Modelling Mosquito Prevalence on a City-Scale in Gothenburg, Sweden. A Methodological Development Study

Abstract

Mosquitoes are one of the most prominent carriers (or vectors) of diseases worldwide, which has an impact on human societies, as up to 1 million people pass away each year from mosquitorelated diseases. Mosquitoes are known carriers of, e.g., malaria, dengue fever and West Nile virus. These pathogens or viruses are temperature dependent, and a warmer future climate is believed to increase their geographical spread. Future warming may also lead to invasive species of mosquitoes establishing in new areas. One of the most common species of mosquitoes in urban areas in Europe is the Culex pipiens. The Cx. pipiens is a known carrier of different viruses and pathogens, e.g., the West Nile virus, and thus, several campaigns to control the species have been organized in cities all over Europe. Detailed species distribution models of mosquitoes could improve such surveillance- and mitigation campaigns. By utilizing Multi-Criteria Analyses, the aim of this study was to model suitability of egglaying (or oviposition) sites and adult distribution of the Cx. pipiens in the city of Gothenburg. Species distribution models of mosquitoes have not been previously performed on a city-scale. The results indicate large intra-urban variations in suitability for both oviposition and adult distribution. The results from the oviposition-model indicate highest suitability in, e.g., cemeteries and residential gardens. Regarding adult distribution, highest suitability is found in densely vegetated areas. An exposure analysis was also performed, which indicates that human exposure to Cx. pipiens is generally low in Gothenburg. However, human exposure to Cx. pipiens in Gothenburg may increase as studies have found that a warming climate might lead to changed dynamics in mosquito-human interactions. The study concludes that modelling mosquito suitability on a city-scale is possible, but further research is needed to validate and develop the models.