Project title: Variability in Normalization Methods of COVID-19 Wastewater Surveillance
Completed in: 2022 | Faculty advisor: John Meschke
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.