Forecast accuracy versus ensemble spread.

<p>The ensemble spread is presented as the percentage of ensemble members predicting the mode peak week (PEMPM). Red lines are generated using the EAKF and blue lines using the PF; solid lines show forecast accuracies for peak timing (within ±1 week of observation); dashed lines show forecast accuracies for peak magnitude (within ±20% of observation). The filled circle size associated with each PEMPM bin represents the fraction of forecasts within each lead category.</p

Accuracy predicting outbreak peak timing (A), peak magnitude (B), onset (C), and duration (D).

<p>Accuracy was calculated over all forecasts (332,400 for each setting of the forecast system). This analysis includes the forecasts for seasonal H1N1, the 2009 pandemic H1N1, H3N2, B and all strains combined. Results are shown for the EAKF (red) and the PF (blue), evaluated using two standards (solid vs. dashed lines, as specified in the parentheses). On the x-axis, positive leads indicate that a peak is forecast in the future; negative leads indicate that a peak is forecast in the past; a 0 week lead indicates that a peak is forecast as the same week of forecast. Leads are relative to the predicted peak for forecasts of the peak timing, peak magnitude, and duration, and relative to the predicted onset for forecasts of onset timing.</p

Performance of the SIR-EAKF (A and B) and the SIR-PF (C and D) for individual strains predictions of peak timing (A and C) and magnitude (B and D).

<p>Performance of the SIR-EAKF (A and B) and the SIR-PF (C and D) for individual strains predictions of peak timing (A and C) and magnitude (B and D).</p

Comparison of forecast accuracy for Hong Kong (HK) and New York City (NYC) using the EAKF and PF filters, as well as random sampling from historical records for HK.

<p>Forecast accuracy was evaluated by grouping predictions based on (A) predicted lead time (i.e. how far in the future the peak is predicted) or (B) actual forecast week relative to the observed peak. Positive leads indicate that a peak is forecast in the future; negative leads indicate that a peak is forecast in the past; a 0 week lead indicates that a peak is forecast for the week of forecast initiation.</p

Accuracy predicting gross epidemic activity.

<p>Four measures, sensitivity (i.e., true positive rate, TPR), specificity (i.e., true negative rate, SPC), precision (i.e., positive predictive value, PPV), and negative predictive value (NPV) are shown for (A) the SIR-EAKF and (B) the SIR-PF forecast system. Results are tallied over forecast of H1N1 (orange), H3N2 (red), Type B (green), all strains combined time series (blue), and all forecasts (white).</p

Ice Bucket Challenge analysis data

Ice Bucket Challenge analysis dat

Comparison of inferred trend from individual surveillance data and from model based on GOPC ILI rate, GP ILI rate and school absenteeism rate with changes in influenza activity^*.

<p>DFC, designated fever clinic; GOPC, general outpatient clinic; GP, general practitioner; ILI, influenza-like-illness.</p>*<p>Influenza activity measured by GP ILI consultation rate×laboratory influenza isolation rate.</p>†<p>Correlations between surveillance data and the log ratios were calculated by fitting a univariate dynamic linear model to each data stream, and an overall multivariate model to all data streams. DFC was excluded from the analysis due to insufficient data for estimation of the inferred trend.</p>‡<p>GOPC data were interrupted during the pandemic period due to the opening of designated flu clinics.</p>§<p>School absenteeism data were occasionally interrupted by school holidays or school closures. Data during the summer holidays were excluded.</p

Estimated effects of age and weight on blood demand, based on the fitted Poisson generalized estimating equations model.

<p>Estimated effects of age and weight on blood demand, based on the fitted Poisson generalized estimating equations model.</p

Predicted blood demand and prediction intervals of Thalamessia Major patients, 2010–2024. Crosses show the actual blood demand in 2005–2009.

<p>Predicted blood demand and prediction intervals of Thalamessia Major patients, 2010–2024. Crosses show the actual blood demand in 2005–2009.</p

Box-plot of inferred influenza level and trend based on multivariate dynamic linear model utilizing four surveillance data streams including influenza-like illness consultation rates in public General Outpatient Clinics (GOPC) and private general practitioners (GP), school absenteeism rates, and number of consultations with patients with febrile illness in Designated Flu Clinics, under different patterns of influenza activity.

<p>Influenza activity was defined as low, medium or high if it is lower than 0.5%, between 0.5–2%, or higher than 2% respectively, defined as decreasing, stable or increasing if the percentage change between the following and preceding week is lower than −30%, between −30–30% or higher than 30% respectively. The inferred influenza level was scaled to the range of the influenza activity proxy measure (product of laboratory influenza isolation rate and GP ILI rate), while the inferred trend of influenza activity under the same model was scaled to the range [−1, 1].</p