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Volume 15, Number 11—November 2009
Dispatch

Evidence-based Tool for Triggering School Closures during Influenza Outbreaks, Japan

Asami SasakiComments to Author , Anne Gatewood Hoen, Al Ozonoff, Hiroshi Suzuki, Naohito Tanabe, Nao Seki, Reiko Saito, and John S. Brownstein
Author affiliations: Harvard School of Public Health, Boston, Massachusetts, USA (A. Sasaki); University of Niigata Prefecture, Niigata, Japan (A. Sasaki); Children’s Hospital, Boston (A. Gatewood Hoen, J.S. Brownstein); Harvard Medical School, Boston (A. Gatewood Hoen, J.S. Brownstein); Boston University School of Public Health, Boston (A. Ozonoff); Niigata University Graduate School of Medical and Dental Sciences, Niigata (H. Suzuki, N. Tanabe, N. Seki, R. Saito)

Main Article

Figure 2

The receiver operating characteristic (ROC) curve for detection of influenza outbreak by 1%–9% thresholds under single-day, double-day, triple-day scenarios. ROC space is defined on the x axis as 1 – specificity and on the y axis as sensitivity. The area under the curve (AUC) is an indicator of the quality of a model; larger AUC values corresponded to better performance. Optimal thresholds for the 3 scenarios are *single-day, 5%; †double-day, 4%; and ‡triple-day, 3%.

Figure 2. The receiver operating characteristic (ROC) curve for detection of influenza outbreak by 1%–9% thresholds under single-day, double-day, triple-day scenarios. ROC space is defined on the x axis as 1 – specificity and on the y axis as sensitivity. The area under the curve (AUC) is an indicator of the quality of a model; larger AUC values corresponded to better performance. Optimal thresholds for the 3 scenarios are *single-day, 5%; †double-day, 4%; and ‡triple-day, 3%.

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