IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v16y2019i22p4309-d283990.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/16/22/4309/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/16/22/4309/
    Download Restriction: no
    ---><---

    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. 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. 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.
    4. 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.
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Elena N. Naumova & Ryan B. Simpson & Bingjie Zhou & Meghan A. Hartwick, 2022. "Global seasonal and pandemic patterns in influenza: An application of longitudinal study designs," International Statistical Review, International Statistical Institute, vol. 90(S1), pages 82-95, December.
    2. Yutong Zhang & Ryan B. Simpson & Lauren E. Sallade & Emily Sanchez & Kyle M. Monahan & Elena N. Naumova, 2022. "Evaluating Completeness of Foodborne Outbreak Reporting in the United States, 1998–2019," IJERPH, MDPI, vol. 19(5), pages 1-19, March.
    3. Ryan B. Simpson & Sofia Babool & Maia C. Tarnas & Paulina M. Kaminski & Meghan A. Hartwick & Elena N. Naumova, 2021. "Signatures of Cholera Outbreak during the Yemeni Civil War, 2016–2019," IJERPH, MDPI, vol. 19(1), pages 1-29, December.
    4. Tania M. Alarcon Falconi & Bertha Estrella & Fernando Sempértegui & Elena N. Naumova, 2020. "Effects of Data Aggregation on Time Series Analysis of Seasonal Infections," IJERPH, MDPI, vol. 17(16), pages 1-21, August.
    5. 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.
    6. 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.
    7. Xiaoli Wang & Shuangsheng Wu & C Raina MacIntyre & Hongbin Zhang & Weixian Shi & Xiaomin Peng & Wei Duan & Peng Yang & Yi Zhang & Quanyi Wang, 2015. "Using an Adjusted Serfling Regression Model to Improve the Early Warning at the Arrival of Peak Timing of Influenza in Beijing," PLOS ONE, Public Library of Science, vol. 10(3), pages 1-14, March.
    8. Supachai Nakapan & Nitin Kumar Tripathi & Taravudh Tipdecho & Marc Souris, 2012. "Spatial Diffusion of Influenza Outbreak-Related Climate Factors in Chiang Mai Province, Thailand," IJERPH, MDPI, vol. 9(11), pages 1-19, October.
    9. Jonathon D. Gass & Nichola J. Hill & Lambodhar Damodaran & Elena N. Naumova & Felicia B. Nutter & Jonathan A. Runstadler, 2023. "Ecogeographic Drivers of the Spatial Spread of Highly Pathogenic Avian Influenza Outbreaks in Europe and the United States, 2016–Early 2022," IJERPH, MDPI, vol. 20(11), pages 1-17, June.
    10. Ayaz Hyder & David L Buckeridge & Brian Leung, 2013. "Predictive Validation of an Influenza Spread Model," PLOS ONE, Public Library of Science, vol. 8(6), pages 1-20, June.
    11. 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.
    12. Wengao Lu & Jingxin Li & Jinsong Li & Danni Ai & Hong Song & Zhaojun Duan & Jian Yang, 2021. "Short-Term Impacts of Meteorology, Air Pollution, and Internet Search Data on Viral Diarrhea Infection among Children in Jilin Province, China," IJERPH, MDPI, vol. 18(21), pages 1-15, November.
    13. Aishwarya Venkat & Tania M. Alarcon Falconi & Melissa Cruz & Meghan A. Hartwick & Shalini Anandan & Naveen Kumar & Honorine Ward & Balaji Veeraraghavan & Elena N. Naumova, 2019. "Spatiotemporal Patterns of Cholera Hospitalization in Vellore, India," IJERPH, MDPI, vol. 16(21), pages 1-14, November.
    14. Coleman, Stephen, 2018. "Geographical Distributions and Equilibrium in Social Norm-Related Behavior in the United States," MPRA Paper 96207, University Library of Munich, Germany.
    15. Ninon A. Becquart & Elena N. Naumova & Gitanjali Singh & Kenneth K. H. Chui, 2018. "Cardiovascular Disease Hospitalizations in Louisiana Parishes’ Elderly before, during and after Hurricane Katrina," IJERPH, MDPI, vol. 16(1), pages 1-22, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:16:y:2019:i:22:p:4309-:d:283990. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.