Objective: To study ambulance transfers in Tokyo as a potential source of Syndromic Surveillance, and examine the possibility of practical application from a statistical view point. Method and Material: The Tokyo Fire Department has recorded the chief complaints of ambulance transferred patients for more than 10 years. We use the number of patients transferred by ambulance due to fever from January 1st, 1995 to December 31st, 2004. We perform the calculations prospectively for days after January 1st, 2000. Meaning, we estimate the baseline from January 1st, 1995 to the day before any given day. Then we predict the number of ambulance transfers in that day. An outbreak is detected if the actual number is larger than the estimated by three times the standard deviation of residuals. So as to check sensitivity and specificity, we add artificial transfers to the data and judge whether they are detected or not. Results: In an average city, we found outbreaks at 1.1%, i.e. a few times a year. However, it rises to 39.7%, i.e. once every two and a half days, in the whole of Tokyo. Specificity in the whole of Tokyo or other urban areas is high and an outbreak is not detected in the case of only one additional patient being transferred. Sensitivity is also high because an outbreak can be detected even if there are only 5 victims of a bioterrorist attack. Discussion: We can evaluate that this system has a high ability to detect outbreaks. However, so as to raise precision and specificity without losing sensitivity, we should use other syndromic surveillance monitoring or monitor other aspects besides ambulance transfers at the same time. The information on ambulance transfers is already electronically recorded. Therefore, if we can add an analytical tool such as the one described in this paper to the system, we can operate a system of syndromic surveillance which covers the largest population in the world. Since its usefulness is confirmed in this paper, we hope the local government of Tokyo will adopt and operate this system as a counter measure for bioterrorism attacks.
View full abstract