Time Series Analysis of Hemorrhagic Fever with Renal Syndrome: A Case Study in Jiaonan County, China
文献类型：SCI/SSCI论文
| 作者 | Li S. J.; Cao, W. ; Ren, H. Y.; Lu, L.; Zhuang, D. F.; Liu, Q. Y.
|
| 发表日期 | 2016 |
| 关键词 | republic-of-china united-states transmission variability model |
| 英文摘要 | Exact prediction of Hemorrhagic fever with renal syndrome (HFRS) epidemics must improve to establish effective preventive measures in China. A Seasonal Autoregressive Integrated Moving Average (SARIMA) model was applied to establish a highly predictive model of HFRS. Meteorological factors were considered external variables through a cross correlation analysis. Then, these factors were included in the SARIMA model to determine if they could improve the predictive ability of HFRS epidemics in the region. The optimal univariate SARIMA model was identified as (0,0,2)(1,1,1)(12). The R-2 of the prediction of HFRS cases from January 2014 to December 2014 was 0.857, and the Root mean square error (RMSE) was 2.708. However, the inclusion of meteorological variables as external regressors did not significantly improve the SARIMA model. This result is likely because seasonal variations in meteorological variables were included in the seasonal characteristics of the HFRS itself. |
| 出处 | Plos One |
| 卷 | 11 |
| 期 | 10 |
| 语种 | 英语 |
| ISSN号 | 1932-6203 |
| DOI标识 | 10.1371/journal.pone.0163771 |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/43066]  |
| 专题 | 地理科学与资源研究所_历年回溯文献 |
| 推荐引用方式 GB/T 7714 | Li S. J.,Cao, W.,Ren, H. Y.,et al. Time Series Analysis of Hemorrhagic Fever with Renal Syndrome: A Case Study in Jiaonan County, China. 2016. |
入库方式： OAI收割
来源：地理科学与资源研究所
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