Respiratory Syncytial Virus-Associated Hospital Admissions in Children Younger Than 5 Years in 7 European Countries Using Routinely Collected Datasets - UTU Tutkimustietojärjestelmä

A1 Vertaisarvioitu alkuperäisartikkeli tieteellisessä lehdessä

Respiratory Syncytial Virus-Associated Hospital Admissions in Children Younger Than 5 Years in 7 European Countries Using Routinely Collected Datasets

Tekijät: Reeves R.M., van Wijhe M., Tong S., Lehtonen T., Stona L., Teirlinck A.C., Fernandez L.V., Li Y., Giaquinto C., Fischer T.K., Demont C., Heikkinen T., Speltra I., van Boven M., Bøås H., Campbell H.; RESCEU Investigators

Kustantaja: Oxford University Press

Julkaisuvuosi: 2020

Journal: Journal of Infectious Diseases

Tietokannassa oleva lehden nimi: The Journal of infectious diseases

Vuosikerta: 222

Numero: supplement 7

Aloitussivu: S599

Lopetussivu: S605

eISSN: 1537-6613

DOI: https://doi.org/10.1093/infdis/jiaa360

Verkko-osoite: https://doi.org/10.1093/infdis/jiaa360

Tiivistelmä

Background

Respiratory syncytial virus (RSV) is a leading cause of respiratory tract infection (RTI) in young children. Registries provide opportunities to explore RSV epidemiology and burden.

Methods

We explored routinely collected hospital data on RSV in children aged < 5 years in 7 European countries. We compare RSV-associated admission rates, age, seasonality, and time trends between countries.

Results

We found similar age distributions of RSV-associated hospital admissions in each country, with the highest burden in children < 1 years old and peak at age 1 month. Average annual rates of RTI admission were 41.3–112.0 per 1000 children aged < 1 year and 8.6–22.3 per 1000 children aged < 1 year. In children aged < 5 years, 57%–72% of RTI admissions with specified causal pathogen were coded as RSV, with 62%–87% of pathogen-coded admissions in children < 1 year coded as RSV.

Conclusions

Our results demonstrate the benefits and limitations of using linked routinely collected data to explore epidemiology and burden of RSV. Our future work will use these data to generate estimates of RSV burden using time-series modelling methodology, to inform policymaking and regulatory decisions regarding RSV immunization strategy and monitor the impact of future vaccines.