Spatial distribution modelling of Culicoides (Diptera: Ceratopogonidae) biting midges, potential vectors of African horse sickness and bluetongue viruses in Senegal
Abstract Background In Senegal, the last epidemic of African horse sickness (AHS) occurred in 2007. The western part of the country (the Niayes area) concentrates modern farms with exotic horses of high value and was highly affected during the 2007 outbreak that has started in the area. Several stud...
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| Format: | Article |
| Language: | English |
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BMC
2018-06-01
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| Series: | Parasites & Vectors |
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| Online Access: | http://link.springer.com/article/10.1186/s13071-018-2920-7 |
| _version_ | 1818991299500441600 |
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| author | Maryam Diarra Moussa Fall Assane Gueye Fall Aliou Diop Renaud Lancelot Momar Talla Seck Ignace Rakotoarivony Xavier Allène Jérémy Bouyer Hélène Guis |
| author_facet | Maryam Diarra Moussa Fall Assane Gueye Fall Aliou Diop Renaud Lancelot Momar Talla Seck Ignace Rakotoarivony Xavier Allène Jérémy Bouyer Hélène Guis |
| author_sort | Maryam Diarra |
| collection | DOAJ |
| description | Abstract Background In Senegal, the last epidemic of African horse sickness (AHS) occurred in 2007. The western part of the country (the Niayes area) concentrates modern farms with exotic horses of high value and was highly affected during the 2007 outbreak that has started in the area. Several studies were initiated in the Niayes area in order to better characterize Culicoides diversity, ecology and the impact of environmental and climatic data on dynamics of proven and suspected vectors. The aims of this study are to better understand the spatial distribution and diversity of Culicoides in Senegal and to map their abundance throughout the country. Methods Culicoides data were obtained through a nationwide trapping campaign organized in 2012. Two successive collection nights were carried out in 96 sites in 12 (of 14) regions of Senegal at the end of the rainy season (between September and October) using OVI (Onderstepoort Veterinary Institute) light traps. Three different modeling approaches were compared: the first consists in a spatial interpolation by ordinary kriging of Culicoides abundance data. The two others consist in analyzing the relation between Culicoides abundance and environmental and climatic data to model abundance and investigate the environmental suitability; and were carried out by implementing generalized linear models and random forest models. Results A total of 1,373,929 specimens of the genus Culicoides belonging to at least 32 different species were collected in 96 sites during the survey. According to the RF (random forest) models which provided better estimates of abundances than Generalized Linear Models (GLM) models, environmental and climatic variables that influence species abundance were identified. Culicoides imicola, C. enderleini and C. miombo were mostly driven by average rainfall and minimum and maximum normalized difference vegetation index. Abundance of C. oxystoma was mostly determined by average rainfall and day temperature. Culicoides bolitinos had a particular trend; the environmental and climatic variables above had a lesser impact on its abundance. RF model prediction maps for the first four species showed high abundance in southern Senegal and in the groundnut basin area, whereas C. bolitinos was present in southern Senegal, but in much lower abundance. Conclusions Environmental and climatic variables of importance that influence the spatial distribution of species abundance were identified. It is now crucial to evaluate the vector competence of major species and then combine the vector densities with densities of horses to quantify the risk of transmission of AHS virus across the country. |
| first_indexed | 2024-12-20T20:08:04Z |
| format | Article |
| id | doaj.art-b81dd4aad8ca41109429b9d0d906ac1f |
| institution | Directory Open Access Journal |
| issn | 1756-3305 |
| language | English |
| last_indexed | 2024-12-20T20:08:04Z |
| publishDate | 2018-06-01 |
| publisher | BMC |
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| series | Parasites & Vectors |
