SARS-CoV-2 wastewater surveillance data can predict hospitalizations and ICU admissions

We measured SARS-CoV-2 RNA load in raw wastewater in Attica, Greece, by RT-qPCR for the environmental surveillance of COVID-19 for 6 months. The lag between RNA load and pandemic indicators (COVID-19 hospital and intensive care unit (ICU) admissions) was calculated using a grid search. Our results showed that RNA load in raw wastewater is a leading indicator of positive COVID-19 cases, new hospitalization and admission into ICUs by 5, 8 and 9 days, respectively. Modelling techniques based on distributed/fixed lag modelling, linear regression and artifi-cial neural networks were utilized to build relationships between SARS-CoV-2 RNA load in wastewater and pandemic health indicators. SARS-CoV-2 mutation analysis in wastewater during the third pandemic wave revealed that the alpha-variant was dominant. Our results demonstrate that clinical and environmental surveillance data can be combined to create robust models to study the on-going COVID-19 infection dynamics and provide an early warning for increased hospital admissions. (c) 2021 Elsevier B.V. All rights reserved.

Automated summary

This study in Greece measured the SARS-CoV-2 RNA load in raw wastewater as an early indicator of COVID-19 cases, hospitalizations, and ICU admissions, showing predictive leads of 5 to 9 days. Modeling techniques were used to establish relationships between RNA load in wastewater and pandemic health indicators, demonstrating the potential of combining clinical and environmental surveillance data to study and predict COVID-19 dynamics.