Escobar Luis E, Carver Scott, Romero-Alvarez Daniel, VandeWoude Sue, Crooks Kevin R, Lappin Michael R, Craft Meggan E
Department of Veterinary Population Medicine, University of Minnesota, Minneapolis, MN, United States.
Department of Fisheries, Wildlife and Conservation Biology, University of Minnesota, St. Paul, MN, United States.
Front Vet Sci. 2017 Oct 17;4:172. doi: 10.3389/fvets.2017.00172. eCollection 2017.
Traditional epidemiological studies of disease in animal populations often focus on directly transmitted pathogens. One reason pathogens with complex lifecycles are understudied could be due to challenges associated with detection in vectors and the environment. Ecological niche modeling (ENM) is a methodological approach that overcomes some of the detection challenges often seen with vector or environmentally dependent pathogens. We test this approach using a unique dataset of two pathogens in wild felids across North America: and spp. in bobcats () and puma (). We found three main patterns. First, showed a broader use of environmental conditions than did spp. Also, ecological niche models, and Normalized Difference Vegetation Index satellite imagery, were useful even when applied to wide-ranging hosts. Finally, ENM results from one region could be applied to other regions, thus transferring information across different landscapes. With this research, we detail the uncertainty of epidemiological risk models across novel environments, thereby advancing tools available for epidemiological decision-making. We propose that ENM could be a valuable tool for enabling understanding of transmission risk, contributing to more focused prevention and control options for infectious diseases.
传统的动物种群疾病流行病学研究通常聚焦于直接传播的病原体。对具有复杂生命周期的病原体研究不足的一个原因可能是与在媒介和环境中进行检测相关的挑战。生态位建模(ENM)是一种方法,它克服了一些在媒介传播或环境依赖性病原体中常见的检测挑战。我们使用北美野生猫科动物中两种病原体的独特数据集来测试这种方法:山猫()和美洲狮()体内的 和 属物种。我们发现了三种主要模式。首先, 比 属物种对环境条件的利用范围更广。此外,生态位模型和归一化植被指数卫星图像即使应用于分布广泛的宿主时也很有用。最后,一个地区的ENM结果可以应用于其他地区,从而在不同景观之间传递信息。通过这项研究,我们详细阐述了跨新环境的流行病学风险模型的不确定性,从而改进了用于流行病学决策的工具。我们认为ENM可能是一种有价值的工具,有助于理解传播风险,为传染病的预防和控制提供更有针对性的选择。