title: Modeling the distribution of Culex tritaeniorhynchus to predict Japanese encephalitis distribution in the Republic of Korea.
abstract: Over 35,000 cases of Japanese encephalitis (JE) are reported worldwide each year. Culex tritaeniorhynchus is the primary vector of the JE virus, while wading birds are natural reservoirs and swine amplifying hosts. As part of a JE risk analysis, the ecological niche modeling programme, Maxent, was used to develop a predictive model for the distribution of Cx. tritaeniorhynchus in the Republic of Korea, using mosquito collection data, temperature, precipitation, elevation, land cover and the normalized difference vegetation index (NDVI). The resulting probability maps from the model were consistent with the known environmental limitations of the mosquito with low probabilities predicted for forest covered mountains. July minimum temperature and land cover were the most important variables in the model. Elevation, summer NDVI (July-September), precipitation in July, summer minimum temperature (May-August) and maximum temperature for fall and winter months also contributed to the model. Comparison of the Cx. tritaeniorhynchus model to the distribution of JE cases in the Republic of Korea from 2001 to 2009 showed that cases among a highly vaccinated Korean population were located in high-probability areas for Cx. tritaeniorhynchus. No recent JE cases were reported from the eastern coastline, where higher probabilities of mosquitoes were predicted, but where only small numbers of pigs are raised. The geographical distribution of reported JE cases corresponded closely with the predicted high-probability areas for Cx. tritaeniorhynchus, making the map a useful tool for health risk analysis that could be used for planning preventive public health measures.
authors.affiliation: Department of Preventive Medicine and Biometrics, Uniformed Services University of the Health Sciences, 4301 Jones Bridge Road, Bethesda, MD 20814, USA. pmasuoka@usuhs.mil
authors.forename: Penny
authors.initials: P
authors.lastname: Masuoka
authors.forename: Terry A
authors.initials: TA
authors.lastname: Klein
authors.forename: Heung-Chul
authors.initials: HC
authors.lastname: Kim
authors.forename: David M
authors.initials: DM
authors.lastname: Claborn
authors.forename: Nicole
authors.initials: N
authors.lastname: Achee
authors.forename: Richard
authors.initials: R
authors.lastname: Andre
authors.forename: Judith
authors.initials: J
authors.lastname: Chamberlin
authors.forename: Jennifer
authors.initials: J
authors.lastname: Small
authors.forename: Assaf
authors.initials: A
authors.lastname: Anyamba
authors.forename: Dong-Kyu
authors.initials: DK
authors.lastname: Lee
authors.forename: Suk H
authors.initials: SH
authors.lastname: Yi
authors.forename: Michael
authors.initials: M
authors.lastname: Sardelis
authors.forename: Young-Ran
authors.initials: YR
authors.lastname: Ju
authors.forename: John
authors.initials: J
authors.lastname: Grieco
mesh_terms: D000818:Animals; D019540:Area Under Curve; D001717:Birds; D002980:Climate; D003465:Culex; D004195:Disease Models, Animal; D004197:Disease Reservoirs; D004672:Encephalitis, Japanese / Q000175:diagnosis / Q000453:epidemiology*; D004812:Epidemiologic Methods; D005843:Geography; D006801:Humans; D015233:Models, Statistical; D011336:Probability; D012372:ROC Curve; D056910:Republic of Korea / Q000453:epidemiology; D018570:Risk Assessment; D013552:Swine