The wave of the SARS-CoV-2 Omicron variant resulted in a rapid spike and decline as highlighted by municipal wastewater surveillance.
Environ Technol Innov
; 28: 102667, 2022 Nov.
Article
in English
| MEDLINE | ID: covidwho-1851091
ABSTRACT
This paper highlights the extraordinarily rapid spread of SARS-CoV-2 loads in wastewater that during the Omicron wave in December 2021-February 2022, compared with the profiles acquired in 2020-21 with 410 samples from two wastewater treatment plants (Trento+suburbs, 132,500 inhabitants). Monitoring of SARS-CoV-2 in wastewater focused on (i) 3 samplings/week and analysis, (ii) normalization to calculate genomic units (GU) inh-1 d-1; (iii) calculation of a 7-day moving average to smooth daily fluctuations; (iv) comparison with the 'current active cases'/100,000 inh progressively affected by the mass vaccination. The time profiles of SARS-CoV-2 in wastewater matched the waves of active cases. In February-April 2021, a viral load of 1.0Eï¼07 GU inh-1 d - 1 corresponded to 700 active cases/100,000 inh. In July-September 2021, although the low current active cases, sewage revealed an appreciable SARS-CoV-2 circulation (in this period 2.2Eï¼07 GU inh-1 d-1 corresponded to 90 active cases/100,000 inh). Omicron was not detected in wastewater until mid-December 2021. The Omicron spread caused a 5-6 fold increase of the viral load in two weeks, reaching the highest peak (2.0-2.2Eï¼08 GU inh-1 d-1 and 4500 active cases/100,000 inh) during the pandemic. In this period, wastewater surveillance anticipated epidemiological data by about 6 days. In winter 2021-22, despite the 4-7 times higher viral loads in wastewater, hospitalizations were 4 times lower than in winter 2020-21 due to the vaccination coverage >80%. The Omicron wave demonstrated that SARS-CoV-2 monitoring of wastewater anticipated epidemiological data, confirming its importance in long-term surveillance.
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Topics:
Vaccines
/
Variants
Language:
English
Journal:
Environ Technol Innov
Year:
2022
Document Type:
Article
Affiliation country:
J.eti.2022.102667
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