Variability in Normalization Methods of COVID-19 Wastewater Surveillance
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Terry, Ivy Bernadette
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Abstract
Wastewater surveillance for SARS-CoV-2 provides an approach for assessing theinfection burden across a sewer service area. For these data to be useful for public health,
measurement variability in relation to normalization methods need to be established. While the
relationships between wastewater SARS-CoV-2 concentrations and COVID-19 incidence are
now being reported widely in the literature, most studies are analyzed using a variety of different
data normalization techniques leading to inconsistency and limited applicability when comparing
data to other systems or studies.This work examines the variability and correlation of
SARS-CoV-2 wastewater concentration normalization methods to improve confidence in these
data for public health surveillance. In this study, we focused on better defining variability in the
wastewater measurements, Total Suspended Solids (TSS), Chemical Oxygen Demand (COD),
and the Pepper Mild Mottle Virus (PMMoV) to improve confidence in the interpretation of data
and to provide evidence to support different study analysis options. This study found that the
COD normalization method has the strongest correlation to our comparative normalization
method of flow and population. TSS as a method also looked promising as a normalization
method for wastewater surveillance with a moderate correlation. PMMoV had the lowest
correlation. These results can help facilitate future wastewater surveillance method
standardization by informing data analysis techniques utilized as well as illustrate variability
between methods in general.
Description
Thesis (Master's)--University of Washington, 2022
