Ecological niche modeling of Aedes aegypti under climate change in Benin

Our study contributed to the protection of the health of the Beninese population against the vector-borne infectious disease dengue fever. Mosquito occurrence data were collected in the municipalities of Natitingou, Parakou, Abomey Calavi, and Cotonou, supplemented by data downloaded from the Global Biodiversity Information Facility (GBIF), as well as environmental variables from Africlim and distance variables. A spatial distribution and ecological niche model of Aedes aegypti was constructed using MaxEnt version 3.4.1k. In total, nearly 300 people randomly selected from the municipalities surveyed were assessed on their knowledge of dengue fever. An analysis of the results showed that only 18% of respondents knew about the disease and its causes. Analysis of the spatial distribution indicated that, at present, the central and the northernmost areas of Benin are unfavorable to the presence of the vector of dengue. Projections for the year 2055 under the Representative Concentration Pathway (RCP) 4.5 and RCP 8.5 scenarios indicated an increase in areas favorable to the vector. These results underscore the need to strengthen surveillance and targeted prevention strategies to reduce future dengue risk in Benin.

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Publication Details

Journal
Academia Biology
Published
2026-02-25
DOI
https://doi.org/10.20935/acadbiol8151
Primary Topic
Species Distribution and Climate Change
Type
article
Field-Weighted Citation Impact
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article

Ecological niche modeling of Aedes aegypti under climate change in Benin

Jean Cossi Ganglo, Rock Aïkpon, Gbessi Steven Kadiri Adjakidje
Academia Biology
Species Distribution and Climate Change
article

Ecological niche modeling of Aedes aegypti under climate change in Benin

Jean Cossi Ganglo, Rock Aïkpon, Gbessi Steven Kadiri Adjakidje
article en

Abstract

Our study contributed to the protection of the health of the Beninese population against the vector-borne infectious disease dengue fever. Mosquito occurrence data were collected in the municipalities of Natitingou, Parakou, Abomey Calavi, and Cotonou, supplemented by data downloaded from the Global Biodiversity Information Facility (GBIF), as well as environmental variables from Africlim and distance variables. A spatial distribution and ecological niche model of Aedes aegypti was constructed using MaxEnt version 3.4.1k. In total, nearly 300 people randomly selected from the municipalities surveyed were assessed on their knowledge of dengue fever. An analysis of the results showed that only 18% of respondents knew about the disease and its causes. Analysis of the spatial distribution indicated that, at present, the central and the northernmost areas of Benin are unfavorable to the presence of the vector of dengue. Projections for the year 2055 under the Representative Concentration Pathway (RCP) 4.5 and RCP 8.5 scenarios indicated an increase in areas favorable to the vector. These results underscore the need to strengthen surveillance and targeted prevention strategies to reduce future dengue risk in Benin.

Academia BiologyVol. 4(1)
Université d'Abomey-Calavi (BJ)
Climate action
Openalex Percentile: Top 46%
Species Distribution and Climate Change
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