| Title: |
Determining the timing of respiratory syncytial virus (RSV) epidemics:a systematic review, 2016 to 2021; method categorisation and identification of influencing factors |
| Authors: |
Staadegaard, Lisa; Dückers, Michel; van Summeren, Jojanneke; van Gameren, Rob; Demont, Clarisse; Bangert, Mathieu; Li, You; Casalegno, Jean-Sebastien; Caini, Saverio; Paget, John |
| Source: |
Staadegaard, L, Dückers, M, van Summeren, J, van Gameren, R, Demont, C, Bangert, M, Li, Y, Casalegno, J-S, Caini, S & Paget, J 2024, 'Determining the timing of respiratory syncytial virus (RSV) epidemics : a systematic review, 2016 to 2021; method categorisation and identification of influencing factors', Euro surveillance : bulletin Europeen sur les maladies transmissibles = European communicable disease bulletin, vol. 29, no. 5, 2300244. https://doi.org/10.2807/1560-7917.ES.2024.29.5.2300244 |
| Publication Year: |
2024 |
| Collection: |
University of Groningen research database |
| Description: |
Background: There is currently no standardised approach to estimate respiratory syncytial virus (RSV) epidemics' timing (or seasonality), a critical information for their effective prevention and control.AimWe aimed to provide an overview of methods to define RSV seasonality and identify factors supporting method choice or interpretation/comparison of seasonal estimates. Methods: We systematically searched PubMed and Embase (2016-2021) for studies using quantitative approaches to determine the start and end of RSV epidemics. Studies' features (data-collection purpose, location, regional/(sub)national scope), methods, and assessment characteristics (case definitions, sampled population's age, in/outpatient status, setting, diagnostics) were extracted. Methods were categorised by their need of a denominator (i.e. numbers of specimens tested) and their retrospective vs real-time application. Factors worth considering when choosing methods and assessing seasonal estimates were sought by analysing studies. Results: We included 32 articles presenting 49 seasonality estimates (18 thereof through the 10% positivity threshold method). Methods were classified into eight categories, two requiring a denominator (1 retrospective; 1 real-time) and six not (3 retrospective; 3 real-time). A wide range of assessment characteristics was observed. Several studies showed that seasonality estimates varied when methods differed, or data with dissimilar assessment characteristics were employed. Five factors (comprising study purpose, application time, assessment characteristics, healthcare system and policies, and context) were identified that could support method choice and result interpretation. Conclusion: Methods and assessment characteristics used to define RSV seasonality are heterogeneous. Our categorisation of methods and proposed framework of factors may assist in choosing RSV seasonality methods and interpretating results. |
| Document Type: |
article in journal/newspaper |
| File Description: |
application/pdf |
| Language: |
English |
| ISSN: |
1560-7917 |
| Relation: |
info:eu-repo/semantics/altIdentifier/pmid/38304952; info:eu-repo/semantics/altIdentifier/hdl/https://hdl.handle.net/11370/c16acb61-3865-434c-b37a-caa6d4d0fb9c; info:eu-repo/semantics/altIdentifier/pissn/1560-7917 |
| DOI: |
10.2807/1560-7917.ES.2024.29.5.2300244 |
| Availability: |
https://hdl.handle.net/11370/c16acb61-3865-434c-b37a-caa6d4d0fb9c; https://research.rug.nl/en/publications/c16acb61-3865-434c-b37a-caa6d4d0fb9c; https://doi.org/10.2807/1560-7917.ES.2024.29.5.2300244; https://pure.rug.nl/ws/files/901062765/eurosurv-29-5_5.pdf |
| Rights: |
info:eu-repo/semantics/openAccess ; http://creativecommons.org/licenses/by/4.0/ |
| Accession Number: |
edsbas.AD534AF8 |
| Database: |
BASE |