The effect of modifi cations of the initial algorithm on the sensitivity for detecting additional counts was examined; each modifi cation was added consecutively (Table  3) . For the DoD data, sensitivity was 40.6% for the initial algorithm and increased to 43.9% when the rate method was used; 70.8% when the minimum SD was increased to 1.0; 79.4% when the baseline duration was increased to 28 days; and 82.0% when a stratifi ed baseline was used. Comparing the initial algoithm to the best algorithm showed a 41.4% increase in sensitivity. For the hospital ED data, sensitivity was 40.2% for the initial algorithm and increased to 64.8% for the best method (minimum SD = 1, 28-day baseline, rate method, unstratifi ed baseline); however, when the stratifi ed baseline was used, sensitivity decreased to 62.1%; the initial algorithm compared with the best algorithm showed a 24.6% increase in sensitivity. When these sensitivity calculations were stratifi ed by mean count for each facility-syndrome (data not shown), we found that the modifi cations increased sensitivity in all strata of the DoD data; for the hospital ED data, the rate method reduced sensitivity by 1.0% in the 8 to <10 count category and by 0.5% in the 10 to <20 count category, but increased sensitivity in other categories and overall. When we limited analysis to ED data with a mean count of 4 to <6 per day and explored sensitivity for detecting varying numbers of additional counts (Figure 2 ), we found, as expected, that as the number of additional counts increased, sensitivity increased. The difference between the initial and best algorithms was highest when sensitivity was ≈50% for the initial algorithm. That is, for 10 additional counts, sensitivity was 49.8% for the initial algorithm and 85.3% for the best algorithm, an improvement of 35.5%. However, if the initial C2 algorithm had either low or high sensitivity, the modifi cations had little effect.