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PHRP : Osong Public Health and Research Perspectives

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Original Article

Prediction Forecast for Culex tritaeniorhynchus Populations in Korea

Osong Public Health and Research Perspectives 2014;5(3):131-137.
Published online: May 16, 2014

aSchool of Economics, Sungkyunkwan University, Seoul, Korea

bDivision of Medical Entomology, Korea National Institute of Health, Osong, Korea

∗Corresponding author. miyeoun@korea.kr
1N.-H.K. and W.-G.L are co-first authors of the paper.
• Received: April 1, 2014   • Revised: April 17, 2014   • Accepted: April 27, 2014

© 2014 Published by Elsevier B.V. on behalf of Korea Centers for Disease Control and Prevention.

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/3.0/).

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  • Genetic diversity and Wolbachia infection in the Japanese encephalitis virus vector Culex tritaeniorhynchus in the Republic of Korea
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    Emerging Microbes & Infections.2020; 9(1): 496.     CrossRef
  • The mitochondrial genomes of Culex tritaeniorhynchus and Culex pipiens pallens (Diptera: Culicidae) and comparison analysis with two other Culex species
    Qian-Chun Luo, You-Jin Hao, Fengxia Meng, Ting-Jing Li, Yi-Ran Ding, Ya-Qiong Hua, Bin Chen
    Parasites & Vectors.2016;[Epub]     CrossRef

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Prediction Forecast for Culex tritaeniorhynchus Populations in Korea
Osong Public Health Res Perspect. 2014;5(3):131-137.   Published online June 30, 2014
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Prediction Forecast for Culex tritaeniorhynchus Populations in Korea
Image Image Image Image
Figure 1 Distribution of mosquitoes and Culex tritaeniorhynchus (CT) per year.
Figure 2 Autocorrelation.
Figure 3 Out-of-sample results used in rolling window regression (weekly data). CT, Culex tritaeniorhynchus. RC: Rolling window regression of CT.
Figure 4 Out-of-sample results used in adding window regression (weekly data). CT, Culex tritaeniorhynchus. AC: Adding window regression of CT.
Prediction Forecast for Culex tritaeniorhynchus Populations in Korea
Table 1 Unit root test (level variables).

*Significant at the 1% level.

ADF = augmented Dickey–Fuller test; PP = Phillips–Perron test.

Table 2 Basic statistical data on mosquito density.

The number in parenthesis represent standard deviation.

* Significant at the 1% level.

Table 3 Time lag test.

AIC = Akaike information criterion; SIC = Schwarz information criteria.

Table 4 Autoregressive model estimation (weekly data).

The results of the autoregressive model showed no differences in superiority with that of autoregressive–moving-average model.

The results of the weekly data were similar to that of the monthly data. Thus, the weekly data, which consists of more data, is described.

* Significant at p < 0.05.

** Significant at p < 0.01.

*** Significant at p < 0.01.

Table 5 MSE of in-sample.

MSE = mean square error.

Table 6 MSPE of out-of-sample prediction.

AD = adding regression; MSPE = mean-square prediction error; RO = rolling regression.