Institut National de la Recherche Agronomique, UR346 d'Epidémiologie Animale, Paris, France.
PLoS One. 2012;7(8):e43360. doi: 10.1371/journal.pone.0043360. Epub 2012 Aug 15.
Understanding where and how fast an infectious disease will spread during an epidemic is critical for its control. However, the task is a challenging one as numerous factors may interact and drive the spread of a disease, specifically when vector-borne diseases are involved. We advocate the use of simultaneous autoregressive models to identify environmental features that significantly impact the velocity of disease spread. We illustrate this approach by exploring several environmental factors influencing the velocity of bluetongue (BT) spread in France during the 2007-2008 epizootic wave to determine which ones were the most important drivers. We used velocities of BT spread estimated in 4,495 municipalities and tested sixteen covariates defining five thematic groups of related variables: elevation, meteorological-related variables, landscape-related variables, host availability, and vaccination. We found that ecological factors associated with vector abundance and activity (elevation and meteorological-related variables), as well as with host availability, were important drivers of the spread of the disease. Specifically, the disease spread more slowly in areas with high elevation and when heavy rainfall associated with extreme temperature events occurred one or two months prior to the first clinical case. Moreover, the density of dairy cattle was correlated negatively with the velocity of BT spread. These findings add substantially to our understanding of BT spread in a temperate climate. Finally, the approach presented in this paper can be used with other infectious diseases, and provides a powerful tool to identify environmental features driving the velocity of disease spread.
了解传染病在流行期间的传播地点和速度对于控制疾病至关重要。然而，由于许多因素可能相互作用并推动疾病的传播，特别是当涉及到媒介传播的疾病时，这项任务极具挑战性。我们提倡使用同时自回归模型来识别对疾病传播速度有重大影响的环境特征。我们通过探索影响法国 2007-2008 年蓝舌病流行期间传播速度的几个环境因素，来说明这种方法，以确定哪些因素是最重要的驱动因素。我们使用了在 4495 个市/镇估计的蓝舌病传播速度，并测试了 16 个协变量，这些协变量定义了五个相关变量主题组：海拔、气象相关变量、景观相关变量、宿主可用性和疫苗接种。我们发现，与媒介丰度和活动相关的生态因素（海拔和气象相关变量）以及宿主可用性是疾病传播的重要驱动因素。具体来说，在海拔较高的地区以及在与极端温度事件相关的强降雨发生一到两个月之前出现首例临床病例时，疾病传播速度较慢。此外，奶牛的密度与蓝舌病的传播速度呈负相关。这些发现极大地增加了我们对温带气候中蓝舌病传播的理解。最后，本文提出的方法可以用于其他传染病，并提供了一个识别驱动疾病传播速度的环境特征的有力工具。
