Wastewater-Based Epidemiology for Spatiotemporal COVID-19 Outbreak Tracking: Disease Surveillance, Quality Assurance and Modelling in the South West UK

Innovations in early warning systems for disease outbreaks are essential as ever more emerging infectious diseases develop into global threats,1 as exemplified by the ongoing COVID-19 pandemic. Wastewater-based epidemiology (WBE) is a potential solution to this urgent need for near-real-time disease outbreak tracking and surveillance. WBE considers wastewater as a fingerprint of the community’s health: a pooled sample of proteins, nucleic acids and small molecules. As WBE requires only a single sample to be processed for a community, this method allows the assessment of community health in a cheap and non-invasive way.

Wastewater-based epidemiology represents a valuable tool for spatiotemporal disease outbreak monitoring, but there are many sources of uncertainty associated with this use. Due to innate methodological variabilities, quality assurance must be rigorously incorporated into method development.2 This study monitors community SARS-CoV-2 disease outbreaks in four well-defined wastewater catchment areas in the South West of the UK. The methodological uncertainty caused by a multitude of factors is also assessed, including: sample stability on storage, wastewater catchment area variability, impact of pasteurisation, impact of removal of solids, accurate population normalisation, and methodological and instrumental precision. Concentration, RNA extraction and reverse transcription quantitative polymerase chain reaction (RT-qPCR) methodologies were developed. Detailed method development work was carried out to establish robust quality assurance data for the precise assessment of methodological uncertainties, and spatiotemporal disease outbreak monitoring work was carried out.

The talk will focus on WBE-based spatiotemporal COVID-19 outbreak surveillance through SARS-CoV-2 RNA quantification in wastewater in four communities in the South West UK. Previously under-researched aspects of quality assurance, uncertainty and modelling will also be discussed, with a focus on the analytical techniques used to quantify methodological uncertainties.


1 E. H. Chan, T. F. Brewer, L. C. Madoff, M. P. Pollack, A. L. Sonricker, M. Keller, C. C. Freifeld, M. Blench, A. Mawudeku and J. S. Brownstein, Proc. Natl. Acad. Sci., 2010, 107, 21701–21706.
2 G. Medema, L. Heijnen, G. Elsinga, R. Italiaander and A. Brouwer, Environ. Sci. Technol. Lett., 2020, 7, 511–516.