31
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Simulated Anthrax Attacks and Syndromic Surveillance

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Bioterrorism surveillance systems can be assessed using modeling to simulate real-world attacks.

          Abstract

          We measured sensitivity and timeliness of a syndromic surveillance system to detect bioterrorism events. A hypothetical anthrax release was modeled by using zip code population data, mall customer surveys, and membership information from HealthPartners Medical Group, which covers 9% of a metropolitan area population in Minnesota. For each infection level, 1,000 releases were simulated. Timing of increases in use of medical care was based on data from the Sverdlovsk, Russia, anthrax release. Cases from the simulated outbreak were added to actual respiratory visits recorded for those dates in HealthPartners Medical Group data. Analysis was done by using the space-time scan statistic. We evaluated the proportion of attacks detected at different attack rates and timeliness to detection. Timeliness and completeness of detection of events varied by rate of infection. First detection of events ranged from days 3 to 6. Similar modeling may be possible with other surveillance systems and should be a part of their evaluation.

          Related collections

          Most cited references12

          • Record: found
          • Abstract: found
          • Article: not found

          The Sverdlovsk anthrax outbreak of 1979.

          In April and May 1979, an unusual anthrax epidemic occurred in Sverdlovsk, Union of Soviet Socialist Republics. Soviet officials attributed it to consumption of contaminated meat. U.S. agencies attributed it to inhalation of spores accidentally released at a military microbiology facility in the city. Epidemiological data show that most victims worked or lived in a narrow zone extending from the military facility to the southern city limit. Farther south, livestock died of anthrax along the zone's extended axis. The zone paralleled the northerly wind that prevailed shortly before the outbreak. It is concluded that the escape of an aerosol of anthrax pathogen at the military facility caused the outbreak.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            Syndromic Surveillance and Bioterrorism-related Epidemics

            To facilitate rapid detection of a future bioterrorist attack, an increasing number of public health departments are investing in new surveillance systems that target the early manifestations of bioterrorism-related disease. Whether this approach is likely to detect an epidemic sooner than reporting by alert clinicians remains unknown. The detection of a bioterrorism-related epidemic will depend on population characteristics, availability and use of health services, the nature of an attack, epidemiologic features of individual diseases, surveillance methods, and the capacity of health departments to respond to alerts. Predicting how these factors will combine in a bioterrorism attack may be impossible. Nevertheless, understanding their likely effect on epidemic detection should help define the usefulness of syndromic surveillance and identify approaches to increasing the likelihood that clinicians recognize and report an epidemic.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              A model-adjusted space-time scan statistic with an application to syndromic surveillance.

              The space-time scan statistic is often used to identify incident disease clusters. We introduce a method to adjust for naturally occurring temporal trends or geographical patterns in illness. The space-time scan statistic was applied to reports of lower respiratory complaints in a large group practice. We compared its performance with unadjusted populations from: (1) the census, (2) group-practice membership counts, and on adjustments incorporating (3) day of week, month, and holidays; and (4) additionally, local history of illness. Using a nominal false detection rate of 5%, incident clusters during 1 year were identified on 26, 22, 4 and 2% of days for the four populations respectively. We show that it is important to account for naturally occurring temporal and geographic trends when using the space-time scan statistic for surveillance. The large number of days with clusters renders the census and membership approaches impractical for public health surveillance. The proposed adjustment allows practical surveillance.
                Bookmark

                Author and article information

                Journal
                Emerg Infect Dis
                Emerging Infect. Dis
                EID
                Emerging Infectious Diseases
                Centers for Disease Control and Prevention
                1080-6040
                1080-6059
                September 2005
                : 11
                : 9
                : 1394-1398
                Affiliations
                [* ]HealthPartners Research Foundation, Minneapolis, Minnesota, USA;
                []Harvard Medical School, Boston, Massachusetts, USA;
                []Harvard Pilgrim Health Care, Boston, Massachusetts, USA;
                [§ ]Kaiser Permanente, Boulder, Colorado, USA;
                []Marshfield Clinic Research Foundation, Marshfield, Wisconsin, USA
                Author notes
                Address for correspondence: James D. Nordin, HealthPartners Research Foundation, 8100 34th Ave South, Mailstop 21111R, Minneapolis, MN 55440-1524, USA; fax: 952- 967-5022; email: james.d.nordin@ 123456healthpartners.com
                Article
                05-0223
                10.3201/eid1109.050223
                3310627
                16229768
                601b8630-ec4f-4c0a-b7e3-2497ce8e8106
                History
                Categories
                Research
                Research

                Infectious disease & Microbiology
                bioterrorism,minnesota,managed care programs,anthrax,population surveillance,statistical models,research

                Comments

                Comment on this article