Abstract
To study the influence and correlation of meteorological factors on the incidence of Henoch-SchÖnlein purpura (HSP), and to establish the grade prediction equation for the number of HSP incidents based on meteorological factors. Methods The data of 7027 HSP cases and meteorological data in the same period from January 2010 to December 2019 in the No.1 People’s hospital of Jining were analysed the number of HSP incidents was classified by K-means cluster analysis. Correlation analysis was used to explore the correlation between various meteorological factors and the number of HSP incidents in the same period, the stepwise regression method was applied to establish the grade prediction equation for the number of HSP incidents in different periods, and the prediction equation was used to verify the grade regression verification. Results The number of HSP incidents in Jining presented different distribution under the influence of different meteorological factors, according to the actual number of HSP incidents, the whole year was divided into three periods, and the number of HSP incidents in each period was different from the meteorological factors with high correlation in the corresponding period. The daily grade prediction equation of the number of HSP incidents based on significant meteorological factors was used to verify the grade back substitution, and the prediction results proved that it had a strong prediction ability. Conclusions The number of HSP incidents in Jining was correlated with the meteorological factors in the same period, the grade prediction equation of the number of HSP incidents in different periods based on meteorological factors had strong prediction ability.
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Acknowledgements
This research was funded by the Natural Science Foundation of Shandong Province (ZR2020MD053), the Scientific Research Project of Shandong Meteorological Bureau (2019sdqxm19).
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Li, F., Guo, Z. (2023). Analysis and Forecast of Meteorological Factors on Henoch-SchÖnlein Purpura in Jining. In: Wen, S., Yang, C. (eds) Biomedical and Computational Biology. BECB 2022. Lecture Notes in Computer Science(), vol 13637. Springer, Cham. https://doi.org/10.1007/978-3-031-25191-7_19
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DOI: https://doi.org/10.1007/978-3-031-25191-7_19
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