Analysis of monitoring of Mycoplasma pneumoniae infection in residents based on big data platforms
LU Jie
YAN Xuanchen
HU Xiaobin
LIU Hongliang
PU Xuhong
Abstract：Objective Digging data resources from big data platforms to lay the foundation for targeted construction of regional disease monitoring and early warning systems.Method Based on the results of spatial autocorrelation analysis,identify hot and cold spot medical areas,and draw a spatial heatmap of the number of visits to residents with Mycoplasma pneumoniae infection;intergroup comparisons were conducted using chi square test or Fisher's exact test.Results The number of visits for Mycoplasma pneumoniae infection among residents in Gansu Province fluctuated significantly over time.The number of visits to different cities(x2=1 635.627)and age groups(x2=42.997)showed statistically significant differences(P＜0.001).The regional clustering of local areas had certain etiological implications;the main infected population was children aged 0-10.The number of visits by women was significantly higher than that of men(x2=20.159,P＜0.001).Conclusion After the autumn of 2023,the number of residents infected with Mycoplasma pneumoniae in Gansu Province has increased sharply,and some cities have shown a trend of regional clustering.The seasonality of this epidemic is not obvious,and there is also a peak in medical visits during the summer.Women are more susceptible than men.The average age of patients seeking medical treatment has decreased.It is necessary to fully tap into the advantages of big data platforms and unleash their potential in disease monitoring and early warning.
Keywords：big data platformsMycoplasma pneumoniae infectiondisease monitoring
Publication Date：2024-04-20
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：4( 164-167 )