Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2019 Nov 1;19(1):45.
doi: 10.1186/s12898-019-0261-9.

Ecological niche modelling to estimate the distribution of Culicoides, potential vectors of bluetongue virus in Senegal

Mamadou Ciss  1 , Biram Biteye  2 , Assane Gueye Fall  3 , Moussa Fall  3 , Marie Cicille Ba Gahn  3   4 , Louise Leroux  5   6 , Andrea Apolloni  3   6   7
Affiliations

Ecological niche modelling to estimate the distribution of Culicoides, potential vectors of bluetongue virus in Senegal

Mamadou Ciss et al. BMC Ecol. .

Abstract

Background: Vector-borne diseases are among the leading causes of morbidity and mortality in humans and animals. In the Afrotropical region, some are transmitted by Culicoides, such as Akabane, bluetongue, epizootic haemorrhagic fever and African horse sickness viruses. Bluetongue virus infection has an enormous impact on ruminant production, due to its high morbidity and mortality rates.

Methods: A nationwide Culicoides trapping campaign was organized at the end of the 2012 rainy season in Senegal. A Maximum Entropy approach (MaxEnt), Boosted Regression Tree (BRT) method and Ecological Niche Factor Analysis (ENFA) were used to develop a predictive spatial model for the distribution of Culicoides, using bio-climatic variables, livestock densities and altitude.

Results: The altitude, maximum temperature of the warmest month, precipitation of the warmest quarter, mean temperature of the wettest quarter, temperature seasonality, precipitation of the wettest quarter and livestock density were among the most important factors to predict suitable habitats of Culicoides. Culicoides occurrences were, in most of the cases, positively correlated to precipitation variables and livestock densities; and negatively correlated to the altitude and temperature indices. The Niayes area and the Groundnut basin were the most suitable habitats predicted.

Conclusion: We present ecological niche models for different Culicoides species, namely C. imicola, C. oxystoma, C. enderleini and C. miombo, potential vectors of bluetongue virus, on a nationwide scale in Senegal. Through our modelling approach, we were able to determine the effect of bioclimatic variables on Culicoides habitats and were able to generate maps for the occurrence of Culicoides species. This information will be helpful in developing risk maps for disease outbreaks.

Keywords: Afrotropical region; Bluetongue; Boosted Regression Tree; Culicoides; Ecological Niche Factor Analysis; Ecological modelling; MaxEnt; Suitable habitats; Vector-borne diseases.

PubMed Disclaimer

Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
Ecological niche factor analysis (ENFA) of Culicoides distribution in Senegal. C. imicola (a), C. oxystoma (b), C. enderleini (c) and C. miombo (d). Variables leading to ecological niche are represented into the light grey polygon and the dark grey polygon shows environmental conditions where Culicoides were observed (representation of the realized niche), and the small white circle corresponds to the barycentre of its distribution
Fig. 2
Fig. 2
MaxEnt predicted suitable areas. C. imicola (a), C. oxystoma (b), C. enderleini (c) and C. miombo (d). Green areas indicate areas that are likely to have suitable habitats for this vector species, while lighter areas indicate areas that are less suitable for the vector
Fig. 3
Fig. 3
BRT predicted suitable areas. C. imicola (a), C. oxystoma (b), C. enderleini (c) and C. miombo (d). Green areas indicate areas that are likely to have suitable habitat for this vector species, while lighter areas indicate areas that are less suitable for the vector
Fig. 4
Fig. 4
Contribution (%) of each variable to the building of the Maxent models. C. imicola (a), C. oxystoma (b), C. enderleini (c) and C. miombo (d)
Fig. 5
Fig. 5
Contribution (%) of each variable to the building of the BRT models. C. imicola (a), C. oxystoma (b), C. enderleini (c) and C. miombo (d)
Fig. 6
Fig. 6
Map of Senegal, a West African country (a), with the location of study sites in 12 Senegalese regions (b). In yellow, the study area and in grey, the unsampled area
See this image and copyright information in PMC

References

    1. Akakpo A, Wombou Toukam C, Mankor A, Ly C: Economic impact of african horse sickness outbreak in senegal in 2007. Inter-african bureau for animal resources po Box, NAIROBI, KENYA 2011, 59(1):1–16.
    1. Diouf N, Etter E, Lo M, Lo M, Akakpo A. Outbreaks of African horse sickness in Senegal, and methods of control of the 2007 epidemic. Vet Rec. 2013;172(6):152. doi: 10.1136/vr.101083. - DOI - PubMed
    1. Lefèvre P-C, Calvez D. La fièvre catarrhale du mouton (bluetongue) en Afrique intertropicale: influence des facteurs écologiques sur la prévalence de l’infection. Revue d’élevage et de médecine vétérinaire des pays tropicaux. 1986;39(3–4):263–268. - PubMed
    1. Lefèvre P-C, Taylor WP. Situation épidémiologique de la fièvre catarrhale du mouton (blue tongue) au Sénégal. Revue d’Elevage et de Médecine vétérinaire des Pays tropicaux. 1983;36(3):241–245. - PubMed
    1. Bakhoum MT: Ecologie et taxonomie intégrative des moucherons piqueurs du genre# Culicoides# Latreille (Diptera: Ceratopogonidae) en région Afrotropicale. PhD, N° 2017AGPT0012, 166 p, AgroParisTech, Paris, France. AgroParisTech; 2017.

Publication types

LinkOut - more resources