IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v19y2022i11p6625-d827090.html
   My bibliography  Save this article

Association between Meteorological Factors and Mumps and Models for Prediction in Chongqing, China

Author

Listed:
  • Hong Zhang

    (School of Public Health and Management, Chongqing Medical University, Chongqing 400016, China
    These authors contributed equally to this work.)

  • Kun Su

    (School of Public Health and Management, Chongqing Medical University, Chongqing 400016, China
    Chongqing Municipal Center for Disease Control and Prevention, Chongqing 400042, China
    Chongqing Public Health Medical Center, Chongqing 400036, China
    These authors contributed equally to this work.)

  • Xiaoni Zhong

    (School of Public Health and Management, Chongqing Medical University, Chongqing 400016, China)

Abstract

(1) Background: To explore whether meteorological factors have an impact on the prevalence of mumps, and to make a short–term prediction of the case number of mumps in Chongqing. (2) Methods: K–means clustering algorithm was used to divide the monthly mumps cases of each year into the high and low case number clusters, and Student t –test was applied for difference analysis. The cross–correlation function (CCF) was used to evaluate the correlation between the meteorological factors and mumps, and an ARIMAX model was constructed by additionally incorporating meteorological factors as exogenous variables in the ARIMA model, and a short–term prediction was conducted for mumps in Chongqing, evaluated by MAE, RMSE. (3) Results: All the meteorological factors were significantly different ( p < 0.05), except for the relative humidity between the high and low case number clusters. The CCF and ARIMAX model showed that monthly precipitation, temperature, relative humidity and wind velocity were associated with mumps, and there were significant lag effects. The ARIMAX model could accurately predict mumps in the short term, and the prediction errors (MAE, RMSE) were lower than those of the ARIMA model. (4) Conclusions: Meteorological factors can affect the occurrence of mumps, and the ARIMAX model can effectively predict the incidence trend of mumps in Chongqing, which can provide an early warning for relevant departments.

Suggested Citation

  • Hong Zhang & Kun Su & Xiaoni Zhong, 2022. "Association between Meteorological Factors and Mumps and Models for Prediction in Chongqing, China," IJERPH, MDPI, vol. 19(11), pages 1-11, May.
  • Handle: RePEc:gam:jijerp:v:19:y:2022:i:11:p:6625-:d:827090
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/19/11/6625/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/19/11/6625/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Qinqin Xu & Runzi Li & Yafei Liu & Cheng Luo & Aiqiang Xu & Fuzhong Xue & Qing Xu & Xiujun Li, 2017. "Forecasting the Incidence of Mumps in Zibo City Based on a SARIMA Model," IJERPH, MDPI, vol. 14(8), pages 1-11, August.
    2. Yuchen Zhu & Dandan Zhang & Yuchen Hu & Chunyu Li & Yan Jia & Kaili She & Tingxuan Liu & Qing Xu & Ying Zhang & Xiujun Li, 2021. "Exploring the Relationship between Mumps and Meteorological Factors in Shandong Province, China Based on a Two-Stage Model," IJERPH, MDPI, vol. 18(19), pages 1-13, October.
    Full references (including those not matched with items on IDEAS)

    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. Yong Li & Xianning Liu & Lianwen Wang, 2017. "Modelling the Transmission Dynamics and Control of Mumps in Mainland China," IJERPH, MDPI, vol. 15(1), pages 1-17, December.
    2. Li Wen & Danling Yang & Yanning Li & Dongjia Lu & Haixia Su & Mengying Tang & Xiaokun Song, 2022. "Spatial Effect of Ecological Environmental Factors on Mumps in China during 2014–2018," IJERPH, MDPI, vol. 19(23), pages 1-16, November.
    3. Wei Kit Phang & Mohd Hafizi Abdul Hamid & Jenarun Jelip & Rose Nani Mudin & Ting-Wu Chuang & Yee Ling Lau & Mun Yik Fong, 2020. "Spatial and Temporal Analysis of Plasmodium knowlesi Infection in Peninsular Malaysia, 2011 to 2018," IJERPH, MDPI, vol. 17(24), pages 1-21, 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:19:y:2022:i:11:p:6625-:d:827090. 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.