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Volume 10, Number 7—July 2004
Research

Alert Threshold Algorithms and Malaria Epidemic Detection

Hailay Desta Teklehaimanot*, Joel Schwartz*, Awash Teklehaimanot†, and Marc Lipsitch*
Author affiliations: *Harvard School of Public Health, Boston, Massachusetts, USA; †Columbia University, New York, New York, USA

Main Article

Figure 2

Percent of potentially preventable cases (PPC) by number of alerts per year for different algorithms. (A) and (B) were obtained from cases in excess of the weekly mean with window of effectiveness of 8 and 24 weeks, respectively. (C) and (D) were obtained from cases in excess of the weekly mean minus one SD for window of 8 and 24 weeks, respectively. The scale of y-axis is higher for (B) and (D) because they are based on 24 weeks of PPC (based on the random alert, the %PPC for the 24-week window

Figure 2. Percent of potentially preventable cases (PPC) by number of alerts per year for different algorithms. (A) and (B) were obtained from cases in excess of the weekly mean with window of effectiveness of 8 and 24 weeks, respectively. (C) and (D) were obtained from cases in excess of the weekly mean minus one SD for window of 8 and 24 weeks, respectively. The scale of y-axis is higher for (B) and (D) because they are based on 24 weeks of PPC (based on the random alert, the %PPC for the 24-week window is three times that of the 8-week window of effectiveness).

Main Article

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