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CoWWAn: Model-based assessment of COVID-19 epidemic dynamics by wastewater analysis
Daniele Proverbio; Françoise Kemp; Stefano Magni; Leslie Ogorzaly; Henry-Michel Cauchie; Jorge Gonçalves; Alexander Skupin; Atte Aalto.
Affiliation
  • Daniele Proverbio; University of Luxembourg
  • Françoise Kemp; University of Luxembourg
  • Stefano Magni; University of Luxembourg
  • Leslie Ogorzaly; Luxembourg Institute of Science and Technology
  • Henry-Michel Cauchie; Luxembourg Institute of Scienceand Technology
  • Jorge Gonçalves; University of Luxembourg
  • Alexander Skupin; University of Luxembourg
  • Atte Aalto; University of Luxembourg
Preprint in English | medRxiv | ID: ppmedrxiv-21265059
ABSTRACT
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.
License
cc_by_nc_nd
Full text: Available Collection: Preprints Database: medRxiv Language: English Year: 2021 Document type: Preprint
Full text: Available Collection: Preprints Database: medRxiv Language: English Year: 2021 Document type: Preprint
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