Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Estimating Wastewater Dilution Using Chemical Markers and Incomplete Flow Measurements: Application to Normalisation of SARS-CoV-2 Measurements

Version 1 : Received: 19 February 2024 / Approved: 20 February 2024 / Online: 20 February 2024 (07:09:16 CET)
Version 2 : Received: 23 April 2024 / Approved: 24 April 2024 / Online: 24 April 2024 (11:44:50 CEST)

How to cite: Jones, O.D.; Baldwin, A.J.; Perry, W.B.; Wilde, H.; Durance, I.; Jones, D.L.; Weightman, A. Estimating Wastewater Dilution Using Chemical Markers and Incomplete Flow Measurements: Application to Normalisation of SARS-CoV-2 Measurements. Preprints 2024, 2024021109. https://doi.org/10.20944/preprints202402.1109.v1 Jones, O.D.; Baldwin, A.J.; Perry, W.B.; Wilde, H.; Durance, I.; Jones, D.L.; Weightman, A. Estimating Wastewater Dilution Using Chemical Markers and Incomplete Flow Measurements: Application to Normalisation of SARS-CoV-2 Measurements. Preprints 2024, 2024021109. https://doi.org/10.20944/preprints202402.1109.v1

Abstract

We construct a Bayesian estimator for the dilution of a wastewater sample, and use it to estimate the prevalence of SARS-CoV-2 in Wales using data from the Wales Environmental Wastewater Analysis and Surveillance for Health project (WEWASH). In Wales wastewater is diluted by rainwater so an estimate of the level of dilution is required if we are to normalise sample measurements of disease markers such as SARS-CoV-2 RNA. We consider the situation where flow measurements are available, but will regularly be unreliable because of the action of combined sewer outflows, which divert wastewater away from treatment plants when the flow is excessive. However we also have proxies for the flow from various chemical markers, whose level per unit of population is fixed. The new estimator has multiple advantages compared to existing procedures: credible intervals for the estimates; optimal weighting of the chemical markers; systematic handling of missing and censored values; and model based smoothing without lags.

Keywords

SARS-CoV-2; wastewater-based epidemiology; wastewater; dilution; flow normalisation; Bayesian

Subject

Environmental and Earth Sciences, Water Science and Technology

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