The mean timeliness was defined as the mean number of complete days that occurred between the beginning of an outbreak and the first day the outbreak was flagged.
Mr. Daisey has been performing this show since July of last year, and while the death of Mr. Jobs lends the evening a certain eerie timeliness, it also means that many in the audience will be familiar with the life and career of Mr. Jobs from reading obituaries and tributes.
We use the delay constraint to indicate the correspondence transmission timeliness metric, which means the maximum allowable transmission delay of a data packet from source to destination.
A paired t test showed that, for each false alarm rate, the mean timeliness of BARD-C was statistically different from the mean timeliness of BARD, at the 0.05 significance level.
Mean timeliness across the scenarios examined was associated with the mean number infected (Pearson's r -0.94, 95% confidence interval -0.98 to -0.79), and an increase of 10,000 infected persons resulted in a decrease in the time until detection of ≈4 hours.
As shown, in Figure 4(a), BARD's mean timeliness over the commuting group is nearly one hour greater than its mean timeliness over the non-commuting group, at each false alarm rate.
Two detection algorithms presented a specificity higher than 85% with a satisfactory mean timeliness: C2, k = 0.07 and 3 days (sensitivity: 100%, specificity: 87.7%, and mean timeliness = 0.5) and C2, k = 0.1 and 3 days (sensitivity: 100%, specificity: 88.0%, and mean timeliness = 0.8).
From the results shown in Table 2 it can be concluded that, at each shown false alarm rate, the mean timeliness, x error, and y error over the non-commuting group are statistically different from the respective means over the commuting group, at the 0.05 significance level.
The best balance between specificity and mean timeliness was obtained with ICD10-consultations series: C2, k = 0.07, 1d (sensitivity = 100%, specificity = 95.7%, and mean timeliness = −1.7 day).
Negative mean timeliness: first day signal before the outbreaks beginning, on average.
