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Short-Term Impacts of Meteorology, Air Pollution, and Internet Search Data on Viral Diarrhea Infection among Children in Jilin Province, China

Author

Listed:
  • Wengao Lu

    (Department of Computer Science and Technology, Beijing Institute of Technology, Beijing 100081, China
    Authors contributed equally to this work.)

  • Jingxin Li

    (National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
    Authors contributed equally to this work.)

  • Jinsong Li

    (National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China)

  • Danni Ai

    (Laboratory of Beijing Engineering Research Center of Mixed Reality and Advanced Display, School of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, China)

  • Hong Song

    (Department of Computer Science and Technology, Beijing Institute of Technology, Beijing 100081, China)

  • Zhaojun Duan

    (National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China)

  • Jian Yang

    (Laboratory of Beijing Engineering Research Center of Mixed Reality and Advanced Display, School of Optics and Photonics, Beijing Institute of Technology, Beijing 100081, China)

Abstract

The influence of natural environmental factors and social factors on children’s viral diarrhea remains inconclusive. This study aimed to evaluate the short-term effects of temperature, precipitation, air quality, and social attention on children’s viral diarrhea in temperate regions of China by using the distribution lag nonlinear model (DLNM). We found that low temperature affected the increase in children’s viral diarrhea infection for about 1 week, while high temperature and heavy precipitation affected the increase in children’s viral diarrhea infection risk for at least 3 weeks. As the increase of the air pollution index may change the daily life of the public, the infection of children’s viral diarrhea can be restrained within 10 days, but the risk of infection will increase after 2 weeks. The extreme network search may reflect the local outbreak of viral diarrhea, which will significantly improve the infection risk. The above factors can help the departments of epidemic prevention and control create early warnings of high-risk outbreaks in time and assist the public to deal with the outbreak of children’s viral diarrhea.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:21:p:11615-:d:672438
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    References listed on IDEAS

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    1. Gasparrini, Antonio, 2011. "Distributed Lag Linear and Non-Linear Models in R: The Package dlnm," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 43(i08).
    2. 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.
    3. Jeremy Ginsberg & Matthew H. Mohebbi & Rajan S. Patel & Lynnette Brammer & Mark S. Smolinski & Larry Brilliant, 2009. "Detecting influenza epidemics using search engine query data," Nature, Nature, vol. 457(7232), pages 1012-1014, February.
    4. Declan Butler, 2013. "When Google got flu wrong," Nature, Nature, vol. 494(7436), pages 155-156, February.
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