Conte A, Ippoliti C, Calistri P, Pelini S, Savini L, Salini R, Goffredo M, Meiswinkel R
Istituto Zooprofilattico Sperimentale dell'Abruzzo e del Molise G. Caporale, Via Campo Boario, Teramo, Italy.
Vet Ital. 2004 Jul-Sep;40(3):311-5.
A geographic information system (GIS) based on grids was developed by the National Reference Center for Veterinary Epidemiology at the Istituto Zooprofilattico Sperimentale dell'Abruzzo e del Molise 'G. Caporale' (IZS) in Teramo to identify potential infectious sites for bluetongue (BT) disease in Italy. Geographical and climatic variables were used to build a spatial process model (SPM); the different layers were combined by sequential addition. The final grids (with a cell size of 0.0387 decimal degrees) were generated for each season of the year, and the suitability of each cell for the presence of C. imicola given a value ranking from 0 to 10. While this model more accurately predicts the presence of C. imicola in the Basilicata and Sicily regions, it still over-predicted its presence in the Puglia region. This could be due to the occurrence of calcareous soils which dominate the Puglia landscape. The present SPM is an additive model that assigns an equal weight to each variable. However, the results suggest the existence of hitherto unconsidered variables that significantly influence the prevalence of C. imicola. To reflect their importance, these variables should be assigned a higher weighting in future models. However, the decision in regard to precisely what this weighting should be depends on a very thorough knowledge of the ecology of C. imicola.
意大利泰拉莫的阿布鲁佐和莫利塞大区动物卫生实验研究所“G. 卡波拉尔”国家兽医流行病学参考中心开发了一种基于网格的地理信息系统（GIS），以识别意大利蓝舌病（BT）的潜在感染地点。利用地理和气候变量构建空间过程模型（SPM）；通过顺序叠加将不同图层进行组合。针对一年中的每个季节生成最终网格（像元大小为0.0387十进制度），并根据0到10的数值排名确定每个像元对伊氏库蠓存在的适宜性。虽然该模型更准确地预测了巴西利卡塔和西西里地区伊氏库蠓的存在，但在普利亚地区仍存在预测过度的情况。这可能是由于普利亚地区以钙质土壤为主。当前的SPM是一种对每个变量赋予同等权重的叠加模型。然而，结果表明存在迄今未考虑的对伊氏库蠓流行率有显著影响的变量。为反映其重要性，这些变量在未来模型中应被赋予更高权重。然而，关于确切权重应为多少的决定取决于对伊氏库蠓生态学的非常透彻的了解。
