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Coronavirus pandemic: A predictive analysis of the peak outbreak epidemic in South Africa, Turkey, and Brazil

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  • Djilali, Salih
  • Ghanbari, Behzad

Abstract

In this research, we are interested in predicting the epidemic peak outbreak of the Coronavirus in South Africa, Turkey, and Brazil. Until now, there is no known safe treatment, hence the immunity system of the individual has a crucial role in recovering from this contagious disease. In general, the aged individuals probably have the highest rate of mortality due to COVID-19. It is well known that this immunity system can be affected by the age of the individual, so it is wise to consider an age-structured SEIR system to model Coronavirus transmission. For the COVID-19 epidemic, the individuals in the incubation stage are capable of infecting the susceptible individuals. All the mentioned points are regarded in building the responsible predictive mathematical model. The investigated model allows us to predict the spread of COID-19 in South Africa, Turkey, and Brazil. The epidemic peak outbreak in these countries is considered, and the estimated time of the end of infection is regarded by the help of some numerical simulations. Further, the influence of the isolation of the infected persons on the spread of COVID-19 disease is investigated.

Suggested Citation

  • Djilali, Salih & Ghanbari, Behzad, 2020. "Coronavirus pandemic: A predictive analysis of the peak outbreak epidemic in South Africa, Turkey, and Brazil," Chaos, Solitons & Fractals, Elsevier, vol. 138(C).
    • Handle: RePEc:eee:chsofr:v:138:y:2020:i:c:s0960077920303702
    DOI: 10.1016/j.chaos.2020.109971
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    References listed on IDEAS

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    1. Djilali, Salih, 2019. "Impact of prey herd shape on the predator-prey interaction," Chaos, Solitons & Fractals, Elsevier, vol. 120(C), pages 139-148.
    2. Riaz, M.B. & Iftikhar, N., 2020. "A comparative study of heat transfer analysis of MHD Maxwell fluid in view of local and nonlocal differential operators," Chaos, Solitons & Fractals, Elsevier, vol. 132(C).
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    Cited by:

    1. Ghanbari, Behzad, 2020. "On forecasting the spread of the COVID-19 in Iran: The second wave," Chaos, Solitons & Fractals, Elsevier, vol. 140(C).
    2. Khan, Hasib & Alam, Khurshaid & Gulzar, Haseena & Etemad, Sina & Rezapour, Shahram, 2022. "A case study of fractal-fractional tuberculosis model in China: Existence and stability theories along with numerical simulations," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 198(C), pages 455-473.
    3. Şuayip Yüzbaşı & Gamze Yıldırım, 2023. "A Pell–Lucas Collocation Approach for an SIR Model on the Spread of the Novel Coronavirus (SARS CoV-2) Pandemic: The Case of Turkey," Mathematics, MDPI, vol. 11(3), pages 1-22, January.
    4. Napasool Wongvanich & I-Ming Tang & Marc-Antoine Dubois & Puntani Pongsumpun, 2021. "Mathematical Modeling and Optimal Control of the Hand Foot Mouth Disease Affected by Regional Residency in Thailand," Mathematics, MDPI, vol. 9(22), pages 1-30, November.
    5. Panwar, Harsh & Gupta, P.K. & Siddiqui, Mohammad Khubeb & Morales-Menendez, Ruben & Bhardwaj, Prakhar & Singh, Vaishnavi, 2020. "A deep learning and grad-CAM based color visualization approach for fast detection of COVID-19 cases using chest X-ray and CT-Scan images," Chaos, Solitons & Fractals, Elsevier, vol. 140(C).

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