7 (2020). https://doi.org/10.12662/2317-3076jhbs.v8i1.3224.p1-7.2020
Hethcote, H.W.: The mathematics of infectious diseases. SIAM Rev. 42(4), 599–653 (2000). https://doi.org/10.1137/S0036144500371907
Keeling, M.J., Rohani, P.: Modeling Infectious Diseases in Humans and Animals. Princeton University Press, Princeton (2011). https://doi.org/10.1111/j.1541-0420.2008.01082_7.x
Kermack, W.O., McKendrick, A.G.: Contributions to the mathematical theory of epidemics–I. Bull. Math. Biol. 53(1), 33–55 (1991). https://doi.org/10.1007/BF02464423
Kermack, W.O., McKendrick, A.G., Walker, G.T.: A contribution to the mathematical theory of epidemics. Proc. R. Soc. Lond. Ser. A, Containing Papers of a Mathematical and Physical Character 115(772), 700–721 (1927). https://doi.org/10.1098/rspa.1927.0118. Publisher: Royal Society
Levine-Tiefenbrun, M., et al.: Decreased SARS-CoV-2 viral load following vaccination. medRxiv (2021)
Li, X., et al.: Estimating the health impact of vaccination against ten pathogens in 98 low-income and middle-income countries from 2000 to 2030: a modelling study. Lancet 397(10272), 398–408 (2021)
Libotte, G.B., Lobato, F.S., Platt, G.M., Silva Neto, A.J.: Determination of an optimal control strategy for vaccine administration in Covid-19 pandemic treatment. Comput. Methods Programs Biomed. 196 (2020). https://doi.org/10.1016/j.cmpb.2020.105664
Nguyen, C., Carlson, J.M.: Optimizing real-time vaccine allocation in a stochastic sir model. PloS one 11(4) (2016)
Reis, R.F., et al.: The quixotic task of forecasting peaks of Covid-19: rather focus on forward and backward projections. Front. Public Health (2021). https://doi.org/10.3389/fpubh.2021.623521
Reis, R.F., et al.: Characterization of the COVID-19 pandemic and the impact of uncertainties, mitigation strategies, and underreporting of cases in South Korea, Italy, and Brazil. Chaos, Solitons Fractals 136 (2020). https://doi.org/10.1016/j.chaos.2020.109888
da Saúde, M.: Preliminary vaccination plan against Covid-19 foresees four phases (2021). https://www.gov.br/saude/pt-br/assuntos/noticias/vacinacao-contra-a-covid-19-sera-feita-em-quatro-fases. Accessed 3 Feb 2021. (in portuguese)
Sobol, I.M.: Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates. Math. Comput. Simul. 55(1–3), 271–280 (2001). https://doi.org/10.1016/S0378-4754(00)00270-6
Voysey, M., et al.: Single dose administration, and the influence of the timing of the booster dose on immunogenicity and efficacy of ChAdOx1 nCoV-19 (AZD1222) vaccine. Preprints with The Lancet (2021)
World Health Organization: WHO timeline - Covid-19 - 27 April 2020 (2020). https://www.who.int/news/item/27-04-2020-who-timeline--covid-19. Accessed 03 Feb 2021
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Oliveira, R.S. et al. (2021). How Fast Vaccination Can Control the COVID-19 Pandemic in Brazil?. In: Paszynski, M., Kranzlmüller, D., Krzhizhanovskaya, V.V., Dongarra, J.J., Sloot, P.M.A. (eds) Computational Science – ICCS 2021. ICCS 2021. Lecture Notes in Computer Science(), vol 12743. Springer, Cham. https://doi.org/10.1007/978-3-030-77964-1_38
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