Automatic Outbreak Detection Algorithm versus Electronic Reporting System
To determine efficacy of automatic outbreak detection algorithms (AODAs), we analyzed 3,582 AODA signals and 4,427 reports of outbreaks caused by Campylobacter spp. or norovirus during 2005–2006 in Germany. Local health departments reported local outbreaks with higher sensitivity and positive predic...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Centers for Disease Control and Prevention
2008-10-01
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| Series: | Emerging Infectious Diseases |
| Subjects: | |
| Online Access: | https://wwwnc.cdc.gov/eid/article/14/10/07-1354_article |
| _version_ | 1818261680094707712 |
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| author | Masja Straetemans Doris Altmann Tim Eckmanns Gérard Krause |
| author_facet | Masja Straetemans Doris Altmann Tim Eckmanns Gérard Krause |
| author_sort | Masja Straetemans |
| collection | DOAJ |
| description | To determine efficacy of automatic outbreak detection algorithms (AODAs), we analyzed 3,582 AODA signals and 4,427 reports of outbreaks caused by Campylobacter spp. or norovirus during 2005–2006 in Germany. Local health departments reported local outbreaks with higher sensitivity and positive predictive value than did AODAs. |
| first_indexed | 2024-12-12T18:51:04Z |
| format | Article |
| id | doaj.art-80c530e9e460414b96c3c2ce4fc72766 |
| institution | Directory Open Access Journal |
| issn | 1080-6040 1080-6059 |
| language | English |
| last_indexed | 2024-12-12T18:51:04Z |
| publishDate | 2008-10-01 |
| publisher | Centers for Disease Control and Prevention |
| record_format | Article |
| series | Emerging Infectious Diseases |
| spelling | doaj.art-80c530e9e460414b96c3c2ce4fc727662022-12-22T00:15:23ZengCenters for Disease Control and PreventionEmerging Infectious Diseases1080-60401080-60592008-10-0114101610161210.3201/eid1410.071354Automatic Outbreak Detection Algorithm versus Electronic Reporting SystemMasja StraetemansDoris AltmannTim EckmannsGérard KrauseTo determine efficacy of automatic outbreak detection algorithms (AODAs), we analyzed 3,582 AODA signals and 4,427 reports of outbreaks caused by Campylobacter spp. or norovirus during 2005–2006 in Germany. Local health departments reported local outbreaks with higher sensitivity and positive predictive value than did AODAs.https://wwwnc.cdc.gov/eid/article/14/10/07-1354_articleinfectious disease reportingcommunicable disease controlalgorithmsoutbreakscampylobacternorovirus |
| spellingShingle | Masja Straetemans Doris Altmann Tim Eckmanns Gérard Krause Automatic Outbreak Detection Algorithm versus Electronic Reporting System Emerging Infectious Diseases infectious disease reporting communicable disease control algorithms outbreaks campylobacter norovirus |
| title | Automatic Outbreak Detection Algorithm versus Electronic Reporting System |
| title_full | Automatic Outbreak Detection Algorithm versus Electronic Reporting System |
| title_fullStr | Automatic Outbreak Detection Algorithm versus Electronic Reporting System |
| title_full_unstemmed | Automatic Outbreak Detection Algorithm versus Electronic Reporting System |
| title_short | Automatic Outbreak Detection Algorithm versus Electronic Reporting System |
| title_sort | automatic outbreak detection algorithm versus electronic reporting system |
| topic | infectious disease reporting communicable disease control algorithms outbreaks campylobacter norovirus |
| url | https://wwwnc.cdc.gov/eid/article/14/10/07-1354_article |
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