{
  "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 $R_{it}$. 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.",
  "abstract_shown": true,
  "affiliations": [],
  "article_type": null,
  "arxiv": "2608.08823",
  "author_total": 8,
  "authors": [
    {
      "name": "Jose R. Palacio"
    },
    {
      "name": "Katherine B. Ensor"
    },
    {
      "name": "Julia Schedler"
    },
    {
      "name": "Rebecca Schneider"
    },
    {
      "name": "Kaavya Domakonda"
    },
    {
      "name": "Loren Hopkins"
    },
    {
      "name": "Lauren B. Stadler"
    },
    {
      "name": "Sharmila Bhandari"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/77m4x95twqkft.bib",
  "cited_by": 0,
  "doi": "10.48550/arxiv.2608.08823",
  "fulltext_url": null,
  "id": "77m4x95twqkft",
  "issns": [],
  "landing_url": "https://arxiv.org/abs/2608.08823",
  "language": null,
  "licence": "LicenseRef-arXiv-nonexclusive-1.0",
  "licence_label": "arXiv licence",
  "licence_source": "article",
  "licence_url": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
  "metadata_licence": "CC0-1.0",
  "native_subjects": [
    [
      "arxiv",
      "stat.AP"
    ],
    [
      "openalex",
      "2713|Respiratory viral infections research"
    ]
  ],
  "openalex": "W7202216544",
  "pdf_url": "https://arxiv.org/pdf/2608.08823",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-04",
  "publisher": null,
  "ris": "https://research.draconitic.com/paper/77m4x95twqkft.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T12:27:16Z",
      "native_id": "2608.08823",
      "source": "arxiv",
      "url": "https://arxiv.org/abs/2608.08823"
    }
  ],
  "subjects": [
    {
      "field": "mathematics",
      "origin": "arxiv:stat.AP",
      "subfield": "statistics"
    }
  ],
  "title": "Modeling Disease Transmission Dynamics with Population-Weighted Spatial Inference for Wastewater-Based Epidemiology",
  "title_text": "Modeling Disease Transmission Dynamics with Population-Weighted Spatial Inference for Wastewater-Based Epidemiology",
  "type": "preprint",
  "updated_at": "2026-10-30T12:27:16Z",
  "url": "https://research.draconitic.com/paper/77m4x95twqkft",
  "venue": "arXiv",
  "versions": []
}