Yiannakoulias Nikolaos W, Svenson Lawrence W
Public Health Surveillance, Alberta Health and Wellness, Edmonton, Alberta, Canada.
Ann N Y Acad Sci. 2007 Apr;1102:135-48. doi: 10.1196/annals.1408.010.
The appearance and spread of West Nile virus (WNv) in North America represent a recent example of how mosquito-borne diseases can develop in new settings. Understanding the epidemiological, biological, and geographical aspects of WNv is critical to developing a greater understanding of how newly emerging, migrating, or evolving vector-borne infectious disease can develop globally. To aid in the allocation of resources that mitigate future outbreaks and to better understand the geographic nature of WNv in the North American prairies, we employ spatial and nonspatial modeling methods to predict municipal-level risk of human WNv infection rates. We use data based on a combination of routinely collected electronic data sources. Our findings suggest general agreement between spatial and nonspatial approaches, and results are consistent with seroprevalence-based estimates. We suggest that spatial models based on administrative data can offer estimates of relative risk in human populations at less cost, and in a timelier manner than estimates based on serology specimens.
西尼罗河病毒（WNv）在北美的出现和传播代表了一个近期的例子，说明了蚊媒疾病如何在新环境中发展。了解WNv的流行病学、生物学和地理方面对于更深入理解新出现、迁移或演变的媒介传播传染病如何在全球发展至关重要。为了有助于分配资源以减轻未来的疫情爆发，并更好地了解北美大草原上WNv的地理特征，我们采用空间和非空间建模方法来预测市级层面人类WNv感染率的风险。我们使用基于常规收集的电子数据源组合的数据。我们的研究结果表明空间和非空间方法之间总体一致，结果与基于血清阳性率的估计一致。我们建议基于行政数据的空间模型能够以比基于血清学标本的估计更低的成本、更及时地提供人群相对风险的估计。
