基于R语言自回归积分移动平均模型的广州市白纹伊蚊密度预测研究

doi:10.11853/j.issn.1003.8280.2018.06.001

中国媒介生物学及控制杂志 ›› 2018, Vol. 29 ›› Issue (6): 545-549.DOI: 10.11853/j.issn.1003.8280.2018.06.001

• 论著 • 下一篇

基于R语言自回归积分移动平均模型的广州市白纹伊蚊密度预测研究

潘衍宇, 吴海霞, 国佳, 刘起勇

中国疾病预防控制中心传染病预防控制所, 传染病预防控制国家重点实验室, 感染性疾病诊治协同创新中心, 世界卫生组织媒介生物监测与管理合作中心, 北京 102206

收稿日期:2018-06-22 出版日期:2018-12-20 发布日期:2018-12-20
通讯作者: 刘起勇,Email:liuqiyong@icdc.cn
作者简介:潘衍宇,男,在读硕士,从事分子流行病学研究,Email:934955946@qq.com
基金资助:
国家重点研发计划（2016YFC1200802）；国家重大科学研究计划（2012CB955504）

Population density prediction of Adeds albopictus in Guangzhou based on autoregressive integrated moving average model

PAN Yan-yu, WU Hai-xia, GUO Jia, LIU Qi-yong

State Key Laboratory of Infectious Disease Prevention and Control, National Institute for Communicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, WHO Collaborating Centre for Vector Surveillance and Management, Beijing 102206, China

Received:2018-06-22 Online:2018-12-20 Published:2018-12-20
Supported by:
Supported by the National Key Research and Development Plan (No. 2016YFC1200802) and the National Basic Research Program of China (No. 2012CB955504)

摘要/Abstract

摘要： 目的构建广州市白纹伊蚊密度自回归积分移动平均模型（ARIMA）并进行预测。方法应用R语言3.4.4将2009年1月至2017年5月的白纹伊蚊月密度数据构建ARIMA模型，进行整体回代评价拟合效果，比较2017年6-12月预测值与真实值，评价外推效果，对2018年白纹伊蚊密度进行预测。结果白纹伊蚊密度监测数据构建ARIMA（0，1，1）（0，1，1）₁₂模型，赤池信息准则（AIC）=-268.83，平稳R²=0.427；残差序列为白噪声（P>0.05），且方差齐性，证明模型有效；2017年6-12月预测值与实际值基本一致，均方根误差（RMSE）=0.087 4，平均绝对误差（MAE）=0.028 3，模型外推良好。结论 ARIMA模型能够较好地预测广州市白纹伊蚊密度消长趋势。

关键词: 时间序列, 自回归积分移动平均模型, 白纹伊蚊, 预测

Abstract: Objective To construct the autoregressive integrated moving average (ARIMA) model to predict by summarizing the density data of Aedes albopictus in Guangzhou. Methods Through the R programming language 3.4.4, the model was constituted by density of Ae. albopictus from January 2009 to June 2017, proceeded significance test of model and parameter, and evaluated the model by overall data. the predicted value and the real value from July to December 2017 were compared to evaluate the extrapolation effect. Results ARIMA (0, 1, 1) (0, 1, 1)₁₂ has been constituted with AIC=-268.83 and R²=0.427. Residual sequence was proved white noise (P>0.05) and homoscedasticity. The predicted value and the real value from July to December 2017 are approximately in agreement, showing the Root Mean Square Error (RMSE)=0.087 4 and the Mean Absolute Error (MAE)=0.028 3. Good data fit was demonstrated. Conclusion The model can well predict the density data of Ae. albopictus in Guangzhou.

Key words: Time series analysis, Autoregressive integrated moving average model, Aedes albopictus, Prediction

中图分类号:

R384.1

潘衍宇, 吴海霞, 国佳, 刘起勇. 基于R语言自回归积分移动平均模型的广州市白纹伊蚊密度预测研究[J]. 中国媒介生物学及控制杂志, 2018, 29(6): 545-549.

PAN Yan-yu, WU Hai-xia, GUO Jia, LIU Qi-yong. Population density prediction of Adeds albopictus in Guangzhou based on autoregressive integrated moving average model[J]. Chines Journal of Vector Biology and Control, 2018, 29(6): 545-549.

