Cited by 117Malaria Research and ControlSpecies Distribution and Climate ChangeMosquito-borne diseases and control

GEOGRAPHIC AND ECOLOGIC DISTRIBUTIONS OF THE ANOPHELES GAMBIAE COMPLEX PREDICTED USING A GENETIC ALGORITHM

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LEVINE, REBECCA S., PETERSON, A. TOWNSEND, BENEDICT, MARK Q.·2004·The American Journal of Tropical Medicine and Hygiene

Abstract

The distribution of the Anopheles gambiae complex of malaria vectors in Africa is uncertain due to under-sampling of vast regions. We use ecologic niche modeling to predict the potential distribution of three members of the complex (A. gambiae, A. arabiensis, and A. quadriannulatus) and demonstrate the statistical significance of the models. Predictions correspond well to previous estimates, but provide detail regarding spatial discontinuities in the distribution of A. gambiae s.s. that are consistent with population genetic studies. Our predictions also identify large areas of Africa where the presence of A. arabiensis is predicted, but few specimens have been obtained, suggesting under-sampling of the species. Finally, we project models developed from African distribution data for the late 1900s into the past and to South America to determine retrospectively whether the deadly 1929 introduction of A. gambiae sensu lato into Brazil was more likely that of A. gambiae sensu stricto or A. arabiensis.

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Crossref · 10.4269/ajtmh.2004.70.105

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  • GARP models have predictive value for mosquitoes that is statistically significant by intrinsic and extrinsic tests.

    “GARP models have been shown to have predictive value for mosquitoes that is statistically significant by both stringent intrinsic tests performed on a subset of the data during development and by extrinsic tests of models using data not included in model development (Peterson 2001, Levine et al. 2004).”

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Authors
LEVINE, R. S., PETERSON, A. T., & BENEDICT, M. Q.
Affiliations
Centers for Disease Control and Prevention (US)
Venue
The American Journal of Tropical Medicine and Hygiene
Published
2004-02
Volume
70
Issue
2
Pages
105-109
ISSN
0002-9637 (ISSN-L)
OpenAlex
W2113237317
Cited by
117
References
21
Citations by year
2026: 1 · 2025: 1 · 2024: 1 · 2023: 1 · 2022: 1 · 2021: 2 · 2020: 5 · 2019: 5 · 2018: 5 · 2017: 3 · 2016: 3 · 2015: 8 · 2014: 8 · 2013: 6 · 2012: 9
FWCI
8.15
Type
journal article
Language
en
Open access
Licence
other-oa
Locations
  • American Journal of Tropical Medicine and Hygiene (publishedVersion)
  • PubMed (publishedVersion)
  • KU ScholarWorks (The University of Kansas) (submittedVersion, other-oa)
Topics
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Malaria Research and Control
  • Physical Sciences › Environmental Science › Ecological Modeling › Species Distribution and Climate Change
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Mosquito-borne diseases and control
Keywords
Anopheles gambiae s.l., Anopheles arabiensis, Anopheles quadriannulatus, malaria vectors, species distribution prediction, genetic algorithm, geographic distribution, undersampling, population structure, South America, Africa
MeSH terms
Africa, Algorithms, Animals, Anopheles, Insect Vectors, Models, Biological, South America, Ecosystem

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