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COVID-19 spreading in Rio de Janeiro, Brazil: Do the policies of social isolation really work?

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  • Crokidakis, Nuno

Abstract

The recent Coronavirus has been spreading through all the world fastly. In this work we focus on the evolution of the COVID-19 in one of the most populous Brazilian states, namely the Rio de Janeiro state. The first case was reported in March 5, 2020, thus we have a considerable amount of available data to make a good analysis. We study the dynamics of COVID-19 through a Susceptible-Infectious-Quarantined-Recovered (SIQR) model with an additional mechanism that represents the implementation of public policies of social isolation. Based on the data collected from the Rio de Janeiro state Department of Health from March 5, 2020 through April 26, 2020, we observed that the implementation of social distancing policies changed the initial exponential growth to a sub-exponential one. The SIQR model with the above-mentioned mechanism is capable of reproducing the data of confirmed cases in Rio de Janeiro, and it explains how that change occurred. The model also predicts an important mitigation effect, namely the flattening effect, i.e., the considerably decrease of the maximum number of confirmed cases. Through the results of the model, this effect can be directly related to the social isolation policies. Finally, we consider the relaxation of such policies, and discuss about the ideal period of time to release people to return to their activities.

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  • Crokidakis, Nuno, 2020. "COVID-19 spreading in Rio de Janeiro, Brazil: Do the policies of social isolation really work?," Chaos, Solitons & Fractals, Elsevier, vol. 136(C).
    • Handle: RePEc:eee:chsofr:v:136:y:2020:i:c:s0960077920303295
    DOI: 10.1016/j.chaos.2020.109930
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    References listed on IDEAS

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    Cited by:

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    2. Okuonghae, D. & Omame, A., 2020. "Analysis of a mathematical model for COVID-19 population dynamics in Lagos, Nigeria," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    3. Moon-Hyun Kim & Jiwon Lee & Hee-Jin Oh & Tsolmon Bayarsaikhan & Tae-Hyoung Tommy Gim, 2023. "A modeling study of the effect of social distancing policies on the early spread of coronavirus disease 2019: a case of South Korea," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 71(1), pages 225-242, August.
    4. de Souza, Silvio L.T. & Batista, Antonio M. & Caldas, Iberê L. & Iarosz, Kelly C. & Szezech Jr, José D., 2021. "Dynamics of epidemics: Impact of easing restrictions and control of infection spread," Chaos, Solitons & Fractals, Elsevier, vol. 142(C).
    5. Crokidakis, Nuno & Sigaud, Lucas, 2021. "Modeling the evolution of drinking behavior: A Statistical Physics perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 570(C).
    6. Castillo, Oscar & Melin, Patricia, 2020. "Forecasting of COVID-19 time series for countries in the world based on a hybrid approach combining the fractal dimension and fuzzy logic," Chaos, Solitons & Fractals, Elsevier, vol. 140(C).
    7. Walter Leal Filho & Amanda Lange Salvia & Arminda Paço & Celia Dias-Ferreira & Samara Neiva & Izabela Simon Rampasso & Rosley Anholon & Claudio Ruy Portela de Vasconcelos & João Henrique Paulino Pires, 2022. "Assessing the Connections between COVID-19 and Waste Management in Brazil," Sustainability, MDPI, vol. 14(13), pages 1-19, July.
    8. Batistela, Cristiane M. & Correa, Diego P.F. & Bueno, Átila M & Piqueira, José Roberto C., 2021. "SIRSi compartmental model for COVID-19 pandemic with immunity loss," Chaos, Solitons & Fractals, Elsevier, vol. 142(C).
    9. Castillo, Oscar & Melin, Patricia, 2021. "A new fuzzy fractal control approach of non-linear dynamic systems: The case of controlling the COVID-19 pandemics," Chaos, Solitons & Fractals, Elsevier, vol. 151(C).

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