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Rotavirus Seasonality: An Application of Singular Spectrum Analysis and Polyharmonic Modeling

Author

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  • Olga K. Alsova

    (Novosibirsk State Technical University, Novosibirsk 630073, Russia)

  • Valery B. Loktev

    (Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences, Novosibirsk 630090, Russia
    State Research Center for Virology and Biotechnology “Vector”, Koltsovo, Novosibirsk Region 630559, Russia)

  • Elena N. Naumova

    (Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA 02111, USA)

Abstract

The dynamics of many viral infections, including rotaviral infections (RIs), are known to have a complex non-linear, non-stationary structure with strong seasonality indicative of virus and host sensitivity to environmental conditions. However, analytical tools suitable for the identification of seasonal peaks are limited. We introduced a two-step procedure to determine seasonal patterns in RI and examined the relationship between daily rates of rotaviral infection and ambient temperature in cold climates in three Russian cities: Chelyabinsk, Yekaterinburg, and Barnaul from 2005 to 2011. We described the structure of temporal variations using a new class of singular spectral analysis (SSA) models based on the “Caterpillar” algorithm. We then fitted Poisson polyharmonic regression (PPHR) models and examined the relationship between daily RI rates and ambient temperature. In SSA models, RI rates reached their seasonal peaks around 24 February, 5 March, and 12 March (i.e., the 55.17 ± 3.21, 64.17 ± 5.12, and 71.11 ± 7.48 day of the year) in Chelyabinsk, Yekaterinburg, and Barnaul, respectively. Yet, in all three cities, the minimum temperature was observed, on average, to be on 15 January, which translates to a lag between the peak in disease incidence and time of temperature minimum of 38–40 days for Chelyabinsk, 45–49 days in Yekaterinburg, and 56–59 days in Barnaul. The proposed approach takes advantage of an accurate description of the time series data offered by the SSA-model coupled with a straightforward interpretation of the PPHR model. By better tailoring analytical methodology to estimate seasonal features and understand the relationships between infection and environmental conditions, regional and global disease forecasting can be further improved.

Suggested Citation

  • 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.
  • Handle: RePEc:gam:jijerp:v:16:y:2019:i:22:p:4309-:d:283990
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    References listed on IDEAS

    as
    1. Katarina Ureña-Castro & Silvia Ávila & Mariela Gutierrez & Elena N. Naumova & Rolando Ulloa-Gutierrez & Alfredo Mora-Guevara, 2019. "Seasonality of Rotavirus Hospitalizations at Costa Rica’s National Children’s Hospital in 2010–2015," IJERPH, MDPI, vol. 16(13), pages 1-13, June.
    2. Pavel S. Stashevsky & Irina N. Yakovina & Tania M. Alarcon Falconi & Elena N. Naumova, 2019. "Agglomerative Clustering of Enteric Infections and Weather Parameters to Identify Seasonal Outbreaks in Cold Climates," IJERPH, MDPI, vol. 16(12), pages 1-19, June.
    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.
    4. 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.
    5. Jyotsna S. Jagai & Jeffrey K. Griffiths & Paul K. Kirshen & Patrick Webb & Elena N. Naumova, 2012. "Seasonal Patterns of Gastrointestinal Illness and Streamflow along the Ohio River," IJERPH, MDPI, vol. 9(5), pages 1-20, May.
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    Cited by:

    1. 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.
    2. 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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