Analysis and prediction of hand, foot and mouth disease incidence in China using Random Forest and XGBoost
文献类型：期刊论文
| 作者 | Meng, Delin1; Xu, Jun2; Zhao, Jijun1 |
| 刊名 | PLOS ONE
 |
| 出版日期 | 2021-12-22 |
| 卷号 | 16期号:12页码:16 |
| ISSN号 | 1932-6203 |
| DOI | 10.1371/journal.pone.0261629 |
| 通讯作者 | Zhao, Jijun(jjzhao@qdu.edu.cn) |
| 英文摘要 | Hand, foot and mouth disease (HFMD) is an increasingly serious public health problem, and it has caused an outbreak in China every year since 2008. Predicting the incidence of HFMD and analyzing its influential factors are of great significance to its prevention. Now, machine learning has shown advantages in infectious disease models, but there are few studies on HFMD incidence based on machine learning that cover all the provinces in mainland China. In this study, we proposed two different machine learning algorithms, Random Forest and eXtreme Gradient Boosting (XGBoost), to perform our analysis and prediction. We first used Random Forest to examine the association between HFMD incidence and potential influential factors for 31 provinces in mainland China. Next, we established Random Forest and XGBoost prediction models using meteorological and social factors as the predictors. Finally, we applied our prediction models in four different regions of mainland China and evaluated the performance of them. Our results show that: 1) Meteorological factors and social factors jointly affect the incidence of HFMD in mainland China. Average temperature and population density are the two most significant influential factors; 2) Population flux has different delayed effect in affecting HFMD incidence in different regions. From a national perspective, the model using population flux data delayed for one month has better prediction performance; 3) The prediction capability of XGBoost model was better than that of Random Forest model from the overall perspective. XGBoost model is more suitable for predicting the incidence of HFMD in mainland China. |
| WOS关键词 | DYNAMICS ; TRANSMISSION ; INFECTIONS ; CITY |
| 资助项目 | Natural Science Foundation of Shandong[ZR2018MH037] |
| WOS研究方向 | Science & Technology - Other Topics |
| 语种 | 英语 |
| WOS记录号 | WOS:000755251000047 |
| 出版者 | PUBLIC LIBRARY SCIENCE |
| 资助机构 | Natural Science Foundation of Shandong |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/170939]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Zhao, Jijun |
| 作者单位 | 1.Qingdao Univ, Complex Sci Inst, Qingdao, Shandong, Peoples R China 2.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing, Peoples R China |
| 推荐引用方式 GB/T 7714 | Meng, Delin,Xu, Jun,Zhao, Jijun. Analysis and prediction of hand, foot and mouth disease incidence in China using Random Forest and XGBoost[J]. PLOS ONE,2021,16(12):16. |
| APA | Meng, Delin,Xu, Jun,&Zhao, Jijun.(2021).Analysis and prediction of hand, foot and mouth disease incidence in China using Random Forest and XGBoost.PLOS ONE,16(12),16. |
| MLA | Meng, Delin,et al."Analysis and prediction of hand, foot and mouth disease incidence in China using Random Forest and XGBoost".PLOS ONE 16.12(2021):16. |
入库方式： OAI收割
来源：地理科学与资源研究所
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