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arXiv · 2511.17816

Inferring Transmission Dynamics of Respiratory Syncytial Virus from Houston Wastewater

Jose R. Palacio·Katherine B. Ensor·Sallie A. Keller·Rebecca Schneider·Kaavya Domakonda·Loren Hopkins·Lauren B. Stadler
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Abstract

Wastewater-based epidemiology (WBE) is an effective tool for tracking community circulation of respiratory viruses. We address estimating the effective reproduction number ($R_t$) and the relative number of infections from wastewater viral load. Using weekly Houston data on respiratory syncytial virus (RSV), we implement a parsimonious Bayesian renewal model that links latent infections to measured viral load through biologically motivated generation and shedding kernels. The framework yields estimates of $R_t$ and relative infections, enabling a coherent interpretation of transmission timing and phase. We compare two input strategies-(i) raw viral-load measurements with a log-scale standard deviation, and (ii) state-space-filtered load estimates with time-varying variances-and find no practically meaningful differences in inferred trajectories or peak timing. Given this equivalence, we report the filtered input as a pragmatic default because it embeds week-specific variances while leaving epidemiological conclusions unchanged.

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Jose R. Palacio, Katherine B. Ensor, Sallie A. Keller, Rebecca Schneider, Kaavya Domakonda, Loren Hopkins, Lauren B. Stadler. 2025-11-21. Inferring Transmission Dynamics of Respiratory Syncytial Virus from Houston Wastewater. https://arxiv.org/abs/2511.17816

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