| spelling | doaj.art-b81dd4aad8ca41109429b9d0d906ac1f2022-12-21T19:27:53ZengBMCParasites & Vectors1756-33052018-06-0111111510.1186/s13071-018-2920-7Spatial distribution modelling of Culicoides (Diptera: Ceratopogonidae) biting midges, potential vectors of African horse sickness and bluetongue viruses in SenegalMaryam Diarra0Moussa Fall1Assane Gueye Fall2Aliou Diop3Renaud Lancelot4Momar Talla Seck5Ignace Rakotoarivony6Xavier Allène7Jérémy Bouyer8Hélène Guis9InstitutSénégalais de Recherches Agricoles, Laboratoire National de l’Elevage et de Recherches VétérinairesInstitutSénégalais de Recherches Agricoles, Laboratoire National de l’Elevage et de Recherches VétérinairesInstitutSénégalais de Recherches Agricoles, Laboratoire National de l’Elevage et de Recherches VétérinairesUniversité Gaston Berger, Laboratoire d’Etudes et de Recherches en Statistiques et DéveloppementCIRAD, ASTREInstitutSénégalais de Recherches Agricoles, Laboratoire National de l’Elevage et de Recherches VétérinairesCIRAD, ASTRECIRAD, ASTREInstitutSénégalais de Recherches Agricoles, Laboratoire National de l’Elevage et de Recherches VétérinairesCIRAD, ASTREAbstract Background In Senegal, the last epidemic of African horse sickness (AHS) occurred in 2007. The western part of the country (the Niayes area) concentrates modern farms with exotic horses of high value and was highly affected during the 2007 outbreak that has started in the area. Several studies were initiated in the Niayes area in order to better characterize Culicoides diversity, ecology and the impact of environmental and climatic data on dynamics of proven and suspected vectors. The aims of this study are to better understand the spatial distribution and diversity of Culicoides in Senegal and to map their abundance throughout the country. Methods Culicoides data were obtained through a nationwide trapping campaign organized in 2012. Two successive collection nights were carried out in 96 sites in 12 (of 14) regions of Senegal at the end of the rainy season (between September and October) using OVI (Onderstepoort Veterinary Institute) light traps. Three different modeling approaches were compared: the first consists in a spatial interpolation by ordinary kriging of Culicoides abundance data. The two others consist in analyzing the relation between Culicoides abundance and environmental and climatic data to model abundance and investigate the environmental suitability; and were carried out by implementing generalized linear models and random forest models. Results A total of 1,373,929 specimens of the genus Culicoides belonging to at least 32 different species were collected in 96 sites during the survey. According to the RF (random forest) models which provided better estimates of abundances than Generalized Linear Models (GLM) models, environmental and climatic variables that influence species abundance were identified. Culicoides imicola, C. enderleini and C. miombo were mostly driven by average rainfall and minimum and maximum normalized difference vegetation index. Abundance of C. oxystoma was mostly determined by average rainfall and day temperature. Culicoides bolitinos had a particular trend; the environmental and climatic variables above had a lesser impact on its abundance. RF model prediction maps for the first four species showed high abundance in southern Senegal and in the groundnut basin area, whereas C. bolitinos was present in southern Senegal, but in much lower abundance. Conclusions Environmental and climatic variables of importance that influence the spatial distribution of species abundance were identified. It is now crucial to evaluate the vector competence of major species and then combine the vector densities with densities of horses to quantify the risk of transmission of AHS virus across the country.http://link.springer.com/article/10.1186/s13071-018-2920-7SenegalAfrican horse sicknessCulicoides vectorsEnvironmental and climatic dataRandom forest modelsGeneralized Linear Models |
| spellingShingle | Maryam Diarra Moussa Fall Assane Gueye Fall Aliou Diop Renaud Lancelot Momar Talla Seck Ignace Rakotoarivony Xavier Allène Jérémy Bouyer Hélène Guis Spatial distribution modelling of Culicoides (Diptera: Ceratopogonidae) biting midges, potential vectors of African horse sickness and bluetongue viruses in Senegal Parasites & Vectors Senegal African horse sickness Culicoides vectors Environmental and climatic data Random forest models Generalized Linear Models |
| title | Spatial distribution modelling of Culicoides (Diptera: Ceratopogonidae) biting midges, potential vectors of African horse sickness and bluetongue viruses in Senegal |
| title_full | Spatial distribution modelling of Culicoides (Diptera: Ceratopogonidae) biting midges, potential vectors of African horse sickness and bluetongue viruses in Senegal |
| title_fullStr | Spatial distribution modelling of Culicoides (Diptera: Ceratopogonidae) biting midges, potential vectors of African horse sickness and bluetongue viruses in Senegal |
| title_full_unstemmed | Spatial distribution modelling of Culicoides (Diptera: Ceratopogonidae) biting midges, potential vectors of African horse sickness and bluetongue viruses in Senegal |
| title_short | Spatial distribution modelling of Culicoides (Diptera: Ceratopogonidae) biting midges, potential vectors of African horse sickness and bluetongue viruses in Senegal |
| title_sort | spatial distribution modelling of culicoides diptera ceratopogonidae biting midges potential vectors of african horse sickness and bluetongue viruses in senegal |
| topic | Senegal African horse sickness Culicoides vectors Environmental and climatic data Random forest models Generalized Linear Models |
| url | http://link.springer.com/article/10.1186/s13071-018-2920-7 |
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