title: Geographical distributions of African malaria vector sibling species and evidence for insecticide resistance.
abstract: Many of the mosquito species responsible for malaria transmission belong to a sibling complex; a taxonomic group of morphologically identical, closely related species. Sibling species often differ in several important factors that have the potential to impact malaria control, including their geographical distribution, resistance to insecticides, biting and resting locations, and host preference. The aim of this study was to define the geographical distributions of dominant malaria vector sibling species in Africa so these distributions can be coupled with data on key factors such as insecticide resistance to aid more focussed, species-selective vector control.
  
  
  
  Within the Anopheles gambiae species complex and the Anopheles funestus subgroup, predicted geographical distributions for Anopheles coluzzii, An. gambiae (as now defined) and An. funestus (distinct from the subgroup) have been produced for the first time. Improved predicted geographical distributions for Anopheles arabiensis, Anopheles melas and Anopheles merus have been generated based on records that were confirmed using molecular identification methods and a model that addresses issues of sampling bias and past changes to the environment. The data available for insecticide resistance has been evaluated and differences between sibling species are apparent although further analysis is required to elucidate trends in resistance.
  
  
  
  Sibling species display important variability in their geographical distributions and the most important malaria vector sibling species in Africa have been mapped here for the first time. This will allow geographical occurrence data to be coupled with species-specific data on important factors for vector control including insecticide resistance. Species-specific data on insecticide resistance is available for the most important malaria vectors in Africa, namely An. arabiensis, An. coluzzii, An. gambiae and An. funestus. Future work to combine these data with the geographical distributions mapped here will allow more focussed and resource-efficient vector control and provide information to greatly improve and inform existing malaria transmission models.
authors.affiliation: Malaria Atlas Project, Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, OX3 7BN, UK.
authors.forename: Antoinette
authors.initials: A
authors.lastname: Wiebe
authors.affiliation: Malaria Atlas Project, Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, OX3 7BN, UK.
authors.forename: Joshua
authors.initials: J
authors.lastname: Longbottom
authors.affiliation: Department of Vector Biology, Liverpool School of Tropical Medicine, Pembroke Place, Liverpool, L3 5QA, UK.
authors.forename: Katherine
authors.initials: K
authors.lastname: Gleave
authors.affiliation: Malaria Atlas Project, Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, OX3 7BN, UK.
authors.forename: Freya M
authors.initials: FM
authors.lastname: Shearer
authors.affiliation: Oxford Long Term Ecology Laboratory, Department of Zoology, University of Oxford, Oxford, OX1 3PS, UK.
authors.forename: Marianne E
authors.initials: ME
authors.lastname: Sinka
authors.affiliation: Oxford Long Term Ecology Laboratory, Department of Zoology, University of Oxford, Oxford, OX1 3PS, UK.
authors.forename: N Claire
authors.initials: NC
authors.lastname: Massey
authors.affiliation: Malaria Atlas Project, Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, OX3 7BN, UK.
authors.forename: Ewan
authors.initials: E
authors.lastname: Cameron
authors.affiliation: Department of Infectious Disease Epidemiology, Imperial College, St Mary's Hospital, London, W2 1NY, UK.
authors.forename: Samir
authors.initials: S
authors.lastname: Bhatt
authors.affiliation: Malaria Atlas Project, Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, OX3 7BN, UK.
authors.forename: Peter W
authors.initials: PW
authors.lastname: Gething
authors.affiliation: Department of Vector Biology, Liverpool School of Tropical Medicine, Pembroke Place, Liverpool, L3 5QA, UK.
authors.forename: Janet
authors.initials: J
authors.lastname: Hemingway
authors.affiliation: Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, 98121, USA.
authors.forename: David L
authors.initials: DL
authors.lastname: Smith
authors.affiliation: Department of Vector Biology, Liverpool School of Tropical Medicine, Pembroke Place, Liverpool, L3 5QA, UK.
authors.forename: Michael
authors.initials: M
authors.lastname: Coleman
authors.affiliation: Malaria Atlas Project, Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, OX3 7BN, UK. catherinemoyes@gmail.com.
authors.forename: Catherine L
authors.initials: CL
authors.lastname: Moyes
mesh_terms: D000349:Africa; D000818:Animals; D000852:Anopheles / Q000145:classification / Q000187:drug effects* / Q000254:growth & development; D007305:Insecticide Resistance; D000072138:Mosquito Vectors / Q000145:classification / Q000187:drug effects* / Q000254:growth & development*; D058974:Phylogeography
keywords: Maps; Species distribution model; Susceptibility bioassays