TY - JOUR
TI - Wastewater monitoring as a supplementary surveillance tool for capturing
SARS-COV-2 community spread. A case study in two Greek municipalities
AU - Koureas, Michalis
AU - Amoutzias, Grigoris D.
AU - Vontas, Alexandros and
AU - Kyritsi, Maria
AU - Pinaka, Ourania
AU - Papakonstantinou, Argyrios and
AU - Dadouli, Katerina
AU - Hatzinikou, Marina
AU - Koutsolioutsou, Anastasia
AU - and Mouchtouri, Varvara A.
AU - Speletas, Matthaios
AU - Tsiodras,
AU - Sotirios
AU - Hadjichristodoulou, Christos
JO - Marine Environmental Research
PY - 2021
VL - 200
TODO - null
SP - null
PB - ACADEMIC PRESS INC ELSEVIER SCIENCE
SN - 0141-1136
TODO - 10.1016/j.envres.2021.111749
TODO - Wastewater-based epidemiology (WBE); COVID-19; SARS-CoV-2; Machine
learning; RNA; RT-PCR
TODO - A pilot study was conducted from late October 2020 until mid-April 2021,
aiming to examine the association between SARS-CoV-2 RNA concentrations
in untreated wastewater and recorded COVID-19 cases in two Greek
municipalities. A population of Random Forest and Linear Regression
Machine Learning models was trained and evaluated incorporating the
concentrations of SARS-CoV-2 RNA in 111 wastewater samples collected
from the inlets of two Wastewater Treatment Plants, along with
physicochemical parameters of the wastewater influent. The model’s
predictions were adequately associated with the 7-day cumulative cases
with the correlation coefficients (after 5-fold cross validation)
ranging from 0.754 to 0.960 while the mean relative errors ranged from
30.42% to 59.46%. Our results provide indications that
wastewater-based predictions can be applied in diverse settings and in
prolonged time periods, although the accuracy of these predictions may
be mitigated. Wastewater-based epidemiology can support and strengthen
epidemiological surveillance.
ER -