Cost-effectiveness of wastewater and environmental monitoring of respiratory syncytial virus to guide universal infant immunoprophylaxis in Canada
Notice bibliographique
Résumé
To compare the cost-effectiveness of wastewater and environmental monitoring (WEM) versus clinical surveillance (CS)-guided respiratory syncytial virus (RSV) prophylaxis programs in Canada. A cost-utility model was developed comprising two identical decision trees for RSV-WEM and RSV-CS. Within each tree, children could conservatively receive nirsevimab prophylaxis (71% coverage) or not at the start of the RSV season and subsequently experience an RSV-related hospitalization, medically-attended, non-hospitalized RSV-infection, or be uninfected/non-medically attended. All children could experience respiratory morbidity up to age 18 years, with higher rates following RSV-related hospitalization. All prophylaxis and RSV-related costs were identical for RSV-WEM and RSV-CS. No costs were assumed for RSV-CS; whereas a cost of CAD$12.31 per infant (infrastructure: CAD$4.07 plus sampling: CAD$8.24) was assumed if a new RSV-WEM system was initiated, with all infrastructure costs included in year 1. Predicated on data from the 2022–23 Ontario RSV season, RSV-WEM was assumed to provide a 15.1% benefit for earlier initiation of the prophylaxis program versus RSV-CS. Outcomes were modelled over an 18-year time horizon (1.5% discounting). RSV-WEM dominated (lower costs and higher utilities) RSV-CS and remained unaltered in all scenario analyses. Scenarios included: amortization of RSV-WEM infrastructure costs over 5 years; using existing WEM infrastructure for RSV detection; 25% reduction in extra cases identified by RSV-WEM; 50%–90% prophylaxis coverage based on real-world data; and 25% increase in the cost of RSV-WEM. The integration of RSV-WEM appears a highly cost-effective strategy (vs RSV-CS exclusively) to guide the earlier launch of RSV seasonal prophylaxis in Canada. What is already known about the topic? Respiratory syncytial virus (RSV) is an important cause of respiratory illness in children, and, in the worst cases, can require hospital care. To maximize the effectiveness of drugs designed to prevent RSV by temporarily boosting the child’s immune system (e.g. palivizumab and nirsevimab), their use needs to be matched to RSV activity in the community. Wastewater and environmental monitoring (WEM) is a technology that can detect the presence of viruses in sewage samples to show when specific diseases are increasing. What does the paper add to existing knowledge? A key question to answer for any investment in a new technology is whether the expected benefits justify the costs associated with setup and use. Cost-utility analysis sets the financial cost of a new technology against any savings it may produce plus the value of any improvements to people’s everyday life. This first assessment of the cost-utility of WEM compares it to clinical surveillance (CS), which is the current standard for assessing RSV activity. The results showed WEM to be a cost-saving approach over CS to guide a Canadian all-infant immunization program with nirsevimab. This means that the costs of implementing the WEM program can be offset by the savings from reducing the need for medical care. What insights does the paper provide for informing healthcare-related decision making? Our cost-utility analysis on the integration of RSV-WEM provides practical information for both provincial and local public health authorities to utilize and supports the implementation of such resources in Canada and other countries. Adoption of RSV-WEM has the potential to precisely guide the initiation of RSV immunization programs which will help reduce avoidable illness and hospitalization, creating cost savings and improving the lives of the protected children and their parents.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,003 | 0,008 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,002 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 source (Gemma direct ou Codex distillé), 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 ».