Modeling and analysis of mosquito and environmental data to predict the risk of Japanese encephalitis

Culex tritaeniorhynchus is the primary vector of Japanese encephalitis virus (JEV) throughout much of the tropical and temperate climates of Asia. Several recent papers have used ecological niche modeling programs, e.g., Maxent and GARP, to predict the distribution of disease vectors (e.g. Peterson and Shaw 2003, Moffett et al. 2007). In this on-going study, we used the Maxent program to model the distribution of Cx. tritaeniorhynchus in the Republic of Korea. Using mosquito collection data, temperature, precipitation, elevation, land cover, and SPOT normalized difference vegetation index (NDVI), models were created for each month for a period of five years. Output maps from the models matched several known ecological characteristics of this species' distribution. The output maps show the highest probabilities of mosquito occurrence in August and September, which correlates to the observed mosquito population density peaks. The model demonstrated low probabilities for forest covered mountains, which corresponds to findings in the literature that Cx. tritaeniorhynchus is infrequently found above 1,000 meters. The modeling effort demonstrated several limitations in the data set, including a low number of collection sites that did not cover the full range of environmental conditions within the study area. Additional collection sites would improve the models and allow for improved testing of the results. Future goals of this project include developing real-time predictions based on NDVI data and expanding the prediction to a larger geographical area.