Wastewater Surveillance of Influenza (A, B) and Respiratory Syncytial Virus (RSV) in Southern Ontario
Notice bibliographique
Résumé
Wastewater-based surveillance (WBS) of SARS-CoV-2 has been highly effective at tracking trends of COVID-19 infections across the globe. This success led to the question of the possible applicability of WBS in monitoring other respiratory viruses that are also posing a concern for healthcare systems. Traditional influenza and RSV surveillance consists of monitoring hospital admissions, clinical testing data and outpatient visits. Even when clinical surveillance and hospitalization admissions are used to monitor the spread of these infections, they are often underestimated, with a lag between detection and community spread. In this study, wastewater surveillance of influenza A, influenza B and respiratory syncytial virus (RSV) was investigated, by quantifying the viral RNA of these viruses in wastewater and comparing these trends to clinical metrices. \nThe solid–liquid partitioning behaviors of influenza A, influenza B, RSV and SARS-CoV-2 in wastewater were examined to understand the behavior of the viruses in wastewater. Analyzing whether each virus is present in the liquid or solid fraction of wastewater may affect the data interpretation and inform further method development. The viral RNA in the liquid and solid fractions were separated and enriched by undergoing different centrifugation settings, overnight polyethylene glycol (PEG) precipitation followed by centrifugation, or ultrafiltration using a Centricon Plus-70 device. The influenza A, influenza B and RSV viral RNA concentrations were found to almost exclusively partition in the solids fraction of wastewater, which increased with an increase in centrifugal settings, unlike SARS-CoV-2 that had a more even split in signal between the solids and liquid fractions. The effectiveness of normalization using the endogenous pepper mild mottled virus (PMMoV) was also examined, by comparing the normalized influenza signal with the raw signal. Normalization using the PMMoV biomarker did not increase or hinder the correlation with clinical testing data relative to the raw influenza signal in wastewater. \nWastewater samples were collected once weekly from two wastewater treatment plants in the Region of Waterloo, Canada, from September 15, 2022, to June 21, 2023. Wastewater was treated overnight with polyethylene glycol (PEG), centrifuged (12,000g 1.5 h), then extracted (pellet) with Qiagen RNeasy PowerMicrobiome Kits and quantified using real-time reverse transcription quantitative polymerase chain reaction (RT-qPCR). The RNA concentrations of influenza A, influenza B and RSV in wastewater strongly correlated with the cases reported by episode date and hospitalizations, in the cities of Kitchener and Waterloo (Spearman’s Rank correlation coefficient rho ranging from 0.41-0.85). Wastewater surveillance can be a very effective additional surveillance tool to support public health officials in monitoring the trends of respiratory viruses in communities. Further development of WBS for respiratory virus monitoring will help public health to better prepare for these and other emerging pathogens in the future.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».