CoWWAn: Model-based assessment of COVID-19 epidemic dynamics by wastewater analysis
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..
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Preprint| Erscheinungsjahr: |
2022 |
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| Erschienen: |
2022 |
| Enthalten in: |
bioRxiv.org - (2022) vom: 25. Mai Zur Gesamtaufnahme - year:2022 |
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| Sprache: |
Englisch |
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| Beteiligte Personen: |
Proverbio, Daniele [VerfasserIn] |
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| Links: |
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| doi: |
10.1101/2021.10.15.21265059 |
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| PPN (Katalog-ID): |
XBI032813198 |
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| 520 | |a 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. | ||
| 700 | 1 | |a Kemp, Françoise |e verfasserin |4 aut | |
| 700 | 1 | |a Magni, Stefano |e verfasserin |4 aut | |
| 700 | 1 | |a Ogorzaly, Leslie |e verfasserin |4 aut | |
| 700 | 1 | |a Cauchie, Henry-Michel |e verfasserin |4 aut | |
| 700 | 1 | |a Gonçalves, Jorge |e verfasserin |4 aut | |
| 700 | 1 | |a Skupin, Alexander |e verfasserin |4 aut | |
| 700 | 1 | |a Aalto, Atte |e verfasserin |4 aut | |
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