Improving wastewater-based epidemiology through strategic placement of samplers
Journal:
arXiv
Published Date:
Jun 17, 2025
Abstract
Wastewater-based epidemiology (WBE) is a fast emerging method for passively
monitoring diseases in a population. By measuring the concentrations of
pathogenic materials in wastewater, WBE negates demographic biases in clinical
testing and healthcare demand, and may act as a leading indicator of disease
incidence.
For a WBE system to be effective, it should detect the presence of a new
pathogen of concern early enough and with enough precision that it can still be
localised and contained. In this study, then, we show how multiple wastewater
sensors can be strategically placed across a wastewater system, to detect the
presence of disease faster than if sampling was done at the wastewater
treatment plant only. Our approach generalises to any tree-like network and
takes into account the structure of the network and how the population is
distributed over it.
We show how placing sensors further upstream from the treatment plant
improves detection sensitivity and can inform how an outbreak is evolving in
different geographical regions. However, this improvement diminishes once
individual-level shedding is modelled as highly dispersed. With overdispersed
shedding, we show using real COVID-19 cases in Scotland that broad trends in
disease incidence (i.e., whether the epidemic is in growth or decline) can
still be reasonably estimated from the wastewater signal once incidence exceeds
about 5 infections per day.
