Sentence examples for flu curve from inspiring English sources

NLS estimates suggest that each additional nomination shifts the flu curve left by 5.7 days (95% C.I. 3.6 8.1) for flu diagnoses by medical staff and 8.0 days (95% C.I. 7.3 8.5) for self-reported symptoms.

NLS estimates suggest that individuals with minimum observed transitivity shift the flu curve left by 31.9 days (95% C.I. 23.5 43.5) for flu diagnoses by medical staff and 15.0 days (95% C.I. 12.7 18.5) for self-reported symptoms compared to those with maximum transitivity.

NLS estimates suggest that individuals with maximum observed centrality shift the flu curve left by 16.5 days (95% C.I. 1.9 28.3) for flu diagnoses by medical staff and 22.9 days (95% C.I. 20.0 27.2) for self-reported symptoms, relative to those with minimum centrality.

NLS estimates suggest that increasing the measure k by one (the range is from 0 to 3) shifts the flu curve left by 4.3 days (95% C.I. 1.8 6.5) for flu diagnoses by medical staff and 7.5 days (95% C.I. 6.8 8.2) for self-reported symptoms.

Deaths from pneumonia and the flu, a wavy curve that is low in summer and high in winter, typically touch the epidemic level for one or two weeks every flu season.

The retrospective period was the two week period that began three weeks before the ILI peak in a given flu season ILI curve; this period can only be identified retrospective to the epidemic peak.

The flow curves of FLU-unloaded MEs and FLU-loaded MEs are presented in Figure 5, in which the relation between the shear rate (Pa) and shear stress (1/s) evidenced that all ME's exhibited non-Newtonian "shear thinning" pseudoplastic flow behaviour.

NLS estimates suggest that the friends curve for flu diagnosed by medical staff is shifted 13.9 days forward in time (95% C.I. 9.9 16.6), thus providing early detection.

As can be seen in Figure 5, a notable thixotropic response was only observed for FLU-unloaded F3 and FLU-loaded F3, because the descending curve does not overlap with the ascending one.

The average reporting timeliness gaps for avian flu and H1N1 outbreaks showed a curved relationship with human development status.

The average reporting timeliness gaps for avian flu and H1N1 outbreaks also showed a curved relationship with the health workforce status.