参考文献

[1] Huhtamo E,Cook S,Moureau G,et al. Novel flaviviruses from mosquitoes:mosquito-specific evolutionary lineages within the phylogenetic group of mosquito-borne flaviviruses[J]. Virology,2014,464-465:320-329. DOI:10.1016/j.virol.2014.07.015.
[2] Wu JY,Lun ZR,James AA,et al. Dengue fever in mainland China[J]. Am J Trop Med Hyg,2010,83(3):664-671. DOI:10.4269/ajtmh.2010.09-0755.
[3] Tran A,L'Ambert G,Balança G,et al. An integrative eco-epidemiological analysis of West Nile virus transmission[J]. Ecohealth,2017,14(3):474-489. DOI:10.1007/s10393-017-1249-6.
[4] Marabuto E,Rebelo MT. The Asian tiger mosquito,Aedes (Stegomyia) albopictus (Skuse),a vector of dengue,chikungunya and Zika viruses,reaches Portugal (Diptera:Culicidae)[J]. Zootaxa,2018,4413(1):197-200. DOI:10.11646/zootaxa. 4413.1.10.
[5] Bhatt S,Gething PW,Brady OJ,et al. The global distribution and burden of dengue[J]. Nature,2013,496(7446):504-507. DOI:10.1038/nature12060.
[6] Weetman D,Kamgang B,Badolo A,et al. Aedes mosquitoes and Aedes-borne arboviruses in Africa:current and future threats[J]. Int J Environ Res Public Health,2018,15(2):220. DOI:10.3390/ijerph15020220.
[7] 刘起勇. 寨卡病毒媒介伊蚊控制策略和措施展望[J]. 中国媒介生物学及控制杂志,2016,27(2):93-98. DOI:10.11853/j.issn.1003.8280.2016.02.001.
[8] Hamer DH,Angelo K,Caumes E,et al. Fatal yellow fever in travelers to brazil,2018[J]. MMWR Morb Mortal Wkly Rep,2018,67(11):340-341. DOI:10.15585/mmwr.mm6711e1.
[9] World Health Organization. Yellow fever-Brazil. Disease outbreak news. Geneva,Switzerland:World Health Organization[EB/OL]. (2018-02-27)[2018-05-01]. http://www.who.int/csr/don/27-february-2018-yellow-fever-brazil/en/.
[10] Chancey C,Grinev A,Volkova E,et al. The global ecology and epidemiology of West Nile virus[J]. Bio Med Res Int,2015,2015:376230. DOI:10.1155/2015/376230.
[11] Beck C,Jimenez-Clavero MA,Leblond A,et al. Flaviviruses in Europe:complex circulation patterns and their consequences for the diagnosis and control of West Nile disease[J]. Int J Environ Res Public Health,2013,10(11):6049-6083. DOI:10.3390/ijerph10116049.
[12] 孟凤霞,王义冠,冯磊,等. 我国登革热疫情防控与媒介伊蚊的综合治理[J]. 中国媒介生物学及控制杂志,2015,26(1):4-10. DOI:10.11853/j.issn.1003.4692.2015.01.002.
[13] Ferreira-de-Lima VHF,Lima-Camara TN. Natural vertical transmission of dengue virus in Aedes aegypti and Aedes albopictus:a systematic review[J]. Parasit Vectors,2018,11:77. DOI:10.1186/s13071-018-2643-9.
[14] Wong PSJ,Li MZI,Chong CS,et al. Aedes (Stegomyia) albopictus(Skuse):a potential vector of Zika virus in Singapore[J]. PLoS Negl Trop Dis,2013,7(8):e2348. DOI:10.1371/journal.pntd. 0002348.
[15] Wu F,Liu QY,Lu L,et al. Distribution of Aedes albopictus (Diptera:Culicidae) in northwestern China[J]. Vector Borne Zoonotic Dis,2011,11(8):1181-1186. DOI:10.1089/vbz. 2010.0032.
[16] Zhang XY,Liu YY,Yang M,et al. Comparative study of four time series methods in forecasting typhoid fever incidence in China[J]. PLoS One,2013,8(5):e63116. DOI:10.1371/journal.pone.0063116.
[17] Bartholomew DJ. Time series analysis forecasting and control[J]. J Oper Res Soc,1971,22(2):199-201. DOI:10.1057/jors. 1971.52.
[18] Burns P. Robustness of the Ljung-Box test and its rank equivalent[J/OL]. (2002-07-18)[2018-05-01]. https://ssrn.com/abstract=443560. DOI:10.2139/ssrn.443560.
[19] Bozdogan H. Model selection and Akaike's Information Criterion (AIC):the general theory and its analytical extensions[J]. Psychometrika,1987,52(3):345-370. DOI:10.1007/BF02294361.
[20] Benitez MA. Climate change could affect mosquito-borne diseases in Asia[J]. Lancet,2009,373(9669):1070. DOI:10. 1016/S0140-6736(09)60634-6.
[21] Reiter P. Climate change and mosquito-borne disease:knowing the horse before hitching the cart[J]. Rev Sci Tech,2008,27(2):383-398.
[22] Siriyasatien P,Phumee A,Ongruk P,et al. Analysis of significant factors for dengue fever incidence prediction[J]. BMC Bioinformatics,2016,17:166. DOI:10.1186/s12859-016-1034-5.
[23] Olliaro P,Fouque F,Kroeger A,et al. Improved tools and strategies for the prevention and control of arboviral diseases:a research-to-policy forum[J]. PLoS Negl Trop Dis,2018,12(2):e0005967. DOI:10.1371/journal.pntd.0005967.

