Spatial inference of Culex pipiens abundance and biting activity distribution in the Netherlands using citizen science

Abstract

Background. The expanding geographical spread of mosquito-borne diseases (MBDs) has intensified the need for effective mosquito surveillance. Additional surveillance, particularly of species such as Culex pipiens, is essential as this species is a key vector of West Nile and Usutu viruses. Citizen science offers an innovative approach to monitoring Cx. pipiens populations. Methods. Our study utilized data from the Mosquito Alert mobile app to model the spatial distribution and abundance of Cx. pipiens and mosquito bites during the summer of 2021 in the Netherlands. Using generalized linear mixed models, climatic and non-climatic factors were analyzed to create two distribution models of adult Cx. pipiens and mosquito bites as outcomes. Results. Population density, income, and agricultural areas (P ≤ 0.007) were identified as key determinants for both models. Blackbird population density, precipitation, and the interaction between artificial surfaces and temperature were also covariates for the Culex model, whereas sand and tree coverage were determinants for the bite model. The study controlled for biases in sampling effort to ensure robust predictions, revealing higher Cx. pipiens abundance in the central eastern areas of the country and widespread mosquito biting activity across the Netherlands. Conclusions. These findings underscore the importance of sociodemographic and environmental factors in mosquito distribution and biting dynamics, with citizen science emerging as a valuable tool for enhancing traditional surveillance. Future research integrating longer temporal datasets and human behavioral factors will further improve predictive accuracy and support more effective MBD prevention efforts.