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Mathematical model of COVID-19 intervention scenarios for São Paulo—Brazil

Author

Listed:
  • Osmar Pinto Neto

    (Anhembi Morumbi University
    Arena235 Research Lab
    Parque Tecnológico)

  • Deanna M. Kennedy

    (Texas A&M University)

  • José Clark Reis

    (Arena235 Research Lab)

  • Yiyu Wang

    (Texas A&M University)

  • Ana Carolina Brisola Brizzi

    (Anhembi Morumbi University
    Arena235 Research Lab)

  • Gustavo José Zambrano

    (Arena235 Research Lab)

  • Joabe Marcos Souza

    (Arena235 Research Lab
    Universidade de São Paulo, Departamento de Engenharia Aeronáutica)

  • Wellington Pedroso

    (Anhembi Morumbi University
    Arena235 Research Lab)

  • Rodrigo Cunha Mello Pedreiro

    (Anhembi Morumbi University
    Estácio de Sá University
    Santo Antônio de Pádua College)

  • Bruno Matos Brizzi

    (Arena235 Research Lab)

  • Ellysson Oliveira Abinader

    (Instituto Abinader)

  • Renato Amaro Zângaro

    (Anhembi Morumbi University
    Parque Tecnológico)

Abstract

With COVID-19 surging across the world, understanding the effectiveness of intervention strategies on transmission dynamics is of primary global health importance. Here, we develop and analyze an epidemiological compartmental model using multi-objective genetic algorithm design optimization to compare scenarios related to strategy type, the extent of social distancing, time window, and personal protection levels on the transmission dynamics of COVID-19 in São Paulo, Brazil. The results indicate that the optimal strategy for São Paulo is to reduce social distancing over time with a stepping-down reduction in the magnitude of social distancing every 80-days. Our results also indicate that the ability to reduce social distancing depends on a 5–10% increase in the current percentage of people strictly following protective guidelines, highlighting the importance of protective behavior in controlling the pandemic. Our framework can be extended to model transmission dynamics for other countries, regions, states, cities, and organizations.

Suggested Citation

  • Osmar Pinto Neto & Deanna M. Kennedy & José Clark Reis & Yiyu Wang & Ana Carolina Brisola Brizzi & Gustavo José Zambrano & Joabe Marcos Souza & Wellington Pedroso & Rodrigo Cunha Mello Pedreiro & Brun, 2021. "Mathematical model of COVID-19 intervention scenarios for São Paulo—Brazil," Nature Communications, Nature, vol. 12(1), pages 1-13, December.
    • Handle: RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-020-20687-y
    DOI: 10.1038/s41467-020-20687-y
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    Cited by:

    1. Li, Tingting & Guo, Youming, 2022. "Optimal control and cost-effectiveness analysis of a new COVID-19 model for Omicron strain," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 606(C).
    2. Li, Tingting & Guo, Youming, 2022. "Modeling and optimal control of mutated COVID-19 (Delta strain) with imperfect vaccination," Chaos, Solitons & Fractals, Elsevier, vol. 156(C).

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