Wastewater-Based Epidemiology for Viral Surveillance from an Endemic Perspective: Evidence and Challenges.
SARS-CoV-2
endemic environmental monitoring
enterovirus
human adenovirus
norovirus
wastewater surveillance
wastewater-based epidemiology
Journal
Viruses
ISSN: 1999-4915
Titre abrégé: Viruses
Pays: Switzerland
ID NLM: 101509722
Informations de publication
Date de publication:
20 Mar 2024
20 Mar 2024
Historique:
received:
05
02
2024
revised:
23
02
2024
accepted:
11
03
2024
medline:
28
3
2024
pubmed:
28
3
2024
entrez:
28
3
2024
Statut:
epublish
Résumé
Wastewater-based epidemiology (WBE) is currently used to monitor not only the spread of the viral SARS-CoV-2 pandemic but also that of other viruses in endemic conditions, particularly in the absence of syndromic surveillance. The continuous monitoring of sewage requires high expenditure and significant time investments, highlighting the need for standardized methods and structured monitoring strategies. In this context, we conducted weekly wastewater monitoring in northwestern Tuscany (Italy) and targeted human adenovirus (HAdV), norovirus genogroup II (NoVggII), enterovirus (EV), and SARS-CoV-2. Samples were collected at the entrances of treatment plants and concentrated using PEG/NaCl precipitation, and viral nucleic acids were extracted and detected through real-time reverse transcription qPCR. NoVggII was the most identified target (84.4%), followed by HAdV, SARS-CoV-2, and EV. Only HAdV and EV exhibited seasonal peaks in spring and summer. Compared with data that were previously collected in the same study area (from February 2021 to September 2021), the results for SARS-CoV-2 revealed a shift from an epidemic to an endemic pattern, at least in the region under investigation, which was likely due to viral mutations that led to the spreading of new variants with increased resistance to summer environmental conditions. In conclusion, using standardized methods and an efficient monitoring strategy, WBE proves valuable for viral surveillance in pandemic and epidemic scenarios, enabling the identification of temporal-local distribution patterns that are useful for making informed public health decisions.
Identifiants
pubmed: 38543847
pii: v16030482
doi: 10.3390/v16030482
pii:
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : Regione Toscana
ID : Monitoring and modeling of SARS-CoV-2 in sewer networks for COVID 19 pandemic spreading early warning system
Organisme : Italian Ministry of Health
ID : "CCM 2020 program" with the project "Wastewater based epidemiology: implementation of a surveillance system for the early detection of pathogens, and specifically SARS-CoV-2"
Organisme : EU Commission
ID : Grant Agreement 060701/2021/864481/SUB/ENV.C2
Organisme : Ministry of University and Research (MUR)
ID : FSE REACT-EU - PON 2014-2020 "Research and Innovation" resources - Green/Innovation Action - DM MUR 1062/2021