This study provides new public health data about U.S. civil air shows. Risk factors for fatalities in civil air show crashes were analyzed. The value of the FIA score in predicting fatal outcomes was evaluated. With the use of the FAA’s General Aviation and Air Taxi Survey and the National Transportation Safety Board’s data, the incidence of civil air show crashes from 1993 to 2013 was calculated. Fatality risk factors for crashes were analyzed by means of regression methods. The FIA index was validated to predict fatal outcomes by using the factors of fire, instrument conditions, and away-from-airport location, and was evaluated through receiver operating characteristic (ROC) curves. The civil air show crash rate was 31 crashes per 1,000 civil air events. Of the 174 civil air show crashes that occurred during the study period, 91 (52%) involved at least one fatality; on average, 1.1 people died per fatal crash. Fatalities were associated with four major risk factors: fire [adjusted odds ratio (AOR) = 7.1, 95% confidence interval (CI) = 2.4 to 20.6, P < .001], pilot error (AOR = 5.2, 95% CI = 1.8 to 14.5, P = .002), aerobatic flight (AOR = 3.6, 95% CI = 1.6 to 8.2, P = .002), and off-airport location (AOR = 3.4, 95% CI = 1.5 to 7.5, P = .003). The area under the FIA score’s ROC curve was 0.71 (95% CI = 0.64 to 0.78). Civil air show crashes were marked by a high risk of fatal outcomes to pilots in aerobatic performances but rare mass casualties. The FIA score was not a valid measurement of fatal risk in civil air show crashes.

We evaluated the performance of X-bar chart, exponentially weighted moving average, and C3 cumulative sums aberration detection algorithms for acute diarrheal disease syndromic surveillance at naval sites in Peru during 2007–2011. The 3 algorithms’ detection sensitivity was 100%, specificity was 97%–99%, and positive predictive value was 27%–46%.

S yndromic surveillance uses prediagnostic healthrelated data to signal probable outbreaks warranting public health response (1). Alerta and Vigila are internet-based syndromic surveillance systems successively implemented by Peru's navy (2-4). Among other disease syndromes, individual cases of acute diarrheal disease (ADD) are self-reported to healthcare workers at sites providing care for service members, dependents, and civilian employees. We assessed the performance of 3 ADD aberration detection algorithms in this resource-limited setting: X-bar chart, exponentially weighted moving average (EWMA), and Early Aberration Reporting System (EARS) C3 cumulative sums (CUSUM) models (5-9).

Vigila is a national electronic surveillance system implemented by the Peruvian Navy in order to monitor infectious diseases. Vigila includes 169 reporting establishments, which treat active military, retired military, dependents, and civilian employees. The goal of this study was to establish baselines of acute diarrheal disease in the Peruvian Navy and detect outbreaks of acute diarrheal disease from 2009-2013. There were 39,764 cases of acute diarrheal disease reported, and 25 outbreaks were detected using Exponentially Weighted Moving Average (EWMA) control charts. These analyses demonstrate the utility of syndromic surveillance in a resource-limited setting.