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Assessing Seasonality Variation with Harmonic Regression: Accommodations for Sharp Peaks

Author

Listed:
  • Kavitha Ramanathan

    (Department of Biostatistics, Christian Medical College, Vellore 632002, India)

  • Mani Thenmozhi

    (Department of Biostatistics, Christian Medical College, Vellore 632002, India)

  • Sebastian George

    (Department of Statistics, St. Thomas College, Palai, Kerala 686575, India)

  • Shalini Anandan

    (Department of Clinical Microbiology, Christian Medical College, Vellore 632004, India)

  • Balaji Veeraraghavan

    (Department of Clinical Microbiology, Christian Medical College, Vellore 632004, India)

  • Elena N. Naumova

    (Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA 02111, USA
    Department of Gastrointestinal Sciences, Christian Medical College, Vellore 632004, India)

  • Lakshmanan Jeyaseelan

    (Department of Biostatistics, Christian Medical College, Vellore 632002, India)

Abstract

The use of the harmonic regression model is well accepted in the epidemiological and biostatistical communities as a standard procedure to examine seasonal patterns in disease occurrence. While these models may provide good fit to periodic patterns with relatively symmetric rises and falls, for some diseases the incidence fluctuates in a more complex manner. We propose a two-step harmonic regression approach to improve the model fit for data exhibiting sharp seasonal peaks. To capture such specific behavior, we first build a basic model and estimate the seasonal peak. At the second step, we apply an extended model using sine and cosine transform functions. These newly proposed functions mimic a quadratic term in the harmonic regression models and thus allow us to better fit the seasonal spikes. We illustrate the proposed method using actual and simulated data and recommend the new approach to assess seasonality in a broad spectrum of diseases manifesting sharp seasonal peaks.

Suggested Citation

  • Kavitha Ramanathan & Mani Thenmozhi & Sebastian George & Shalini Anandan & Balaji Veeraraghavan & Elena N. Naumova & Lakshmanan Jeyaseelan, 2020. "Assessing Seasonality Variation with Harmonic Regression: Accommodations for Sharp Peaks," IJERPH, MDPI, vol. 17(4), pages 1-14, February.
  • Handle: RePEc:gam:jijerp:v:17:y:2020:i:4:p:1318-:d:322193
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    References listed on IDEAS

    as
    1. Olga K. Alsova & Valery B. Loktev & Elena N. Naumova, 2019. "Rotavirus Seasonality: An Application of Singular Spectrum Analysis and Polyharmonic Modeling," IJERPH, MDPI, vol. 16(22), pages 1-20, November.
    2. Chui, K.K.H. & Jagai, J.S. & Griffiths, J.K. & Naumova, E.N., 2011. "Hospitalization of the elderly in the United States for nonspecific gastrointestinal diseases: A search for etiological clues," American Journal of Public Health, American Public Health Association, vol. 101(11), pages 2082-2086.
    3. Julia B Wenger & Elena N Naumova, 2010. "Seasonal Synchronization of Influenza in the United States Older Adult Population," PLOS ONE, Public Library of Science, vol. 5(4), pages 1-11, April.
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    Cited by:

    1. Anastasia Marshak & Aishwarya Venkat & Helen Young & Elena N. Naumova, 2021. "How Seasonality of Malnutrition Is Measured and Analyzed," IJERPH, MDPI, vol. 18(4), pages 1-12, February.

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