Analysis on the Impacting Factors of Hand, Foot and Mouth Disease Incidence Using Random Forest
2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS)(2021)
摘要
Hand, foot and mouth disease (HFMD) has circulated in China and caused yearly outbreak. In order to find the impacting factors that affect HFMD incidence, we used Random Forest to examine the association between HFMD incidence and potential variables for 31 provinces in mainland China. We also used the K-means clustering algorithm to classify 31 provinces by potential variables. Our results show that: 1) Incidence patterns of HFMD cannot be fully explained by geographical proximity; climate variables alone cannot explain the spread of HFMD; 2) Population flux plays an important role in affecting HFMD incidence, especially in China's four municipalities; 3) Average temperature is the one that affects HFMD incidence the most among all climatic variables. Among all 31 provinces in mainland China, average temperature is the primary impacting factor in 24 provinces.
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关键词
Hand foot and mouth disease,Random Forest,K-means clustering algorithm
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