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.
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]. Chinese Journal of Vector Biology and Control, 2018
, 29(6)
: 545
-549
.
DOI: 10.11853/j.issn.1003.8280.2018.06.001
[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.
