Projects per year
Abstract
Researchers around the world have demonstrated correlations between measurements of SARS-CoV-2 RNA in wastewater (WW) and case rates of COVID-19 derived from direct testing of individuals. This has raised concerns that wastewater-based epidemiology (WBE) methods might be used to quantify the spread of this and other diseases, perhaps faster than direct testing, and with less expense and intrusion. We illustrate, using data from Scotland and the USA, the issues regarding the construction of effective predictive models for disease case rates. We discuss the effects of variation in, and the problem of aligning, public health (PH) reporting and WW measurements. We investigate time-varying effects in PH-reported case rates and their relationship to WW measurements. We show the lack of proportionality of WW measurements to case rates with associated spatial heterogeneity. We illustrate how the precision of predictions is affected by the level of aggregation chosen. We determine whether PH or WW measurements are the leading indicators of disease and how they may be used in conjunction to produce predictive models. The prospects of using WW-based predictive models with or without ongoing PH data are discussed.
Original language | English |
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Article number | jwh2022020 |
Pages (from-to) | 1038-1050 |
Number of pages | 13 |
Journal | Journal of Water and Health |
Volume | 20 |
Issue number | 7 |
DOIs | |
Publication status | Published - 1 Jul 2022 |
Funding
We are grateful to the Scottish government and Biobot for making the data available. Funding from the UKRI (EP/V028499/1) is greatly appreciated.
ASJC Scopus subject areas
- Water Science and Technology
- Waste Management and Disposal
- Public Health, Environmental and Occupational Health
- Microbiology (medical)
- Infectious Diseases
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Dive into the research topics of 'Challenges in realising the potential of wastewater-based epidemiology to quantitatively monitor and predict the spread of disease'. Together they form a unique fingerprint.Projects
- 1 Finished
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UKRI GCRF/Newton Fund : Building an Early Warning System for community-wide infectious disease spread: SARS-CoV-2 tracking in Africa via environment fingerprinting- COVID-19
Kasprzyk-Hordern, B. (PI), Faraway, J. (CoI), Feil, E. (CoI), Smith, T. (CoI), Ehrhardt, B. (Researcher) & Gibbon, M. (Researcher)
Engineering and Physical Sciences Research Council
14/08/20 → 31/03/22
Project: Research council