Modeling Disease Transmission Dynamics with Population-Weighted Spatial Inference for Wastewater-Based Epidemiology
Abstract
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 Rit. 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 Rit relative to the independent-plant baseline (ρ= 0) while leaving inferred infection trajectories essentially unchanged.
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BibTeX
@misc{palacio2026modeling,
title = {{Modeling Disease Transmission Dynamics with Population-Weighted Spatial Inference for Wastewater-Based Epidemiology}},
author = {Jose R. Palacio and Katherine B. Ensor and Julia Schedler and Rebecca Schneider and Kaavya Domakonda and Loren Hopkins and Lauren B. Stadler and Sharmila Bhandari},
howpublished = {arXiv},
year = {2026},
month = oct,
doi = {10.48550/arxiv.2608.08823},
eprint = {2608.08823},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2608.08823},
}
RIS
TY - UNPB
TI - Modeling Disease Transmission Dynamics with Population-Weighted Spatial Inference for Wastewater-Based Epidemiology
AU - Jose R. Palacio
AU - Katherine B. Ensor
AU - Julia Schedler
AU - Rebecca Schneider
AU - Kaavya Domakonda
AU - Loren Hopkins
AU - Lauren B. Stadler
AU - Sharmila Bhandari
PY - 2026
DA - 2026/10/04
PB - arXiv
DO - 10.48550/arxiv.2608.08823
UR - https://arxiv.org/abs/2608.08823
AB - 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.
ER -