U.S. Geological Survey, Pennsylvania Cooperative Fish & Wildlife Research Unit, The Pennsylvania State University, University Park, Pennsylvania, 16802, USA.
Wildlife Health Lab, Cornell University, 240 Farrier Road, Ithaca, NY, 14853, USA.
Spat Spatiotemporal Epidemiol. 2024 Jun;49:100650. doi: 10.1016/j.sste.2024.100650. Epub 2024 Apr 11.
Chronic wasting disease (CWD) is a transmissible spongiform encephalopathy that was first detected in captive cervids in Colorado, United States (US) in 1967, but has since spread into free-ranging white-tailed deer (Odocoileus virginianus) across the US and Canada as well as to Scandinavia and South Korea. In some areas, the disease is considered endemic in wild deer populations, and governmental wildlife agencies have employed epidemiological models to understand long-term environmental risk. However, continued rapid spread of CWD into new regions of the continent has underscored the need for extension of these models into broader tools applicable for wide use by wildlife agencies. Additionally, efforts to semi-automate models will facilitate access of technical scientific methods to broader users. We introduce software (Habitat Risk) designed to link a previously published epidemiological model with spatially referenced environmental and disease testing data to enable agency personnel to make up-to-date, localized, data-driven predictions regarding the odds of CWD detection in surrounding areas after an outbreak is discovered. Habitat Risk requires pre-processing publicly available environmental datasets and standardization of disease testing (surveillance) data, after which an autonomous computational workflow terminates in a user interface that displays an interactive map of disease risk. We demonstrated the use of the Habitat Risk software with surveillance data of white-tailed deer from Tennessee, USA.
慢性消瘦病(CWD)是一种传染性海绵状脑病,于 1967 年首次在美国科罗拉多州的圈养鹿群中发现,但此后已传播到美国和加拿大的自由放养白尾鹿(Odocoileus virginianus)以及斯堪的纳维亚和韩国。在某些地区,这种疾病被认为是野生鹿群中的地方病,政府野生动物机构已经使用流行病学模型来了解长期的环境风险。然而,CWD 继续迅速传播到该大陆的新地区,这突显了需要将这些模型扩展到更广泛的工具,以便野生动物机构广泛使用。此外,努力使模型半自动化将有助于更多用户使用技术科学方法。我们引入了软件(栖息地风险),旨在将以前发表的流行病学模型与空间参考环境和疾病检测数据联系起来,使机构人员能够根据发现疫情后周围地区检测到 CWD 的几率做出最新的、本地化的、数据驱动的预测。栖息地风险需要对公共环境数据集进行预处理,并对疾病检测(监测)数据进行标准化,然后自主计算工作流程在用户界面中结束,该界面显示疾病风险的交互式地图。我们用来自美国田纳西州的白尾鹿监测数据演示了栖息地风险软件的使用。