Simulated Anthrax Attacks and Syndromic Surveillance
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 metropolita...
| Main Authors: | , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Centers for Disease Control and Prevention
2005-09-01
|
| Series: | Emerging Infectious Diseases |
| Subjects: | |
| Online Access: | https://wwwnc.cdc.gov/eid/article/11/9/05-0223_article |
| _version_ | 1817991200957792256 |
|---|---|
| author | James D. Nordin Michael J. Goodman Martin Kulldorff Debra P. Ritzwoller Allyson M. Abrams Ken Kleinman Mary Jeanne Levitt James Donahue Richard Platt |
| author_facet | James D. Nordin Michael J. Goodman Martin Kulldorff Debra P. Ritzwoller Allyson M. Abrams Ken Kleinman Mary Jeanne Levitt James Donahue Richard Platt |
| author_sort | James D. Nordin |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-04-14T01:10:05Z |
| format | Article |
| id | doaj.art-334a89ab39e44fc799b34e540957486b |
| institution | Directory Open Access Journal |
| issn | 1080-6040 1080-6059 |
| language | English |
| last_indexed | 2024-04-14T01:10:05Z |
| publishDate | 2005-09-01 |
| publisher | Centers for Disease Control and Prevention |
| record_format | Article |
| series | Emerging Infectious Diseases |
| spelling | doaj.art-334a89ab39e44fc799b34e540957486b2022-12-22T02:21:07ZengCenters for Disease Control and PreventionEmerging Infectious Diseases1080-60401080-60592005-09-011191394139810.3201/eid1109.050223Simulated Anthrax Attacks and Syndromic SurveillanceJames D. NordinMichael J. GoodmanMartin KulldorffDebra P. RitzwollerAllyson M. AbramsKen KleinmanMary Jeanne LevittJames DonahueRichard PlattWe 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.https://wwwnc.cdc.gov/eid/article/11/9/05-0223_articleAnthraxbioterrorismmanaged care programsMinnesotastatistical modelspopulation surveillance |
| spellingShingle | James D. Nordin Michael J. Goodman Martin Kulldorff Debra P. Ritzwoller Allyson M. Abrams Ken Kleinman Mary Jeanne Levitt James Donahue Richard Platt Simulated Anthrax Attacks and Syndromic Surveillance Emerging Infectious Diseases Anthrax bioterrorism managed care programs Minnesota statistical models population surveillance |
| title | Simulated Anthrax Attacks and Syndromic Surveillance |
| title_full | Simulated Anthrax Attacks and Syndromic Surveillance |
| title_fullStr | Simulated Anthrax Attacks and Syndromic Surveillance |
| title_full_unstemmed | Simulated Anthrax Attacks and Syndromic Surveillance |
| title_short | Simulated Anthrax Attacks and Syndromic Surveillance |
| title_sort | simulated anthrax attacks and syndromic surveillance |
| topic | Anthrax bioterrorism managed care programs Minnesota statistical models population surveillance |
| url | https://wwwnc.cdc.gov/eid/article/11/9/05-0223_article |
| work_keys_str_mv | AT jamesdnordin simulatedanthraxattacksandsyndromicsurveillance AT michaeljgoodman simulatedanthraxattacksandsyndromicsurveillance AT martinkulldorff simulatedanthraxattacksandsyndromicsurveillance AT debrapritzwoller simulatedanthraxattacksandsyndromicsurveillance AT allysonmabrams simulatedanthraxattacksandsyndromicsurveillance AT kenkleinman simulatedanthraxattacksandsyndromicsurveillance AT maryjeannelevitt simulatedanthraxattacksandsyndromicsurveillance AT jamesdonahue simulatedanthraxattacksandsyndromicsurveillance AT richardplatt simulatedanthraxattacksandsyndromicsurveillance |