BACKGROUND: Japanese encephalitis virus (JEV), the causative agent of Japanese encephalitis (JE), is endemic to the Republic of Korea (ROK) where unvaccinated United States (U.S.) military Service members, civilians and family members are stationed. The primary vector of the JEV in the ROK is Culex tritaeniorhynchus. The ecological relationship between Culex spp. and rice fields has been studied extensively; rice fields have been shown to increase the prevalence of Cx. tritaeniorhynchus. This research was conducted to determine if the quantification of rice field land cover surrounding U.S. military installations in the ROK should be used as a parameter in a larger risk model that predicts the abundance of Cx. tritaeniorhynchus populations. Mosquito data from the U.S. Forces Korea (USFK) mosquito surveillance program were used in this project. The average number of female Cx. tritaeniorhynchus collected per trap night for the months of August and September, 2002-2008, was calculated. Rice fields were manually digitized inside 1.5 km buffer zones surrounding U.S. military installations on high-resolution satellite images, and the proportion of rice fields was calculated for each buffer zone. RESULTS: Mosquito data collected from seventeen sample sites were analyzed for an association with the proportion of rice field land cover. Results demonstrated that the linear relationship between the proportion of rice fields and mosquito abundance was statistically significant (R2 = 0.62, r = .79, F = 22.72, p < 0.001). CONCLUSIONS: The analysis presented shows a statistically significant linear relationship between the two parameters, proportion of rice field land cover and log10 of the average number of Cx. tritaeniorhynchus collected per trap night. The findings confirm that agricultural land cover should be included in future studies to develop JE risk prediction models for non-indigenous personnel living at military installations in the ROK.
BACKGROUND:Japanese encephalitis virus (JEV), the causative agent of Japanese encephalitis (JE), is endemic to the Republic of Korea (ROK) where unvaccinated United States (U.S.) military Service members, civilians and family members are stationed. The primary vector of the JEV in the ROK is Culex tritaeniorhynchus. The ecological relationship between Culex spp. and rice fields has been studied extensively; rice fields have been shown to increase the prevalence of Cx. tritaeniorhynchus. This research was conducted to determine if the quantification of rice field land cover surrounding U.S. military installations in the ROK should be used as a parameter in a larger risk model that predicts the abundance of Cx. tritaeniorhynchus populations. Mosquito data from the U.S. Forces Korea (USFK) mosquito surveillance program were used in this project. The average number of female Cx. tritaeniorhynchus collected per trap night for the months of August and September, 2002-2008, was calculated. Rice fields were manually digitized inside 1.5 km buffer zones surrounding U.S. military installations on high-resolution satellite images, and the proportion of rice fields was calculated for each buffer zone. RESULTS: Mosquito data collected from seventeen sample sites were analyzed for an association with the proportion of rice field land cover. Results demonstrated that the linear relationship between the proportion of rice fields and mosquito abundance was statistically significant (R2 = 0.62, r = .79, F = 22.72, p < 0.001). CONCLUSIONS: The analysis presented shows a statistically significant linear relationship between the two parameters, proportion of rice field land cover and log10 of the average number of Cx. tritaeniorhynchus collected per trap night. The findings confirm that agricultural land cover should be included in future studies to develop JE risk prediction models for non-indigenous personnel living at military installations in the ROK.
Authors: T Solomon; N M Dung; R Kneen; M Gainsborough; D W Vaughn; V T Khanh Journal: J Neurol Neurosurg Psychiatry Date: 2000-04 Impact factor: 10.154
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Authors: Daniel E Impoinvil; Tom Solomon; W William Schluter; Ajit Rayamajhi; Ram Padarath Bichha; Geeta Shakya; Cyril Caminade; Matthew Baylis Journal: PLoS One Date: 2011-07-21 Impact factor: 3.240
Authors: Alexandra Hiscox; Phasouk Khammanithong; Surinder Kaul; Pany Sananikhom; Ruedi Luthi; Nigel Hill; Paul T Brey; Steve W Lindsay Journal: PLoS One Date: 2013-05-20 Impact factor: 3.240