Wastewater-based surveillance for SARS-CoV-2 in Alberta

International Journal of Population Data Science(2024)

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摘要
Objective Alberta's largest research universities collaborated to expand COVID-19 wastewater monitoring throughout the province to regularly provide evidence of SARS-CoV-2 burden in municipalities representing 3.2 million people. Approach Sampling was conducted at 26 wastewater treatment plants and facilities across the province. The project quantified SARS-CoV-2 genomic material in wastewater to reveal population-level trends of COVID-19 cases. This inclusive and comprehensive strategy captures everyone who contributes to wastewater, including those not clinically diagnosed. Researchers collected wastewater samples in municipalities three times a week. Additional sentinel monitoring was undertaken in neighbourhoods, hospitals, long-term care facilities, worksites, shelters, and schools. Results were shared on the public COVID Data Tracker website (https://covid-tracker.chi-csm.ca/). Data was additionally linked with hospital outcomes, workforce absenteeism and outbreak information. Results Wastewater-based surveillance (WBS) for SARS-CoV-2 genomic RNA associates very strongly with clinically diagnosed cases and health resource utilization, providing a ≥6-day leading indicator. WBS can effectively be performed across a range of geographic scales (from cities to individual facilities), ensuring actionable data that is relevant to end-users. We have published how outbreaks across a range of high-risk facilities can be monitored and predicted with WBS and can also be used to model COVID-19-associated workforce absenteeism. Emails and website interactions suggested widespread citizen engagement using data for evidence-based decisions. Conclusion WBS is a valuable tool for identifying potential outbreaks and tailoring response measures at the policy level and by individual citizens. We've created customizable real-time data-sharing tools catering to both the public (enhanced data transparency) and government (actionable insights).
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