发表机构
Rice University; California Polytechnic State University; Houston Health Department（莱斯大学; 加州州立理工大学; 休斯顿卫生局）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
该研究利用休斯顿15座污水处理厂的废水数据，通过新型距离构建空间权重矩阵扩展贝叶斯更新模型，揭示了跨污水处理厂的呼吸道合胞病毒传播，为病毒监测提供了更准确的方法。
AI 中文摘要
基于废水的流行病学（WBE）是一种有效且无创的工具，用于追踪社区层面呼吸道病毒的传播，然而标准更新模型会孤立处理每个污水处理厂（WWTP），尽管呼吸道合胞病毒（RSV）会通过跨越服务区域边界的接触网络传播。利用休斯顿15座WWTP的每周数据，我们通过一种新型人口扩展豪斯多夫距离构建的空间权重矩阵，将相邻WWTP耦合，扩展了单厂贝叶斯更新模型；该距离定义为WWTP之间的方向距离，衡量WWTP需延伸多远才能接触到相邻WWTP居民的有意义比例。单个参数ρ控制厂级增长率中的空间混合，使我们能够恢复有效再生数R_it。我们发现ρ的估计值远高于零，表明存在大量跨WWTP传播，这是独立厂模型无法捕捉的。与独立厂基准（ρ=0）相比，空间耦合改变了厂级R_it，同时基本未改变推断的感染轨迹。
英文摘要
Wastewater-based epidemiology (WBE) is an effective, noninvasive tool for tracking community-level circulation of respiratory viruses, yet standard renewal models treat each wastewater treatment plant (WWTP) in isolation, even though respiratory syncytial virus (RSV) spreads through contact networks that cross service-area boundaries. Using weekly data from $m = 15$ Houston WWTPs, we extend a single-plant Bayesian renewal model by coupling neighboring WWTPs via a spatial weight matrix built using a novel Population Extended Hausdorff Distance, defined as a directional distance between WWTPs. This distance measures how far a WWTP must reach to access a meaningful share of a neighboring WWTP's residents. A single parameter $ρ$ controls spatial mixing in the plant-level growth rate, allowing us to recover the effective reproduction number $R_{it}$. We find that $ρ$ is estimated well above zero, indicating substantial cross-WWTP transmission that the independent-plant model cannot capture. Spatial coupling reshapes plant-level $R_{it}$ relative to the independent-plant baseline ($ρ= 0$) while leaving inferred infection trajectories essentially unchanged.
Comments44 pages (including Appendix, pp. 42-44), 18 figures, 2 tables
