One Health issues, such as the spread of highly pathogenic avian influenza (HPAI), present significant challenges at the intersection of human, animal, and environmental health. Recent H5N1 outbreaks underscore the need for comprehensive modeling that capture the complex interactions between various entities in these interconnected ecosystems, encompassing livestock, wild birds, and human populations. To support such efforts, we present a synthetic spatiotemporal gridded dataset for the contiguous United States, referred to as a digital similar. The methodology for constructing this digital similar involves fusing diverse datasets using statistical and optimization techniques. The livestock component includes farm-level representations of multiple livestock types -- cattle, poultry, hogs, and sheep -- including further categorization into subtypes, such as milk and beef cows, chicken, turkeys, ducks, etc. It also includes location-level data for livestock-product processing centers. Weekly abundance data for key wild bird species involved in avian flu transmission are included along with temporal networks of movements. Gridded distributions of the human population, along with demographic and occupational features, capture the placement of agricultural workers and the general population. The digital similar is verified and validated in multiple ways.This dataset aims to provide a comprehensive basis for modeling complex phenomena at the wild-domestic-human interfaces.

翻译："同一健康"议题，如高致病性禽流感（HPAI）的传播，在人类、动物与环境健康的交叉领域提出了重大挑战。近期H5N1疫情暴发凸显了建立综合性模型的必要性，这类模型需能捕捉这些相互关联的生态系统中各类实体（涵盖家畜、野生鸟类与人群）间的复杂相互作用。为支持此类研究，我们提出了一个针对美国本土的合成时空网格化数据集，称为数字孪生体。构建该数字孪生体的方法涉及运用统计与优化技术融合多源数据集。家畜模块包含多种家畜类型（牛、禽类、猪、羊）的农场级表征，并进一步细分子类型（如奶牛与肉牛、鸡、火鸡、鸭等），同时包含畜产品加工中心的位置级数据。数据集整合了参与禽流感传播的关键野生鸟类的周度丰度数据及其时空移动网络。人口的空间网格化分布，连同人口统计与职业特征，捕捉了农业从业人员与普通人群的分布格局。该数字孪生体通过了多维度验证。本数据集旨在为模拟野生动物-家养动物-人类交界面的复杂现象提供综合性基础。