• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

[自回归积分滑动平均模型在疟疾发病率预测中的应用]

[Application of ARIMA model on prediction of malaria incidence].

作者信息

Jing Xia, Hua-Xun Zhang, Wen Lin, Su-Jian Pei, Ling-Cong Sun, Xiao-Rong Dong, Mu-Min Cao, Dong-Ni Wu, Shunxiang Cai

机构信息

Institute of Schistosomiasis Control, Hubei Provincial Center for Disease Control and Prevention, Wuhan 430079, China.

出版信息

Zhongguo Xue Xi Chong Bing Fang Zhi Za Zhi. 2016 Jan 29;28(2):135-140. doi: 10.16250/j.32.1374.2015207.

DOI:10.16250/j.32.1374.2015207
PMID:29469288
Abstract

OBJECTIVE

To predict the incidence of local malaria of Hubei Province applying the Autoregressive Integrated Moving Average model (ARIMA).

METHODS

SPSS 13.0 software was applied to construct the ARIMA model based on the monthly local malaria incidence in Hubei Province from 2004 to 2009. The local malaria incidence data of 2010 were used for model validation and evaluation.

RESULTS

The model of ARIMA (1, 1, 1) (1, 1, 0) was tested as relatively the best optimal with the AIC of 76.085 and SBC of 84.395. All the actual incidence data were in the range of 95% of predicted value of the model. The prediction effect of the model was acceptable.

CONCLUSIONS

The ARIMA model could effectively fit and predict the incidence of local malaria of Hubei Province.

摘要

目的

应用自回归积分滑动平均模型(ARIMA)预测湖北省本地疟疾的发病率。

方法

运用SPSS 13.0软件,基于2004年至2009年湖北省本地疟疾月发病率构建ARIMA模型。2010年的本地疟疾发病率数据用于模型验证和评估。

结果

ARIMA(1, 1, 1)(1, 1, 0)模型经检验为相对最佳模型,AIC为76.085,SBC为84.395。所有实际发病率数据均在模型预测值的95%范围内。该模型的预测效果可接受。

结论

ARIMA模型能够有效拟合和预测湖北省本地疟疾的发病率。

相似文献

1
[Application of ARIMA model on prediction of malaria incidence].[自回归积分滑动平均模型在疟疾发病率预测中的应用]
Zhongguo Xue Xi Chong Bing Fang Zhi Za Zhi. 2016 Jan 29;28(2):135-140. doi: 10.16250/j.32.1374.2015207.
2
[Application of ARIMA model to predict number of malaria cases in China].[自回归积分滑动平均模型在预测中国疟疾病例数中的应用]
Zhongguo Xue Xi Chong Bing Fang Zhi Za Zhi. 2017 Aug 15;29(4):436-440. doi: 10.16250/j.32.1374.2017088.
3
[Study on the feasibility for ARIMA model application to predict malaria incidence in an unstable malaria area].[自回归积分滑动平均(ARIMA)模型应用于不稳定疟区疟疾发病率预测的可行性研究]
Zhongguo Ji Sheng Chong Xue Yu Ji Sheng Chong Bing Za Zhi. 2007 Jun;25(3):232-6.
4
[Application of multiple seasonal autoregressive integrated moving average model in predicting the mumps incidence].多重季节性自回归积分滑动平均模型在预测流行性腮腺炎发病率中的应用
Zhonghua Yu Fang Yi Xue Za Zhi. 2015 Dec;49(12):1042-6.
5
[Establishing and applying of autoregressive integrated moving average model to predict the incidence rate of dysentery in Shanghai].[自回归积分滑动平均模型的建立与应用以预测上海市痢疾发病率]
Zhonghua Yu Fang Yi Xue Za Zhi. 2010 Jan;44(1):48-53.
6
[Prediction of epidemic tendency of schistosomiasis with time-series model in Hubei Province].[湖北省血吸虫病流行趋势的时间序列模型预测]
Zhongguo Xue Xi Chong Bing Fang Zhi Za Zhi. 2014 Dec;26(6):613-7.
7
[Prediction of schistosomiasis infection rates of population based on ARIMA-NARNN model].基于ARIMA-NARNN模型的人群血吸虫病感染率预测
Zhongguo Xue Xi Chong Bing Fang Zhi Za Zhi. 2016 Jul 12;28(6):630-634. doi: 10.16250/j.32.1374.2016089.
8
[Application of ARIMA model in predicting the incidence of tuberculosis in China from 2018 to 2019].[自回归积分滑动平均(ARIMA)模型在预测2018年至2019年中国结核病发病率中的应用]
Zhonghua Liu Xing Bing Xue Za Zhi. 2019 Jun 10;40(6):633-637. doi: 10.3760/cma.j.issn.0254-6450.2019.06.006.
9
[Study on the ARIMA model application to predict echinococcosis cases in China].[应用自回归积分滑动平均模型预测中国棘球蚴病病例的研究]
Zhongguo Xue Xi Chong Bing Fang Zhi Za Zhi. 2018 Feb 26;30(1):47-53. doi: 10.16250/j.32.1374.2017173.
10
[Autoregressive integrated moving average model in food poisoning prediction in Hunan Province].[自回归积分滑动平均模型在湖南省食物中毒预测中的应用]
Zhong Nan Da Xue Xue Bao Yi Xue Ban. 2012 Feb;37(2):142-6. doi: 10.3969/j.issn.1672-7347.2012.02.005.