Abstract
Malaria is a vector-borne disease transmitted by Anopheline mosquitoes. In Korea, Plasmodium vivax malaria is an endemic disease and the main vector is Anopheles sinensis. Plasmodium vivax malaria is common in the northwestern part of South Korea, including in the city of Goyang in regions near the demilitarized zone. This study aimed to identify the best time-series model for predicting mosquito average abundance in Goyang, Korea. Mosquito data were obtained from the Mosquito Surveillance Program of the Goyang Ilsanseogu Public Health Center for the period 2008-2012. Black light traps were set up periodically in a park, a senior community center, and a village community center, public health center, drainage pumping station, cactus research center, restaurant near forest, in which many activities occur at night. In total, 9,512 female mosquitoes were collected at 12 permanent trapping sites during the mosquito season in the study period. Weekly An. sinensis average abundance was positively correlated with minimum grass temperature (r = 0.694, p < 0.001), precipitation (r = 0.326, p = 0.001). The results showed that seasonal autoregressive integrated moving average (SARIMA) (1,0,0)(0,0,1)21 with minimum grass temperature variable at time lag0 weeks and the precipitation variable at time lag1 weeks provided that best model of mosquito average abundance. The multivariate model accounted for about 54.1% of the mosquito average abundance variation. Time-series analysis of mosquito average abundance and climate factors provided basic information for predicting the occurrence of malaria mosquitoes.