We systematically reviewed available evidence from Embase, Medline, and the Cochrane Library on diagnostic accuracy and clinical impact of commercially available rapid (results <3 hours) molecular diagnostics for respiratory viruses as compared to conventional molecular tests. Quality of included studies was assessed using the Quality Assessment of Diagnostic Accuracy Studies criteria for diagnostic test accuracy (DTA) studies, and the Cochrane Risk of Bias Assessment and Risk of Bias in Nonrandomized Studies of Interventions criteria for randomized and observational impact studies, respectively. Sixty-three DTA reports (56 studies) were meta-analyzed with a pooled sensitivity of 90.9% (95% confidence interval [CI], 88.7%-93.1%) and specificity of 96.1% (95% CI, 94.2%-97.9%) for the detection of either influenza virus (n = 29), respiratory syncytial virus (RSV) (n = 1), influenza virus and RSV (n = 19), or a viral panel including influenza virus and RSV (n = 14). The 15 included impact studies (5 randomized) were very heterogeneous and results were therefore inconclusive. However, we suggest that implementation of rapid diagnostics in hospital care settings should be considered.

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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.