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Persons using assistive technology might not be able to fully access information in this file. For assistance, please send e-mail to: mmwrq@cdc.gov. Type 508 Accommodation and the title of the report in the subject line of e-mail. Syndromic Surveillance for Early Location of Terrorist Incidents Outside of Residential AreasManfred S. Green,1,2 Z. Kaufman1
Corresponding author: Manfred S. Green, Israel Center for Disease Control, Gertner Institute, Sheba Medical Center, Tel Hashomer, Israel 52621. Telephone: 972-3-737-1500; Fax: 972-3-737-1515; E-mail: m.green@icdc.health.gov.il. Disclosure of relationship: The contributors of this report have disclosed that they have no financial interest, relationship, affiliation, or other association with any organization that might represent a conflict of interest. In addition, this report does not contain any discussion of unlabeled use of commercial products or products for investigational use. AbstractIntroduction: A terrorist attack might occur at places outside of residential areas (e.g., workplace, entertainment venues, or shopping centers). Cluster analysis using available data on residential addresses alone will not yield the probable place of exposure. Objectives: The study aimed to facilitate early detection of terrorist incidents in areas outside of residential areas (e.g., workplaces and shopping centers). Methods: An approach was suggested for estimating the probable location of exposure on the basis of the distribution of the residential addresses on the assumption that persons tend to live closer to their place of work, or visit entertainment venues or shopping centers closer to their place of residence than would be expected by chance. A two-stage process of implementing available spatial statistics programs was proposed. In the first stage, a cluster analysis program was employed by using residential addresses. The SaTScan software, developed at the National Cancer Institute, was used with its space-time permutation model specifically developed for conducting continuous surveillance. If more than one substantial cluster is identified, a possible incident outside of the residential area was considered. The mean center and standard deviation are computed for those census tracts included in the substantial clusters to identify the area where the exposure might have occurred. For this task, the CrimeStat II was used, a spatial statistic program originally developed for analysis of crime locations. To narrow potential places of exposure, the cluster analysis should be performed in the first stage by age groups such as infants, children, persons aged <19 years, the working age category (19--65 years), and older persons (>65 years). Substantial clusters in the working age category alone could focus the resulting investigation on workplaces. A geographical information system (GIS) program (ArcGIS, ESRI, Redlands, California) was used for geocoding addresses and for other procedures needed to prepare data for cluster analysis and for presenting the results. This approach was demonstrated through a series of simulations of deliberate dispersion of anthrax spores in a large hospital where residential addresses of all the staff members were available. Simulated cases among the staff were superimposed on background data of patient visits to community clinics for influenza-like illness. Results: A possible place of exposure was identified at a distance of approximately 1 kilometer from the hospital Conclusion: The combination of multiple spatial statistics tools demonstrates promising capabilities for identifying terrorist incidents outside of residential areas, even when only residential addresses are available.
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