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Self-affinity in the dengue fever time series

Author

Listed:
  • S. M. Azevedo

    (Programa de Modelagem Computacional - SENAI - Cimatec, Salvador, Bahia, Brazil2Universidade Estadual de Feira de Santana, Feira de Santana, Bahia, Brazil)

  • H. Saba

    (Universidade do Estado da Bahia, Salvador, Bahia, Brazil)

  • J. G. V. Miranda

    (Universidade Federal da Bahia, Salvador, Bahia, Brazil)

  • A. S. Nascimento Filho

    (Programa de Modelagem Computacional - SENAI - Cimatec, Salvador, Bahia, Brazil)

  • M. A. Moret

    (Programa de Modelagem Computacional - SENAI - Cimatec, Salvador, Bahia, Brazil3Universidade do Estado da Bahia, Salvador, Bahia, Brazil)

Abstract

Dengue is a complex public health problem that is common in tropical and subtropical regions. This disease has risen substantially in the last three decades, and the physical symptoms depict the self-affine behavior of the occurrences of reported dengue cases in Bahia, Brazil. This study uses detrended fluctuation analysis (DFA) to verify the scale behavior in a time series of dengue cases and to evaluate the long-range correlations that are characterized by the power law α exponent for different cities in Bahia, Brazil. The scaling exponent (α) presents different long-range correlations, i.e. uncorrelated, anti-persistent, persistent and diffusive behaviors. The long-range correlations highlight the complex behavior of the time series of this disease. The findings show that there are two distinct types of scale behavior. In the first behavior, the time series presents a persistent α exponent for a one-month period. For large periods, the time series signal approaches subdiffusive behavior. The hypothesis of the long-range correlations in the time series of the occurrences of reported dengue cases was validated. The observed self-affinity is useful as a forecasting tool for future periods through extrapolation of the α exponent behavior. This complex system has a higher predictability in a relatively short time (approximately one month), and it suggests a new tool in epidemiological control strategies. However, predictions for large periods using DFA are hidden by the subdiffusive behavior.

Suggested Citation

  • S. M. Azevedo & H. Saba & J. G. V. Miranda & A. S. Nascimento Filho & M. A. Moret, 2016. "Self-affinity in the dengue fever time series," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 27(12), pages 1-9, December.
  • Handle: RePEc:wsi:ijmpcx:v:27:y:2016:i:12:n:s0129183116501436
    DOI: 10.1142/S0129183116501436
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    Citations

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    Cited by:

    1. Filho, A.S. Nascimento & Araújo, M.L.V. & Miranda, J.G.V. & Murari, T.B. & Saba, H. & Moret, M.A., 2018. "Self-affinity and self-organized criticality applied to the relationship between the economic arrangements and the dengue fever spread in Bahia," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 502(C), pages 619-628.
    2. Santos, J.V.C. & Moreira, D.M. & Moret, M.A. & Nascimento, E.G.S., 2019. "Analysis of long-range correlations of wind speed in different regions of Bahia and the Abrolhos Archipelago, Brazil," Energy, Elsevier, vol. 167(C), pages 680-687.

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