Severe acute respiratory
syndrome coronavirus-2 (SARS-CoV-2) in
wastewater has been used to track community infections of coronavirus
disease-2019 (COVID-19), providing critical information for public
health interventions. Since levels in wastewater are dependent upon
human inputs, we hypothesize that tracking infections can be improved
by normalizing wastewater concentrations against indicators of human
waste [Pepper Mild Mottle Virus (PMMoV), β-2 Microglobulin (B2M),
and fecal coliform]. In this study, we analyzed SARS-CoV-2 and indicators
of human waste in wastewater from two sewersheds of different scales:
a University campus and a wastewater treatment plant. Wastewater data
were combined with complementary COVID-19 case tracking to evaluate
the efficiency of wastewater surveillance for forecasting new COVID-19
cases and, for the larger scale, hospitalizations. Results show that
the normalization of SARS-CoV-2 levels by PMMoV and B2M resulted in
improved correlations with COVID-19 cases for campus data using volcano
second generation (V2G)-qPCR chemistry (r
s = 0.69 without normalization, r
s = 0.73
with normalization). Mixed results were obtained for normalization
by PMMoV for samples collected at the community scale. Overall benefits
from normalizing with measures of human waste depend upon qPCR chemistry
and improves with smaller sewershed scale. We recommend further studies
that evaluate the efficacy of additional normalization targets.
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