Mosquitoes were collected in the Danube Delta during the active seasons of 2011-2013. For Culex spp. mosquitoes, the abundance was calculated. Culex pipiens (sensu lato), (s.l.) and Culex modestus pools were tested for the presence of West Nile virus (WNV) genome, and the maximum likelihood of the infection rate was established. Mean daily temperatures and precipitation were obtained for the closest meteorological station. A negative binominal model was used to evaluate linkages between the temperature/precipitation and mosquito population size. A zero-inflated negative binomial model was used to test the relationship between the temperature and the infection rate. A single complex model for infection rate prediction was also used. The linkages were calculated for lag 0 and for 10 days earlier (lag 1), 20 days earlier (lag 2), and 30 days earlier (lag 3). Significant positive linkages (P < 0.001) were detected between temperature and mosquito population size for lag 1, lag 2, and lag 3. The linkages between temperature and infection rates were positive and significant for lag 2 and lag 3. Negative significant (P < 0.001) results were detected between precipitation and infection rates for lags 1, 2, and 3. The complex model showed that the best predictors for infection rate are the temperature, 20 days earlier (positive linkage) and the precipitation, 30 days earlier (negative linkage). Positive temperature anomalies in spring and summer and rainfall decrease contributed to the increase in the Culex spp. abundance and accelerated the WNV amplification in mosquito vector populations in the following weeks.
Keywords: Danube Delta; West Nile virus; climate change; infection rate; mosquitoes; weather factors.