The dominant Anopheles vectors of human malaria in Africa, Europe and the Middle East: occurrence data, distribution maps and bionomic précis
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BACKGROUND: This is the second in a series of three articles documenting the geographical distribution of 41 dominant vector species (DVS) of human malaria. The first paper addressed the DVS of the Americas and the third will consider those of the Asian Pacific Region. Here, the DVS of Africa, Europe and the Middle East are discussed. The continent of Africa experiences the bulk of the global malaria burden due in part to the presence of the An. gambiae complex. Anopheles gambiae is one of four DVS within the An. gambiae complex, the others being An. arabiensis and the coastal An. merus and An. melas. There are a further three, highly anthropophilic DVS in Africa, An. funestus, An. moucheti and An. nili. Conversely, across Europe and the Middle East, malaria transmission is low and frequently absent, despite the presence of six DVS. To help control malaria in Africa and the Middle East, or to identify the risk of its re-emergence in Europe, the contemporary distribution and bionomics of the relevant DVS are needed. RESULTS: A contemporary database of occurrence data, compiled from the formal literature and other relevant resources, resulted in the collation of information for seven DVS from 44 countries in Africa containing 4234 geo-referenced, independent sites. In Europe and the Middle East, six DVS were identified from 2784 geo-referenced sites across 49 countries. These occurrence data were combined with expert opinion ranges and a suite of environmental and climatic variables of relevance to anopheline ecology to produce predictive distribution maps using the Boosted Regression Tree (BRT) method. CONCLUSIONS: The predicted geographic extent for the following DVS (or species/suspected species complex*) is provided for Africa: Anopheles (Cellia) arabiensis, An. (Cel.) funestus*, An. (Cel.) gambiae, An. (Cel.) melas, An. (Cel.) merus, An. (Cel.) moucheti and An. (Cel.) nili*, and in the European and Middle Eastern Region: An. (Anopheles) atroparvus, An. (Ano.) labranchiae, An. (Ano.) messeae, An. (Ano.) sacharovi, An. (Cel.) sergentii and An. (Cel.) superpictus*. These maps are presented alongside a bionomics summary for each species relevant to its control.
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An. arabiensis typically inhabit arid savannah landscapes and are often absent in field collections of adult or larval mosquitoes in the humid rainforest zone of southern Nigeria.
“An. arabiensis typically inhabit arid savannah landscapes and are often absent in field collections of adult or larval mosquitoes in the humid rainforest zone of southern Nigeria [48].”
From Sibling species of the major malaria vector Anopheles gambiae display divergent preferences for aquatic breeding sites in southern Nigeria (2024) · cites this paper as [48]
The Results section (Bionomics of the African DVS; page unavailable) describes An. arabiensis as a species of dry savannah and sparse woodland, supporting the habitat claim. It does not report that adult or larval field collections often fail to find it in the humid rainforest zone of southern Nigeria. The Discussion instead describes rare encounters in a humid region of eastern Madagascar. (LLM, conf=0.86)
Experimental — accuracy not yet measuredContrary to their choice of clean water bodies, An. arabiensis larvae occurred in polluted water in drainages in Agbor-Obi.
“Contrary to their choice of clean water bodies (see review by [48, 57], An. arabiensis larvae occurred in polluted water in drainages in Agbor-Obi.”
From Sibling species of the major malaria vector Anopheles gambiae display divergent preferences for aquatic breeding sites in southern Nigeria (2024) · cites this paper as [48]
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- Authors
- Sinka, M. E., Bangs, M. J., Manguin, S., Coetzee, M., Mbogo, C. M., Hemingway, J., Patil, A. P., Temperley, W. H., Gething, P. W., Kabaria, C. W., Okara, R. M., Van Boeckel, T., Godfray, H. C. J., Harbach, R. E., & Hay, S. I.
- Affiliations
- University of Oxford (GB)
- Université de Montpellier (FR)
- National Health Laboratory Service (ZA)
- Kenya Medical Research Institute (KE)
- Liverpool School of Tropical Medicine (GB)
- Kenyatta National Hospital (KE)
- Natural History Museum (GB)
- Corresponding author
- Sinka, Marianne E
- Hay, Simon I
- ORCID
- Venue
- Parasites & Vectors
- Published
- 2010-12
- Volume
- 3
- Issue
- 1
- Pages
- 117-117
- ISSN
- 1756-3305 (ISSN-L)
- PMC
- PMC3016360
- OpenAlex
- W2166231658
- Cited by
- 761
- References
- 350
- Citations by year
- 2026: 39 · 2025: 59 · 2024: 62 · 2023: 67 · 2022: 63 · 2021: 69 · 2020: 57 · 2019: 41 · 2018: 51 · 2017: 34 · 2016: 39 · 2015: 47 · 2014: 45 · 2013: 46 · 2012: 27
- FWCI
- 27.68
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Parasites & Vectors (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Dépôt institutionnel de l'Université libre de Bruxelles (Université Libre de Bruxelles) (submittedVersion, other-oa)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion)
- Greater South Information System
- Funders
- Wellcome Trust (083534, 079080, 079091)
- Topics
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Malaria Research and Control
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Mosquito-borne diseases and control
- Physical Sciences › Environmental Science › Ecological Modeling › Species Distribution and Climate Change
- Keywords
- malaria vectors, Anopheles, geographic distribution, Anopheles gambiae s.l., Anopheles funestus, Anopheles arabiensis, Anopheles melas, Anopheles merus, Anopheles moucheti, Anopheles nili, Anopheles atroparvus, Anopheles labranchiae, Anopheles messeae, Anopheles sacharovi, Anopheles sergentii, Anopheles superpictus, bionomics
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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