biostudies-literatureSantos JMFundação para a Ciência e a TecnologiaFundação para a Ciência e Tecnologiae0010715https://www.ebi.ac.uk/biostudies/studies/S-EPMC9499243biostudies-literatureUnknown16(9)The Aedes aegypti mosquito is the main vector for several diseases of global importance, such as dengue and yellow fever. This species was first identified on Madeira Island in 2005, and between 2012 and 2013 was responsible for an outbreak of dengue that affected several thousand people. However, the potential distribution of the species on the island remains poorly investigated. Here we assess the suitability of current and future climatic conditions to the species on the island and complement this assessment with estimates of the suitability of land use and human settlement conditions. We used four modelling algorithms (boosted regression trees, generalized additive models, generalized linear models and random forest) and data on the distribution of the species worldwide and across the PLoS neglected tropical diseasesThe current and future distribution of the yellow fever mosquito (Aedes aegypti) on Madeira Island.PMC9499243CEECIND/02037/2017;UIDP/00295/2020PTDC/SAU-PUB/30089/2017SFRH/BD/139753/2018PTDC/GES -OUT/30210/2017UIDB/00295/2020GHTM-UID/Multi/04413/2013Capinha CRocha JSantos JMSousa CAfalseThe current and future distribution of the yellow fever mosquito (Aedes aegypti) on Madeira Island.The Aedes aegypti mosquito is the main vector for several diseases of global importance, such as dengue and yellow fever. This species was first identified on Madeira Island in 2005, and between 2012 and 2013 was responsible for an outbreak of dengue that affected several thousand people. However, the potential distribution of the species on the island remains poorly investigated. Here we assess the suitability of current and future climatic conditions to the species on the island and complement this assessment with estimates of the suitability of land use and human settlement conditions. We used four modelling algorithms (boosted regression trees, generalized additive models, generalized linear models and random forest) and data on the distribution of the species worldwide and across the 2022-01-01T00:00:00Z2022 Sep2025-04-04T12:26:01.619Z2025-04-04T12:26:01.619ZS-EPMC94992433609495110.1371/journal.pntd.0010715