The Effect of Climate on the Presence of Culicoides imicola in Italy

Abstract

A model was developed to classify the Italian territories in relation to their suitability to harbour populations of Culicoides imicola and, as a consequence, also able to sustain a bluetongue (BT) epidemic. Italy was subdivided into 3507 10 x 10 km cells. In 546 cells at least one collection was made. The cell was considered the unit for all subsequent analyses. Culicoides were collected using Onderstepoort-type blacklight traps. Some traps were operated weekly at chosen sites; the remainder were moved almost daily to new sites. Only the results obtained during the peak August-November period were used, to exclude bias caused by the seasonality of C. imicola. Climate data for the period 1999-2001 were obtained from 80 weather stations. Multiple logistic regression was performed using the presence or absence of C. imicola in a specific cell as the dependent variable. Annual means of daily values for minimum temperature and minimum relative humidity, and the mean altitude above sea level, were the independent variables. The probability of occurrence of C. imicola in each grid cell was used to create a prediction map for Italy. The model was able to correctly classify 77.5% of the 546 grid cells in which at least one collection had been made. Culicoides imicola was found frequently through much of Sardinia, in parts of southern Italy, and further north along the Tyrrhenian coast, but was absent from along most of the Adriatic coast, and the internal mainland, and from most of Sicily. Six detailed maps are provided. Also mapped are areas where the probability of the occurrence of C. imicola is lower than 5%. This identification of possible mountainous C. imicola-free areas in central Italy could facilitate safer animal trade and transhumance, even if BT infections in traded animals or moving stock, were to go undetected. Needless to say this depends upon no cool-adapted species of Culicoides being involved in the transmission of BT disease.

Biting of anthropophilic Culicoides fulvithorax (Diptera: Ceratopogonidae), a vector of Mansonella perstans in Nigeria

“…However, the monthly biting rate of C. fulvithorax was not correlated with temperature in this study. A previous study showed that temperature and relative humidity, vis-à-vis Culicoides occurrence, are independent variables (Conte et al, 2003).…”

“…Therefore, literature is replete with information on studies on these insects from different parts of the world (Noireau et al, 1990;Conte et al, 2003;Mercer et al, 2003). To the best of our knowledge, most of the previous Culicoides studies from Nigeria were associated with wild or domestic animals (Dipeolu, 1976a(Dipeolu, , 1976bDipeolu and Ogunrinade, 1977;Udonsi, 1988), and none assessed human biting rates.…”

Mosquitoes and Culicoides biting midges: vector range and the influence of climate change

“…Other investigators (67,68) have, however, remained circumspect about the mooted continuing northward range expansion of C. imicola, proposing instead that, in the past, it had simply been overlooked, due to its mosaical distribution and narrow seasonality (August to November), exacerbated by inferior surveillance tools and sporadic, short-term collecting efforts. Indeed, in Italy at least, C. imicola would appear to be in stasis as it has shown no expansion whatsoever in its range since the year 2000, when Italy implemented its large-scale vector surveillance programme, which has been maintained continuously ever since (69).…”

Climate, Landscape, and the Risk of Orbivirus Exposure in Cattle in Illinois and Western Indiana

“…24 Bluetongue viruses have received considerable attention in this regard, although most efforts have focused on Europe, Africa, and Australia. [25][26][27][28][29][30][31][32][33][34][35][36][37][38][39][40][41][42] In North America there have been efforts to study the relationship between BTV in cattle and environmental or climatic variables. Seroconversion to BTV in cattle, based on a microimmunodiffusion test, was modeled using several variables related to temperature, precipitation, and humidity in Alabama.…”