Second Wave Analysis and Confirmed Forecasts of the SARS-Cov-2 Epidemic Outbreak in São Paulo, Brazil

Sergio Celaschi

Abstract


Objective: A SEIR compartmental model was previously selected to estimate future outcomes to the dynamics of the Covid-19 epidemic breakout in Brazil. Method: Compartments for individuals vaccinated and prevalent SARS-Cov-2 variants were not included. A time-dependent incidence weight on the reproductive basic number accounted for Non Pharmaceutical Interventions (NPI). A first series of published data from March 1st to May 8, 2020 was used to adjust all model parameters aiming to forecast one year of evolutionary outbreak. The cohort study was set as a city population-based analysis. Analysis: A population-based sample of 25,366 confirmed cases on exposed individuals was used during the first study period. The analysis was applied to predict the consequences of NPI enforcements followed by progressive releases, and indicates the appearance of a second wave starting last quarter of 2020. Findings: By March 1st 2021, the number of confirmed cases was predicted to reach 0.47Million (0.24-0.78), and fatalities would account for 21 thousand (12-33), 5 to 95% CRI. A second series of data published from May 9, 2020 to March 1st, 2021 confirms the forecasts previously reported for the evolution of infected people and fatalities. Novelty: By March 1st 2021, the number of confirmed cases reached 527,710 (12% above the predicted average of accumulated cases) and fatalities accounted for 18,769 (10% below the accumulated average of estimated fatalities). After March 1st, new peaks on reported numbers of daily new infected and new fatalities appeared as a combined result to the appearance of the prevalent SARS-CoV-2 P1 variant, and the increased number of vaccinated individuals.

 

Doi: 10.28991/SciMedJ-2021-03-SI-10

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Keywords


COVID-19; Brazil; Confirmed Forecast; NPI and Mitigation Policy; Second Wave; Prevalent Variants; Vaccination.

References


De Macedo, A. V. (2020). Brazil and COVID-19-A Fleeting Glimpse of What Is to Come. JAMA Health Forum, 1(9), e201061. doi:10.1001/jamahealthforum.2020.1061.

De Souza, W. M., Buss, L. F., Candido, D. da S., Carrera, J.-P., Li, S., Zarebski, A. E., … Faria, N. R. (2020). Epidemiological and clinical characteristics of the COVID-19 epidemic in Brazil. Nature Human Behaviour, 4(8), 856–865. doi:10.1038/s41562-020-0928-4.

Dong, E., Du, H., & Gardner, L. (2020). An interactive web-based dashboard to track COVID-19 in real time. The Lancet Infectious Diseases, 20(5), 533–534. doi:10.1016/s1473-3099(20)30120-1.

Celaschi, S. (2020). Quantifying Effects, Forecasting Releases, and Herd Immunity of the Covid-19 Epidemic in S. Paulo – Brazilâ€, The International Journal of Engineering and Science (IJES), 9(07), Series II, 33-42.

Zlojutro, A., Rey, D., & Gardner, L. (2019). A decision-support framework to optimize border control for global outbreak mitigation. Scientific Reports, 9(1). doi:10.1038/s41598-019-38665-w.

Wang, L., & Wu, J. T. (2018). Characterizing the dynamics underlying global spread of epidemics. Nature Communications, 9(1). doi:10.1038/s41467-017-02344-z.

Li, R., Pei, S., Chen, B., Song, Y., Zhang, T., Yang, W., & Shaman, J. (2020). Substantial undocumented infection facilitates the rapid dissemination of novel coronavirus (SARS-CoV-2). Science, 368(6490), 489–493. doi:10.1126/science.abb3221.

Parino, F., Zino, L., Porfiri, M., & Rizzo, A. (2021). Modelling and predicting the effect of social distancing and travel restrictions on COVID-19 spreading. Journal of the Royal Society Interface, 18(175). doi:10.1098/rsif.2020.0875.

Eggo, R. M., Dawa, J., Kucharski, A. J., & Cucunuba, Z. M. (2021). The importance of local context in COVID-19 models. Nature Computational Science, 1(1), 6–8. doi:10.1038/s43588-020-00014-7.

Kissler, S. M., Tedijanto, C., Goldstein, E., Grad, Y. H., & Lipsitch, M. (2020). Projecting the transmission dynamics of SARS-CoV-2 through the postpandemic period. Science, 368(6493), 860–868. doi:10.1126/science.abb5793.

Godio, A., Pace, F., & Vergnano, A. (2020). SEIR Modeling of the Italian Epidemic of SARS-CoV-2 Using Computational Swarm Intelligence. International Journal of Environmental Research and Public Health, 17(10), 3535. doi:10.3390/ijerph17103535.

Bastos, S. B., & Cajueiro, D. O. (2020). Modeling and forecasting the early evolution of the Covid-19 pandemic in Brazil. Scientific Reports, 10(1). doi:10.1038/s41598-020-76257-1.

Korber, B., Fischer, W. M., Gnanakaran, S., Yoon, H., Theiler, J., Abfalterer, W., … Wyles, M. D. (2020). Tracking Changes in SARS-CoV-2 Spike: Evidence that D614G Increases Infectivity of the COVID-19 Virus. Cell, 182(4), 812–827.e19. doi:10.1016/j.cell.2020.06.043.

Celaschi, S., “The Impact of SARS-CoV-2 Variant to COVID-19 Epidemic in Brazilâ€, medRxiv. doi:10.1101/2020.09.25.20201558.

Oliveira, J. F., Jorge, D. C. P., Veiga, R. V., Rodrigues, M. S., Torquato, M. F., da Silva, N. B., … Andrade, R. F. S. (2021). Mathematical modeling of COVID-19 in 14.8 million individuals in Bahia, Brazil. Nature Communications, 12(1). doi:10.1038/s41467-020-19798-3.

Coronavirus casos em SP. Available online: https://www.seade.gov.br/coronavirus/ (accessed on April 25, 2020).

Lamarca, A. P., de Almeida, L. G. P., Francisco, R. da S., Lima, L. F. A., Scortecci, K. C., Perez, V. P., … Vasconcelos, A. T. R. (2021). Genomic surveillance of SARS-CoV-2 tracks early interstate transmission of P.1 lineage and diversification within P.2 clade in Brazil. medRxiv. doi:10.1101/2021.03.21.21253418.

Faria, N. R., Mellan, T. A., Whittaker, C., Claro, I. M., Candido, D. da S., Mishra, S., … McCrone, J. T. (2021). Genomics and epidemiology of a novel SARS-CoV-2 lineage in Manaus, Brazil. medRxiv. doi:10.1101/2021.02.26.21252554

Palacios, R., Batista, A. P., Albuquerque, C. S. N., Patiño, E. G., Santos, J. D. P., Tilli Reis Pessoa Conde, M., ... & Kallas, E. G. (2021). Efficacy and safety of a COVID-19 inactivated vaccine in healthcare professionals in Brazil: the PROFISCOV study. SSRN Preprint. doi:10.2139/ssrn.3822780.

Study suggests the Brazilian variant emerged in November, is more transmissible and can cause reinfection. Available online: https://agencia.fapesp.br/study-suggests-the-brazilian-variant-emerged-in-november-is-more-transmissible-and-can-cause-reinfection/35414/ (accessed on April 25, 2020).


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DOI: 10.28991/SciMedJ-2021-03-SI-10

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