COWWID-19 | Surveillance of SARS-CoV-2 in Wastewater - an Early Warning System to Track the Spatio-temporal Development of COVID-19

Imagine we could i) screen effectively thousands of people for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) simultaneously, ii) detect the outbreak before people with symptoms present at hospitals, and iii) track the spatio-temporal dynamics in real-time. The quantification of the SARS-CoV-2 load in wastewater enables such an opportunity: a single routine wastewater sample encompasses viruses shed in an entire wastewater treatment plant's (WWTP) catchment, and includes viruses excreted by infected individuals well before they are clinically diagnosed. Recognizing the unique potential of wastewater-based epidemiology (WBE) to serve as an early warning tool, we rapid-ly assembled an interdisciplinary team and started daily wastewater sample collection on 28 February in the affected areas Ticino, Vaud and Zurich (12 WWTPs covering a population of 737'000 people). Based on our team's experience in environmental virology, we anticipate detecting a SARS-CoV-2 signal in raw wastewater from as few as 10 infected indi-viduals. Our ultimate objective is to establish a WBE tool to track the current and future disease outbreaks in close to real-time. A WBE early warning system would allow public health institutions and decision makers to gain valuable time to assess the 'true' extent of an outbreak and react to its dynamics. This will facilitate adapting and enforcing mitigation measures, and ultimately save lives. Our specific goals (G) are:G1: Detect - Early detection and continued monitoring of outbreak. The reliable and rapid detection of SARS-CoV-2 in wastewater is instrumental to implementing a WBE approach to detect an outbreak early. We will optimize and apply a method to concentrate wastewater samples and quantify the concentration of SARS-CoV-2 with a turnaround time of 10 hours from sampling to result. With accompanying chemical analyses we will provide a second, indirect tool to esti-mate the outbreak dynamics, by measuring the medical intervention of the population. Selected wastewater samples will be screened for medication like antiretroviral drugs that may be used and co-occur with the COVID-19 diagnosis. G2: Model - Estimate outbreak curve and effect of mitigation measures. SARS-CoV-2 loading in raw wastewater pro-vides a quantitative indicator of the number of people actively shedding the virus in feces. Time series data on loading will be used to track the outbreak curve, preceding clinical case confirmation data by up to two weeks. Through analysis of the trajectory of loading rates, we will inform the true COVID-19 epidemic curve, including magnitude of the out-break, timing of outbreak stabilization, and - crucially - real-time feedback on intervention effectiveness.G3: Implement - Suggest design for future early warning system. Routine samples from selected WWTPs should be available for collection and analyses at any time. Aiming for a substantial population size and a good geographical distri-bution of WWTPs, a future emergency wastewater surveillance network in Switzerland could consist of 19 WWTPs covering 2.5 million people (30% of the population). The number and strategic selection of WWTPs can be extended depending on testing capacity. Our approach is not limited to COVID-19 and can readily be adapted to include notifiable seasonal viruses (e.g., influen-za) or future pandemic viruses. The relevance of this work thus goes beyond the current COVID-19 crisis.