基于R语言自回归积分移动平均模型的广州市白纹伊蚊密度预测研究

Population density prediction of Adeds albopictus in Guangzhou based on autoregressive integrated moving average model

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics

本文评价

[1]	孙钦同, 韩英男, 刘言, 王学军, 刘峰, 赖世宏, 景晓. 山东省登革热媒介白纹伊蚊生态学调查分析[J]. 中国媒介生物学及控制杂志, 2022, 33(1): 16-20.
[2]	李天奇, 刘钦梅, 吴瑜燕, 罗明宇, 王金娜, 龚震宇. 浙江省登革热重点地区2020年白纹伊蚊幼蚊种群密度监测分析[J]. 中国媒介生物学及控制杂志, 2022, 33(1): 21-24.
[3]	魏超, 马海芳, 廖宁, 熊绮梦. 广西壮族自治区2020－2021年登革热媒介伊蚊密度专项调查结果分析[J]. 中国媒介生物学及控制杂志, 2022, 33(1): 25-29.
[4]	赵春春, 周欣欣, 李文玉, 伦辛畅, 刘小波, 吴海霞, 王君, 刘起勇, 孟凤霞. 2020年中国13省份登革热媒介白纹伊蚊抗药性监测及分析研究[J]. 中国媒介生物学及控制杂志, 2022, 33(1): 30-37.
[5]	郑宇婷, 杨春梅, 杨明东, 姜进勇. 云南边境地区登革热媒介伊蚊生态学及抗药性监测[J]. 中国媒介生物学及控制杂志, 2022, 33(1): 38-43.
[6]	涂涛田, 肖汉森, 孟凤霞, 刘起勇, 刘小波, 何亚明, 季恒青. 重庆市2019年登革热暴发疫情应急控制后媒介伊蚊抗药性调查[J]. 中国媒介生物学及控制杂志, 2022, 33(1): 44-47.
[7]	周欣欣, 李芬, 段文波, 马欣然, 宋秀平, 吴少英, 孟凤霞. 白纹伊蚊电压门控钠离子通道基因克隆及其生物信息学分析[J]. 中国媒介生物学及控制杂志, 2021, 32(6): 672-679.
[8]	薛海滨, 孟金霞, 任乐, 景晓. 山东省临沂市2018－2020年白纹伊蚊幼蚊监测与风险评估[J]. 中国媒介生物学及控制杂志, 2021, 32(6): 686-690.
[9]	张育富, 张守刚, 朱丁, 顾灯安, 葛小伍, 袁建明, 崔倩, 褚宏亮. 江苏省多层住宅居民区不同楼层白纹伊蚊分布调查[J]. 中国媒介生物学及控制杂志, 2021, 32(6): 700-704.
[10]	孙钦同, 韩英男, 刘言, 赖世宏, 王学军, 康殿民. 应用自回归移动平均（ARIMA）模型预测山东省鼠密度趋势[J]. 中国媒介生物学及控制杂志, 2021, 32(6): 744-748.
[11]	周毅彬, 朱奕奕, 朱伟, 姚隽一, 朱江, 冷培恩, 吴寰宇. 诱蚊诱卵器监测的空间抽样方法研究[J]. 中国媒介生物学及控制杂志, 2021, 32(6): 749-755.
[12]	朱伟, 刘翔宇, 周毅彬. 绿篱喷洒控制白纹伊蚊密度的时空变化研究[J]. 中国媒介生物学及控制杂志, 2021, 32(6): 772-778.
[13]	郭秀霞, 程鹏, 刘丽娟, 王海防, 张崇星, 王怀位, 公茂庆. 白纹伊蚊紫外光敏感视蛋白基因的克隆及序列特征[J]. 中国媒介生物学及控制杂志, 2021, 32(5): 553-559.
[14]	张家林, 黄发源. 安徽省2015－2019年登革热媒介伊蚊监测结果分析[J]. 中国媒介生物学及控制杂志, 2021, 32(5): 582-585.
[15]	邓惠, 刘礼平, 许齐爱, 廉战民, 段金花, 陈宗晶, 芦瑞鹏, 沈秀婷, 阴伟雄, 吴军, 林立丰. 3种蚊虫引诱剂与不同流量CO₂对白纹伊蚊诱集效果的研究[J]. 中国媒介生物学及控制杂志, 2021, 32(5): 637-641.