Author: Proverbio, D.; Kemp, F.; Magni, S.; Ogorzaly, L.; Cauchie, H.-M.; Goncalves, J.; Skupin, A.; Aalto, A.
Title: CoWWAn: Model-based assessment of COVID-19 epidemic dynamics by wastewater analysis Cord-id: 3pz10nrz Document date: 2021_10_18
ID: 3pz10nrz
Snippet: We present COVID-19 Wastewater Analyser (CoWWAn) to reconstruct the epidemic dynamics from SARS-CoV-2 viral load in wastewater. As demonstrated for various regions and sampling protocols, this mechanistic model-based approach quantifies the case numbers, provides epidemic indicators and accurately infers future epidemic trends. In situations of reduced testing capacity, analysing wastewater data with CoWWAn is a robust and cost-effective alternative for real-time surveillance of local COVID-19 d
Document: We present COVID-19 Wastewater Analyser (CoWWAn) to reconstruct the epidemic dynamics from SARS-CoV-2 viral load in wastewater. As demonstrated for various regions and sampling protocols, this mechanistic model-based approach quantifies the case numbers, provides epidemic indicators and accurately infers future epidemic trends. In situations of reduced testing capacity, analysing wastewater data with CoWWAn is a robust and cost-effective alternative for real-time surveillance of local COVID-19 dynamics.
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