Modelling the Abundances of Two Major Culicoides (Diptera: Ceratopogonidae) Species in the Niayes Area of Senegal [texte imprimé] / M Diarra, Auteur ; M. Fall, Auteur ; R. Lancelot, Auteur ; A. Diop, Auteur ; A G Fall, Auteur ; A Dicko, Auteur ; Mor Talla Seck, Auteur ; C Garros, Auteur ; X Alléne, Auteur ; I Rakotoarivony, Auteur ; M. T. Bakhoum, Auteur ; Jérémy Bouyer, Auteur ; H Guis, Auteur . - Dakar (PRH, Sénégal) : ISRA/LNERV, 2015. Langues : Anglais ( eng) Catégories : | SCIENCES, PRODUCTION ET PROTECTION ANIMALES
| Mots-clés : | Culicoides, Espèce, Territoire Sénégal, Maladie des Ruminants, Virus | Index. décimale : | L730-Maladie des animaux | Résumé : | In Senegal, considerable mortality in the equine population and hence major economic
losses were caused by the African horse sickness (AHS) epizootic in 2007. Culicoides oxystoma
and Culicoides imicola, known or suspected of being vectors of bluetongue and AHS
viruses are two predominant species in the vicinity of horses and are present all year-round
in Niayes area, Senegal. The aim of this study was to better understand the environmental
and climatic drivers of the dynamics of these two species. Culicoides collections were
obtained using OVI (Onderstepoort Veterinary Institute) light traps at each of the 5 sites for
three nights of consecutive collection per month over one year. Cross Correlation Map analysis
was performed to determine the time-lags for which environmental variables and abundance
data were the most correlated. C. oxystoma and C. imicola count data were highly
variable and overdispersed. Despite modelling large Culicoides counts (over 220,000 Culicoides
captured in 354 night-traps), using on-site climate measures, overdispersion persisted
in Poisson, negative binomial, Poisson regression mixed-effect with random effect at
the site of capture models. The only model able to take into account overdispersion was the
Poisson regression mixed-effect model with nested random effects at the site and date of
capture levels. According to this model, meteorological variables that contribute to explaining
the dynamics of C. oxystoma and C. imicola abundances were: mean temperature and
relative humidity of the capture day, mean humidity between 21 and 19 days prior a capture
event, density of ruminants, percentage cover of water bodies within a 2 km radius and
interaction between temperature and humidity for C. oxystoma; mean rainfall and NDVI of
the capture day and percentage cover of water bodies for C. imicola. Other variables such
as soil moisture, wind speed, degree days, land cover or landscape metrics could be tested
to improve the models. Further work should also assess whether other trapping methods
such as host-baited traps help reduce overdispersion. |
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