Ecological niche modelling to estimate the distribution of Culicoides, potential vectors of bluetongue virus in Senegal.
Afrotropical region
Bluetongue
Boosted Regression Tree
Culicoides
Ecological Niche Factor Analysis
Ecological modelling
MaxEnt
Suitable habitats
Vector-borne diseases
Journal
BMC ecology
ISSN: 1472-6785
Titre abrégé: BMC Ecol
Pays: England
ID NLM: 101088674
Informations de publication
Date de publication:
01 11 2019
01 11 2019
Historique:
received:
31
01
2019
accepted:
14
10
2019
entrez:
3
11
2019
pubmed:
5
11
2019
medline:
21
11
2019
Statut:
epublish
Résumé
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. 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. 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. 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.
Sections du résumé
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.
Identifiants
pubmed: 31676006
doi: 10.1186/s12898-019-0261-9
pii: 10.1186/s12898-019-0261-9
pmc: PMC6825335
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
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