Cargando…
Use of the moving epidemic method (MEM) to assess national surveillance data for respiratory syncytial virus (RSV) in the Netherlands, 2005 to 2017
BACKGROUND: To control respiratory syncytial virus (RSV), which causes acute respiratory infections, data and methods to assess its epidemiology are important. AIM: We sought to describe RSV seasonality, affected age groups and RSV-type distribution over 12 consecutive seasons in the Netherlands, as...
Autores principales: | , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
European Centre for Disease Prevention and Control (ECDC)
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6530251/ https://www.ncbi.nlm.nih.gov/pubmed/31115311 http://dx.doi.org/10.2807/1560-7917.ES.2019.24.20.1800469 |
Sumario: | BACKGROUND: To control respiratory syncytial virus (RSV), which causes acute respiratory infections, data and methods to assess its epidemiology are important. AIM: We sought to describe RSV seasonality, affected age groups and RSV-type distribution over 12 consecutive seasons in the Netherlands, as well as to validate the moving epidemic method (MEM) for monitoring RSV epidemics. METHODS: We used 2005−17 laboratory surveillance data and sentinel data. For RSV seasonality evaluation, epidemic thresholds (i) at 1.2% of the cumulative number of RSV-positive patients per season and (ii) at 20 detections per week (for laboratory data) were employed. We also assessed MEM thresholds. RESULTS: In laboratory data RSV was reported 25,491 times (no denominator). In sentinel data 5.6% (767/13,577) of specimens tested RSV positive. Over 12 seasons, sentinel data showed percentage increases of RSV positive samples. The average epidemic length was 18.0 weeks (95% confidence intervals (CI): 16.3–19.7) and 16.5 weeks (95% CI: 14.0–18.0) for laboratory and sentinel data, respectively. Epidemics started on average in week 46 (95% CI: 45–48) and 47 (95% CI: 46–49), respectively. The peak was on average in the first week of January in both datasets. MEM showed similar results to the other methods. RSV incidence was highest in youngest (0–1 and >1–2 years) and oldest (>65–75 and > 75 years) age groups, with age distribution remaining stable over time. RSV-type dominance alternated every one or two seasons. CONCLUSIONS: Our findings provide baseline information for immunisation advisory groups. The possibility of employing MEM to monitor RSV epidemics allows prospective, nearly real-time use of surveillance data. |
---|